CN112954060A

CN112954060A - Data analysis method and device, electronic equipment and storage medium

Info

Publication number: CN112954060A
Application number: CN202110191935.2A
Authority: CN
Inventors: 张磊; 陈宏君; 刘坤; 李响; 文继锋; 刘宁; 韩科文; 赵奎
Original assignee: NR Electric Co Ltd; NR Engineering Co Ltd
Current assignee: NR Electric Co Ltd; NR Engineering Co Ltd
Priority date: 2021-02-19
Filing date: 2021-02-19
Publication date: 2021-06-11
Anticipated expiration: 2041-02-19
Also published as: CN112954060B

Abstract

The embodiment of the application discloses a data analysis method, a data analysis device, electronic equipment and a storage medium, wherein the method comprises the following steps: acquiring a first task chain and a second task chain to be detected; determining a cyclic redundancy check, CRC, 1 for the first task chain based on the first data flow network for the first task chain; determining a CRC2 for the second task chain based on the second data stream network for the second task chain; and under the condition that the CRC1 is consistent with the CRC2, analyzing the data dependency relationship existing in the first data stream network and the second data stream network to determine whether the logic functions of the first task chain and the second task chain are consistent. In this way, the task chains before and after modification are taken as a whole to respectively calculate the CRC1 and the CRC2, and when the CRC1 and the CRC2 are consistent, whether the logic functions of the task chains before and after modification are consistent can be determined by analyzing the data dependency existing in the data stream network, so that the technical problem that whether the logic functions of the task chains before and after modification are consistent cannot be analyzed from a macro level in the related art is solved.

Description

Data analysis method and device, electronic equipment and storage medium

Technical Field

The present application relates to the field of visual programming technologies, and in particular, to a data analysis method and apparatus, an electronic device, and a storage medium.

Background

In the process of upgrading and maintaining the direct current control protection visual engineering, the difference before and after modification needs to be analyzed, and then whether the modification has the change of logic functions or not is analyzed. However, the existing analysis and comparison method mainly performs page-by-page comparison and analysis by taking a page as a unit, and forms a call chain by taking an output symbol as a keyword in a single page to perform matching and comparison.

Although the above analysis and comparison method can accurately determine the situations of addition and deletion of symbols in a page and modification of links, the analysis and comparison method for a simple page cannot meet the requirement of analyzing whether logic functions are consistent from a macro level for some special situations, such as the situation that a local visualization program is migrated from a page a to a page B.

Disclosure of Invention

The application provides a data analysis method, a data analysis device, an electronic device and a storage medium, and whether the logic functions of the task chains before and after modification are consistent or not is analyzed by taking the task chains as a whole, so that the accuracy of upgrading and maintaining the visual engineering can be improved.

The technical scheme of the application is realized as follows:

in a first aspect, an embodiment of the present application provides a data analysis method, where the method includes:

acquiring a first task chain and a second task chain to be detected;

determining a Cyclic Redundancy Check (CRC) 1 for the first task chain based on a first data flow network of the first task chain;

determining 2 a CRC for the second task chain based on a second data stream network of the second task chain;

in the case that the CRC1 is consistent with the CRC2, analyzing data dependencies existing in the first data stream network and the second data stream network to determine whether logical functions of the first task chain and the second task chain are consistent.

In a second aspect, an embodiment of the present application provides a data analysis apparatus, including: an acquisition unit, a determination unit, and an analysis unit, wherein,

the acquisition unit is used for acquiring a first task chain and a second task chain to be detected;

the determining unit is configured to determine CRC1 of the first task chain based on a first data flow network of the first task chain; and determining a CRC2 for the second task chain based on a second data stream network of the second task chain;

the analysis unit is configured to, if the CRC1 is consistent with the CRC2, analyze data dependencies existing in the first data stream network and the second data stream network to determine whether logical functions of the first task chain and the second task chain are consistent.

In a third aspect, an embodiment of the present application provides an electronic device, including: a memory and a processor; wherein,

the memory for storing a computer program operable on the processor;

the processor is configured to perform the steps of the data analysis method according to the first aspect when running the computer program.

In a fourth aspect, the present application provides a computer storage medium storing a computer program, which when executed by at least one processor implements the steps of the data analysis method according to the first aspect.

According to the data analysis method, the data analysis device, the electronic equipment and the storage medium, a first task chain and a second task chain to be detected are obtained; then determining a Cyclic Redundancy Check (CRC) 1 for the first task chain based on a first data flow network of the first task chain; and determining a CRC2 for the second task chain based on a second data stream network of the second task chain; and analyzing the data dependency relationship existing in the first data stream network and the second data stream network to determine whether the logic functions of the first task chain and the second task chain are consistent under the condition that the CRC1 is consistent with the CRC 2. Therefore, the task chains are used as a whole to respectively calculate the CRC1 and the CRC2, and when the CRC1 is consistent with the CRC2, whether the logic functions of the first task chain and the second task chain are consistent can be determined by analyzing the data dependence relation existing in the data stream network, so that the technical problem that whether the logic functions of the task chains are consistent in the analysis from a macro level in the related technology can be solved, and meanwhile, the accuracy of upgrading and maintaining of visual engineering is improved.

Drawings

Fig. 1 is a schematic flow chart of a data analysis method according to an embodiment of the present application;

fig. 2 is a schematic flowchart of determining CRC1 of a first task chain according to an embodiment of the present disclosure;

fig. 3 is a schematic flowchart of determining CRC2 of a second task chain according to an embodiment of the present disclosure;

FIG. 4 is a schematic flowchart of a task chain logical function consistency analysis according to an embodiment of the present disclosure;

fig. 5A is a schematic diagram illustrating a task chain execution position change according to an embodiment of the present application;

FIG. 5B is a schematic diagram illustrating another example of a task chain execution location change according to an embodiment of the present disclosure;

FIG. 6 is a schematic flow chart diagram of another data analysis method provided in the embodiments of the present application;

fig. 7 is a schematic diagram illustrating task chain consistency determination based on a data flow subnetwork according to an embodiment of the present application;

fig. 8 is a schematic diagram illustrating another task chain consistency determination based on a data flow subnetwork according to an embodiment of the present application;

fig. 9 is a schematic structural diagram of a data analysis apparatus according to an embodiment of the present disclosure;

fig. 10 is a schematic diagram of a specific hardware structure of an electronic device according to an embodiment of the present disclosure.

Detailed Description

The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. It is to be understood that the specific embodiments described herein are merely illustrative of the relevant application and are not limiting of the application. It should be noted that, for the convenience of description, only the parts related to the related applications are shown in the drawings.

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of the present application only and is not intended to be limiting of the application.

In the following description, reference is made to "some embodiments" which describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict.

It should be noted that the terms "first \ second \ third" referred to in the embodiments of the present application are only used for distinguishing similar objects and do not represent a specific ordering for the objects, and it should be understood that "first \ second \ third" may be interchanged under specific ordering or sequence if allowed, so that the embodiments of the present application described herein can be implemented in other orders than illustrated or described herein.

In the related art, for the process of upgrading and maintaining the direct current control protection visual engineering, the difference before and after modification needs to be analyzed, and then whether the modification has the change of the logic function or not needs to be analyzed. The existing analysis and comparison method mainly uses a page as a unit to perform page-by-page comparison and analysis, and uses an output symbol as a keyword in a single page to form a calling chain for matching and comparison. Although the method can accurately judge the conditions of adding and deleting the symbols in the page and modifying the connecting lines. In actual engineering, however, some special cases are aimed at. For example, a situation that a local visualization program is migrated from a page a to a page B exists between pages in a task chain, and it is necessary to evaluate whether local network migration affects an overall logic function, but a simple page is relatively unable to meet the requirement. Therefore, there is a need for a method to analyze the impact of changes in information and execution order of various data flow sub-networks within a task chain on logical functions.

Based on this, the embodiments of the present application provide a data analysis method, and the basic idea of the method is: acquiring a first task chain and a second task chain to be detected; determining a CRC1 for the first task chain based on a first data flow network of the first task chain; determining 2 a CRC for the second task chain based on a second data stream network of the second task chain; and analyzing the data dependency relationship existing in the first data stream network and the second data stream network to determine whether the logic functions of the first task chain and the second task chain are consistent under the condition that the CRC1 is consistent with the CRC 2. Therefore, the task chains are used as a whole to respectively calculate the CRC1 and the CRC2, and when the CRC1 is consistent with the CRC2, whether the logic functions of the first task chain and the second task chain are consistent can be determined by analyzing the data dependence relation existing in the data stream network, so that the technical problem that whether the logic functions of the task chains are consistent in the analysis from a macro level in the related technology can be solved, and meanwhile, the accuracy of upgrading and maintaining of visual engineering is improved.

Embodiments of the present application will be described in detail below with reference to the accompanying drawings.

In an embodiment of the present application, referring to fig. 1, a flowchart of a data analysis method provided in an embodiment of the present application is shown. As shown in fig. 1, the method may include:

s101, a first task chain and a second task chain to be detected are obtained.

It should be noted that the method described in this embodiment may be applied to a device for dc control protection, and in the process of upgrading and maintaining a dc control protection visual project, the logical function consistency of the task chain before and after modification is analyzed and judged. Here, the device may be, for example, a smart terminal, a personal computer, an industrial modular computer, an industrial control device, an industrial server, a general-purpose server, a chassis, a screen cabinet, a substation, and the like, and the embodiment of the present application is not particularly limited.

It should be further noted that, in a possible implementation, the task chain before modification may be defined as a first task chain, and the task chain after modification may be defined as a second task chain; illustratively, the second task chain may be obtained after the data stream sub-network migration is performed on the first task chain.

In addition, when modifying the visualization program, sometimes a developer is required to modify the relevant program in an office area of a manufacturer and send the modified content to a field technical support staff, and then the field technical support staff modifies the relevant program according to the modified content sent by the manufacturer. Therefore, in another possible embodiment, the first task chain may also be a task chain of a visualization program modified by a manufacturer for a specific business requirement, and the second task chain may be a task chain of a visualization program modified by a field technical support person for the specific business requirement. That is, the following description will be made of the case where the first task chain and the second task chain are the task chains before and after modification, respectively, but the present embodiment is not particularly limited thereto.

S102, determining a CRC1 of the first task chain based on a first data flow network of the first task chain; and determining 2 a CRC for the second task chain based on a second data stream network of the second task chain.

It should be noted that a Cyclic Redundancy Check (CRC) is a commonly used check code having the capability of detecting and correcting errors, and is commonly used for data check of synchronous communication between the external memory and the computer. In addition, the cyclic redundancy check code may establish a convention relationship between data bits and check bits through some mathematical operation.

It should be further noted that, here, "determining the CRC1 of the first task chain based on the first data stream network of the first task chain" and "determining the CRC2 of the second task chain based on the second data stream network of the second task chain" may be performed simultaneously or sequentially in any order, and this embodiment of the present application is not specifically limited.

The method of determining CRC1 in this step is the same as the implementation of determining CRC 2. Here, taking determination of CRC1 as an example, referring to fig. 2, which shows a flowchart of determining CRC1 of a first task chain according to an embodiment of the present application, as shown in fig. 2, the method may include:

s10211, obtaining a data connection relation between at least one symbol of the initial page based on the initial page included in the first task chain.

It should be noted that, for a task chain including at least one page, in the embodiment of the present application, the task chain is taken as a whole, and the influence of the whole group of migration of the data stream sub-network between the pages of the task chain in the task chain on the logical function of the task chain can be analyzed.

Therefore, in the embodiment of the present application, first, pages included in the first task chain need to be read, where the pages included in the first task chain are referred to as initial pages; and acquiring a data connection relation between symbols in the initial page based on the initial page contained in the first task chain, wherein the symbols in the initial page can include but are not limited to input symbols, output symbols and one or more of various function block symbols. It will be appreciated that for the first task chain, it contains at least one number of symbols on the initial page.

S10212, extracting the input symbol in the initial page, taking the input symbol as a starting symbol, and performing depth-first traversal according to a data connection relation between at least one symbol of the initial page to obtain at least one first data stream sub-network.

It should be noted that, here, the input symbols in the initial page are extracted, and the extracted input symbols are used as starting symbols, and the symbols in the initial page are subjected to depth-first traversal according to the data connection relationship between the symbols to form at least one first data stream subnetwork.

S10213, sorting the at least one first data stream sub-network in descending order based on the symbol variable name of the input symbol to obtain the first data stream network.

It should be noted that, here, the symbol variable names of the input symbols in the data stream sub-networks are set as the Identity identification numbers (IDs) of the data stream sub-networks, and then all the first data stream sub-networks are arranged in a descending order according to the IDs of the input symbols, that is, the input symbols in each first data stream sub-network are arranged in a descending order according to the symbol variable names of the input symbols in each first data stream sub-network, so that a group of ordered first data stream sub-networks in the whole task chain can be obtained, and at this time, the ordered group of first data stream sub-networks arranged in the first task chain may be referred to as a first data stream network.

It is understood that in the embodiment of the present application, the first data stream network is an entirety of all the ordered first data stream subnetworks.

Further, in different initial pages of the first task chain, there may exist first data stream subnetworks with the same ID, and at this time, the data stream subnetworks with the same ID across the pages need to be spliced and merged; then, as described above, the data is sorted in descending order according to the ID thereof. Therefore, in some embodiments, when the number of the initial pages is at least two, the method may further include:

and if first input symbols with the same symbol variable names across the pages exist in at least two initial pages, splicing and merging the first data stream sub-networks to which the first input symbols belong according to the execution sequence of the at least two initial pages.

It should be noted that, in this embodiment of the present application, the first data stream subnetworks with the same ID across pages are merged and merged according to the execution order between the initial pages, that is, for the first data stream subnetwork in the first data stream subnetwork after merging, the first data stream subnetwork with the initial page that itself belongs to has the execution order before is still before when traversing after merging.

S10214, traversing at least one symbol in the first data stream network, and extracting first symbol information.

It should be noted that, in this step, each symbol in the first data stream network is traversed to extract symbol information for comparison, where the symbol information for comparison in the first data stream network is referred to as first symbol information. Specifically, the symbol information includes at least one of: the symbol type, the symbol variable name, the symbol variable value, the symbol variable description, the symbol variable type, the source output symbol type corresponding to the symbol input point and the source output point variable name.

S10215, determining a first information text of the first task chain based on the first symbol information.

It should be noted that, for a first data stream subnetwork, the information text is symbol information spliced in the sequence formed by the data connection relationship in the first data stream subnetwork. For the first task chain, the first information text is formed by splicing the information texts of all the first data stream sub-networks in the first data stream network. It can be understood that, for the first information text, since the first data stream network is obtained by sorting the IDs of the first data stream subnetworks in a descending order, the specific content of the first information text is also sorted in a descending order according to the IDs of the first data stream subnetworks.

S10216, calculating CRC1 of the first task chain based on the first information text.

It should be noted that the CRC obtained by calculating the first information text is CRC1 of the first task chain.

Thus, the CRC1 for the first task chain is obtained.

Similar to the step of determining CRC1, referring to fig. 3, which shows a flowchart of determining CRC2 of the second task chain according to the embodiment of the present application, as shown in fig. 3, the method may include:

s10221, obtaining a data connection relation between at least one symbol of the target page based on the target page included in the second task chain.

S10222, extracting the input symbol in the target page, taking the input symbol as a starting symbol, and performing depth-first traversal according to a data connection relation between at least one symbol of the target page to obtain at least one second data stream sub-network.

S10223, performing descending order arrangement on the at least one second data stream sub-network according to the symbol variable name of the input symbol to obtain the second data stream network.

S10224, traversing at least one symbol in the second data stream network, and extracting second symbol information.

S10225, determining a second information text of the second task chain based on the second symbol information.

S10226, calculating CRC2 of the second task chain based on the second information text.

In an embodiment of the present application, for at least one symbol in the second data stream network, the symbol information includes at least one of: the symbol type, the symbol variable name, the symbol variable value, the symbol variable description, the symbol variable type, the source output symbol type corresponding to the symbol input point and the source output point variable name.

In addition, in different target pages of the second task chain, there may exist first data stream subnetworks with the same ID, and at this time, the data stream subnetworks with the same ID across the pages also need to be spliced and merged; then, as described above, the data is sorted in descending order according to the ID thereof. Therefore, in some embodiments, when the number of the target pages is at least two, the method may further include: and if second input symbols with the same cross-page symbol variable names exist in at least two target pages, splicing and merging the sub-networks of the second data streams to which the cross-page second input symbols belong according to the execution sequence of the at least two target pages.

It should be noted that, for steps S10221 to S10226, the implementation mode is the same as steps S10211 to S10216, but different names are adopted for the same concept and are easy to distinguish, for example, a page included in the second task chain is called a target page, a data stream sub-network in the second task chain is called a second data stream sub-network, a data stream network in the second task chain is called a second data stream network, an input symbol in the second task chain with the same symbol variable name across pages is called a second input symbol, symbol information in the second task chain is called second symbol information, an information text of the second task chain is called a second information text, and the CRC2 of the second task chain is finally calculated. For specific description of the implementation steps, reference may be made to steps S10211 to S10216, which is not described in detail in this embodiment of the application.

To this end, the CRC1 of the first task chain and the CRC2 of the second task chain may be obtained.

S103, under the condition that the CRC1 is consistent with the CRC2, analyzing data dependency existing in the first data stream network and the second data stream network, and determining whether the logic functions of the first task chain and the second task chain are consistent.

It should be noted that, if CRC1 of the first task chain is consistent with CRC2 of the second task chain, it cannot be determined whether the logical functions of the first task chain are consistent with the logical functions of the second task chain, and whether the logical functions of the first task chain are consistent with the logical functions of the second task chain needs to be analyzed according to the data dependency existing in the first data stream sub-network and the data dependency existing in the second data stream sub-network.

Specifically, referring to fig. 4, a flowchart of a task chain logic function consistency analysis provided by an embodiment of the present application is shown. As illustrated in fig. 4, the method may include:

s1031, under the condition that the first data stream network and the second data stream network have a data dependency relationship, obtaining a first relative position of at least one pair of target data stream subnetworks having a data dependency relationship in the first task chain; and acquiring a second relative position of the at least one pair of target data stream sub-networks with data dependency relationship in the second task chain.

It should be noted that, taking the first task chain as an example, the criterion for whether the first data stream network has a data dependency relationship may be: for different initial pages PageA and PageB in the first task chain, if the symbol variable name of the output symbol of the page PageA is the same as the symbol variable name of the input symbol of the page PageB, a data dependency relationship exists between two first data stream subnetworks to which the two symbols with the same name belong, that is, the first data stream subnetworks have a data dependency relationship. It can be understood that, for the second task chain, the criterion whether the second data stream network has the data dependency relationship is the same as the criterion whether the first data stream network has the data dependency relationship, and only the corresponding required content is replaced by the corresponding content of the second task chain, so that the details are not repeated.

It is understood that in any task chain, the data stream subnetworks having data dependencies should be paired, and herein, a pair of data stream subnetworks having data dependencies is referred to as a target data stream subnetwork. For example, if there is a data dependency relationship between the data stream subnetworks Var3 and Var4 in a task chain, then Var3 and Var4 are a pair of target data stream subnetworks. For another example, if there is a data dependency relationship between the data flow subnetworks Var2 and Var4 and between the data flow subnetworks Var3 and Var4 in a task chain, there are two pairs of data flow subnetworks in the task chain, for example, the data flow subnetworks Var2 and Var4 are a pair of target data flow subnetworks, and the data flow subnetworks Var3 and Var4 are another pair of target data flow subnetworks.

It should be further noted that there may be one or more pairs of target data stream subnetworks in each of the first task chain and the second task chain, and since the first task chain and the second task chain represent task chains before and after modification, respectively, and this step is only performed when CRC1 is consistent with CRC2, for the first task chain and the second task chain, if there are one or more pairs of target data stream subnetworks, the target data stream subnetworks in the first task chain and the second task chain are consistent, that is, for any pair of target data stream subnetworks, the pair of target data stream subnetworks corresponds to a first relative position in the first task chain and a second relative position in the second task chain. So here is obtained a first relative position of at least one pair of target data stream sub-networks in which there is a data dependency in the first task chain; and a second relative position of the at least one pair of target data streaming subnetworks in the second task chain where data dependencies exist.

S1032, determining whether the logical functions of the first task chain and the second task chain are consistent based on the first relative position of the at least one pair of target data streaming subnetworks and the second relative position of the at least one pair of target data streaming subnetworks.

In some embodiments, determining whether the logical functions of the first task chain and the second task chain are consistent based on the first relative position of the at least one pair of target data flow subnetworks and the second relative position of the at least one pair of target data flow subnetworks may include:

if the first relative position and the second relative position corresponding to one pair of target data stream sub-networks are inconsistent, determining that the logic functions of the first task chain and the second task chain are inconsistent;

and if the first relative position and the second relative position corresponding to any pair of target data stream sub-networks are consistent, determining that the logic functions of the first task chain and the second task chain are consistent.

It should be noted that, since there may be multiple pairs of target data stream subnetworks in both the first task chain and the second task chain, when there is inconsistency between the first relative position and the second relative position corresponding to a certain pair of target data stream subnetworks, it can be determined that the logical functions of the first task chain and the second task chain are inconsistent; when the first relative position and the second relative position corresponding to each pair of target data stream subnetworks are consistent, the logical functions of the first task chain and the second task chain can be determined to be consistent.

It should be further noted that the first relative position and the second relative position corresponding to a pair of target data streaming subnetworks may be different from each other: there is a positive-negative change between the first and second relative positions corresponding to the pair of target data streaming subnetworks, and therefore,

in some embodiments, the determining whether the logical functions of the first task chain and the second task chain are consistent based on the first relative position of the at least one pair of target data flow subnetworks and the second relative position of the at least one pair of target data flow subnetworks may include:

if positive and negative direction changes exist between the first relative position and the second relative position corresponding to one pair of target data stream sub-networks, determining that the logic functions of the first task chain are inconsistent with the logic functions of the second task chain;

and if no positive and negative direction change exists between the first relative position and the second relative position corresponding to any pair of target data stream sub-networks, determining that the logic functions of the first task chain and the second task chain are consistent.

It should be noted that, a positive-negative direction change exists between the first relative position and the second relative position of the pair of target data stream subnetworks, that is, the relative position of the pair of target data stream subnetworks having a data dependency relationship changes in a positive-negative direction.

In some embodiments, the method may further comprise:

determining a first execution order and a first second execution order for each of a pair of target data streaming subnetworks in the first task chain, and a second first execution order and a second execution order for each of the pair of target data streaming subnetworks in the second task chain;

if the difference between the first execution order and the first second execution order is less than zero and the difference between the second execution order and the second execution order is greater than zero, or the difference between the first execution order and the first second execution order is greater than zero and the difference between the second execution order and the second execution order is less than zero, it is determined that there is a positive-negative change between the first relative position and the second relative position corresponding to one of the pair of target data streaming subnetworks.

Exemplarily, the following steps are carried out: if a pair of target data streaming sub-networks with data dependency relationship are respectively a data streaming sub-network subnet a and a data streaming sub-network subnet b, in the first task chain, the execution sequence of subnet a is a first one-to-one execution sequence SeqA1, and the execution sequence of subnet b is a first two-to-one execution sequence SeqB 1; in the second task chain, the execution sequence of SubnetA is a second first execution sequence SeqA2, and the execution sequence of SubNetB is a second execution sequence SeqB 2; preferably, the difference between the first execution order and the second execution order may be referred to as a first relative position of the pair of target data stream sub-networks, and the difference between the second execution order and the second execution order may be referred to as a second relative position of the pair of target data stream sub-networks, and if ((SeqA1-SeqB1) <0& (SeqA2-SeqB2) >0) is true or ((SeqA1-SeqB1) >0& & (SeqA2-SeqB2) <0) is true, it is determined that a positive-negative direction change occurs in the relative positions of the pair of target data stream sub-networks and the data stream sub-network SubnetB (i.e., there is a positive-negative direction change between the first relative position and the second relative position of the pair of target data stream sub-networks).

For example, if SeqA1 ═ 3, SeqB1 ═ 5, SeqA2 ═ 3, and SeqB2 ═ 2, then SeqA1-SeqB1 ═ 3-5 ═ -2, and SeqA2-SeqB2 ═ 3-2 ═ 1, and it is true that ((SeqA1-SeqB1) <0& & (SeqA2-SeqB2) >0), it can be determined that the relative position of the pair of target data stream sub-networks SubnetA and SubnetB has changed in the positive-negative direction.

It should also be noted that the embodiments of the present application perform position change via a data stream subnetworkThe diagram can intuitively obtain the relative position change situation of the data stream sub-network. Specifically, referring to fig. 5A, a schematic diagram of a task chain execution position change provided by an embodiment of the present application is shown. As shown in fig. 5A, where the first execution position diagram represents the execution order of the first data stream sub-network in the first task chain and the second execution position diagram represents the execution order of the second data stream sub-network in the second task chain, it can be understood that since the IDs of the data stream sub-networks are named by the symbolic variable names of their input symbols, the execution position diagram can also be understood as representing the execution order of the sub-networks in the task chain as input symbols. In the first execution position diagram, the execution sequence of each first data stream sub-network is Var1-Var2-Var3-Var4-Var 7; in the second execution position diagram, the execution order of each second data stream sub-network is Var1-Var2-Var7-Var3-Var4, and there are data dependencies between the data stream sub-network Var7 and the data stream sub-networks Var3 and Var4, that is, there are two pairs of target data stream sub-networks, which can be respectively denoted as target data stream sub-networks Var3-Var7 and target data stream sub-networks Var4-Var 7. The execution sequence of Var3 in the first execution position diagram is denoted as SeqVar3₁The execution sequence of Var4 is denoted as SeqVar4₁The execution sequence of Var7 is denoted as SeqVar7₁(ii) a The execution sequence of Var3 in the second execution position diagram is denoted as SeqVar3₂The execution sequence of Var4 is denoted as SeqVar4₂The execution sequence of Var7 is denoted as SeqVar7₂. Performing a difference calculation on the execution order of the two pairs of target data stream subnetworks: SeqVar7₁-SeqVar3₁＝5-3＝2，SeqVar7₁-SeqVar4₁＝5-4＝1；SeqVar7₂-SeqVar3₂＝3-4＝-1，SeqVar7₂-SeqVar4₂3-5-2. From the calculation results, it can be seen that both pairs of target data stream subnets satisfy ((SeqVar 7)₁-SeqVar3₁)>0&&(SeqVar7₂-SeqVar3₂)<0) True, also satisfies ((SeqVar 7)₁-SeqVar4₁)>0&&(SeqVar7₂-SeqVar4₂)<0) Is true. Namely the target data streaming subnetwork Var3-Var7, and the target data streaming subnetwork Var4-Var7The position changes in positive and negative directions. Therefore, for the first execution position diagram and the second execution position diagram in fig. 5A, the logic functions of the corresponding first task chain and the second task chain are inconsistent.

Referring to fig. 5B, which illustrates another schematic diagram of the task chain execution position change provided in the embodiment of the present application, it can be seen that, although the target data flow subnetworks Var3-Var7 and Var4-Var7 exist therein, the execution order of the two pairs of target data flow subnetworks does not change in the first execution position diagram and the second execution position diagram. Therefore, for the first execution position diagram and the second execution position diagram in fig. 5B, the logic functions of the corresponding first task chain and the second task chain are consistent.

In fig. 5A and 5B, each Var may be regarded as a data stream sub-network or as a sub-network of input symbols, and the determination method and the determination result are not affected regardless of whether it is regarded as a data stream sub-network or a sub-network of input symbols.

It should be further noted that, for a data stream sub-network without data dependency, the logical function of the task chain is not affected whether the relative position of the data stream sub-network changes, and therefore, in some embodiments, the method may further include:

and if the first data stream network and the second data stream network do not have data dependency relationship, determining that the logic functions of the first task chain and the second task chain are consistent.

It should be noted that the foregoing embodiments are all analysis and judgment performed when the CRC1 is consistent with the CRC2, and when the CRC1 is inconsistent with the CRC2, it may be directly determined that the logic functions of the first task chain are inconsistent with the logic functions of the second task chain. Thus, in some embodiments, the method may further comprise:

determining that the logical functionality of the first task chain and the second task chain are not consistent if the CRC1 is not consistent with the CRC 2.

It should be noted that, when CRC1 is inconsistent with CRC2, CRCs of page information texts of the first task chain and the second task chain may be compared, where a page information text is obtained by splicing information texts of data stream subnetworks arranged in descending order according to IDs of the data stream subnetworks in the page, and at this time, the modified consistency between pages is determined by comparing CRCs of pages with the same name in the first task chain and the second task chain, and the inconsistent pages are analyzed for differences.

Further, in some embodiments, the method may further comprise:

comparing and analyzing the configuration information of the first task chain and the configuration information of the second task chain; and if the first task chain and the second task chain have configuration difference, determining that the logic functions of the first task chain and the second task chain are inconsistent.

Specifically, the configuration information at least includes at least one of: task period and task level, number of pages, and page execution call order. As such, in some embodiments, the method may further comprise:

and if any one of the configuration information changes, determining that a configuration difference exists between the first task chain and the second task chain.

It should be noted that, when the first task chain and the second task chain are obtained, configuration analysis may be performed on the first task chain and the second task chain, and if it is determined that a configuration difference exists between the first task chain and the second task chain, it may be stated that the logical functions of the first task chain and the second task chain are inconsistent. At this time, a conclusion may be drawn and the process may be ended, or the detection may be continued according to the foregoing steps to further determine whether the logic functions of the two are consistent, which is not specifically limited in this embodiment of the application.

The embodiment provides a data analysis method, which comprises the steps of obtaining a first task chain and a second task chain to be detected; then determining a CRC1 for the first task chain based on a first data flow network of the first task chain; and determining a CRC2 for the second task chain based on a second data stream network of the second task chain; and analyzing the data dependency relationship existing in the first data stream network and the second data stream network to determine whether the logic functions of the first task chain and the second task chain are consistent under the condition that the CRC1 is consistent with the CRC 2. Therefore, the CRC1 and the CRC2 are respectively calculated by taking the task chains before and after modification as a whole, and when the CRC1 is consistent with the CRC2, whether the logic functions of the first task chain and the second task chain are consistent can be determined by analyzing the data dependency relationship existing in the data stream network, so that the technical problem that whether the logic functions of the task chains are consistent in the analysis from a macro level in the related technology can be solved, and meanwhile, the accuracy of visual engineering upgrade maintenance is improved.

In another embodiment of the present application, refer to fig. 6, which shows a schematic flow chart of another data analysis method provided in the embodiment of the present application. As shown in fig. 6, the method may include:

s601, acquiring a task chain before and after modification of analysis to be detected.

It should be noted that, in the embodiment of the present application, after the flow of data analysis is started, the task chain before and after modification for analysis detection is acquired first. Here, the task chains before and after modification of the analysis to be detected are also the first task chain and the second task chain in the foregoing embodiment.

And S602, analyzing the configuration difference of the task chain before and after modification.

It should be noted that, analyzing the configuration difference of the task chain before and after modification, including analyzing whether the task cycle and the task level of the task chain before and after modification are modified; whether each page on the task chain is increased or decreased; and whether the execution calling sequence of each page is changed or not. If any of the above items is changed, that is, it is stated that there is a difference in the task chain configuration before and after modification, step S603 is executed to draw a conclusion that the task chains are inconsistent, that is, the task chain logic functions are inconsistent. Otherwise, i.e. there is no difference in the task chain configuration before and after modification, step S604 is executed.

And S603, determining that the task chains before and after modification are inconsistent.

And S604, reading pages contained in the task chain before and after modification.

It should be noted that if there is no difference between the configurations of the task chains before and after modification, further analysis is needed to determine whether the logical functions of the task chains before and after modification are changed. Therefore, in the step, the pages included in the task chains before and after modification are respectively read, and the data connection relation between the symbols in the pages is respectively obtained. It can be understood that the page included in the task chain before modification read here is the initial page in the foregoing embodiment, and the page included in the task chain after modification read here is the target page in the foregoing embodiment.

It should be further noted that, after step S603, the process may be ended, or subsequent steps may be continuously performed to further determine the modification consistency of the task chain, which is not specifically limited in this embodiment of the application.

And S605, respectively extracting each input symbol in the page in the task chain before and after modification, performing depth-first traversal by taking the input symbol as a starting point to form a single-input-multiple-output data stream sub-network, wherein the ID of the data stream sub-network is the symbol variable name of the input symbol, and splicing and merging the data stream sub-networks with the same ID across the page according to the page calling sequence.

Note that, the depth-first traversal using the input symbol as the starting symbol is performed in accordance with the data connection relationship between symbols, and finally, a plurality of data stream sub-networks are formed. Here, the data stream sub-network may be a single-input-multiple-output or a single-input-single-output sub-network, for example, for the data stream sub-network "Var 1 → XOR → Var 2", it includes a sub-network Var1 as an input symbol and a sub-network Var2 as an output symbol, that is, the input symbol and the output symbol are both one, that is, the data stream sub-network of single-input-single-output. Illustratively, for data streaming sub-networks

It contains one sub-network Var1 as input symbol and two sub-networks Var2 and Var3 as output symbol, i.e. a single-input-multiple-output data stream sub-network. It should also be noted thatThe single-input single-output/single-input multi-output data streaming sub-network is only an exemplary data streaming sub-network of the embodiment of the present application, and particularly, the page of the actual task chain is taken as a standard, and the embodiment of the present application is not limited to this specifically. The symbol variable name of the input symbol is known or preset, and here, the ID of each data stream subnet is the symbol variable name of the input symbol.

The input symbols can be symbols of zero input points and one output point, and input variables on one page are defined according to the symbols; the input points can lead out a plurality of connecting lines to be connected to the symbols of the programming function blocks, and the symbols of the function blocks are also connected through the connecting lines. When a plurality of connecting lines are led out from one output point at the same time, the sequence of the subsequent data flow traversal of the connecting lines is determined according to the sequence of the positions of the input points of the functional blocks connected with the terminal ends of the connecting lines from top to bottom, and the data flow traverses to the output blocks or the symbols of zero output points on the data flow sub-network in the page through depth first.

If two or more pages define input symbols with the same symbol variable name, that is, if the IDs of the data stream subnetworks across pages of the input symbols including the same symbol variable name are the same, merging of the data stream subnetworks with the same ID is performed, and the merging order is performed according to the calling order (that is, the execution order) of the pages to which the data stream subnetworks belong. Therefore, the data stream sub-networks with the same ID across the page are merged and traversed, so that the data stream sub-networks obtained after traversal are all different IDs.

Illustratively, page A and page B are executed in the order A → B, with page A having a data flow subnetwork Var1 prior to merging: "Var 1 → ADD → XOR → Var 2", page B presents a data flow sub-network Var 1: "Var 1 → ADD → Var 3", because the symbol variable names of the input symbols of the two are the same, the IDs thereof are the same, and at this time, they need to be merged, and they are spliced and merged according to the page execution order, so that the merged data stream sub-network Var1 can be obtained:

and S606, arranging the data flow sub-networks of the task chains before and after modification in a descending order according to the IDs respectively to form the data flow sub-networks with the ordered task chains before and after modification.

It should be noted that, after depth-first traversal is performed to obtain the data stream subnetworks of the task chain before and after modification, the data stream subnetworks are arranged in a descending order according to the IDs of the data stream subnetworks, so as to form the ordered data stream subnetworks under the whole task chain. The sequenced data flow sub-networks are collectively referred to as a data flow network, where the data flow network of the task chain before modification is the first data flow network in the foregoing embodiment, and the data flow network of the task chain after modification is the second data flow network in the foregoing embodiment.

And S507, traversing the symbols of the data stream sub-networks after the task chains before and after modification are sequenced respectively, extracting information for comparison, summarizing information texts, calculating CRC (cyclic redundancy check) of the task chain information texts before and after modification, and detecting the consistency of the task chains before and after modification.

It should be noted that, preferably, the information of the single symbol participating in the comparison includes: the symbol type, the symbol variable name, the symbol variable value, the symbol variable description, the symbol variable type, the source output symbol type corresponding to the symbol input point and the source output point variable name. The information text of the single-input-multiple-output/single-output data stream sub-network is the symbol information in the data stream sub-network spliced according to the sequence formed by the data connection relations among the symbols in the data stream sub-network.

It should be further noted that, what is calculated and compared in this step is the CRC of the information texts of the task chains before and after modification, that is, traversing the symbols of the sorted data stream sub-networks, extracting information for comparison, splicing the information texts of all the data stream sub-networks of each page in the data stream networks of the task chains before and after modification obtained in the previous step, respectively, to obtain an information text of the entire task chain, which may also be referred to as an information total text of the task chain, and calculating and comparing the CRCs of the information total texts of the task chains before and after modification. It can be understood that the total information text of the pre-modification task chain is the first information text in the previous embodiment, and CRC1 is calculated for the first information text; the total information text of the modified task chain is the second information text in the previous embodiment, and CRC2 is calculated for the second information text.

And S608, judging whether the CRC of the task chain is consistent before and after modification.

It should be noted that, after comparing the CRCs of the task chains before and after modification, if the CRCs of the task chains before and after modification are inconsistent, step S609 is executed; if so, step S6010 is performed.

And S609, performing CRC comparison on each page information text, and performing difference analysis on inconsistent pages.

It should be noted that this step is performed when CRCs of task chains before and after modification are inconsistent. The page information text is formed by splicing the data stream sub-network information texts arranged in the page according to the ID descending order, namely, the page information text CRC is calculated only by splicing the information texts of the data stream sub-networks in a certain page and is used for judging the consistency of the pages with the same name in the task chains before and after modification.

It should be further noted that when the task chains CRC before and after modification are inconsistent, it can be concluded that the task chains logical functions before and after modification are inconsistent, and the further analysis is to analyze the consistency of the pages of the task chains before and after modification.

S6010, respectively traversing the pages of the task chains before and after modification according to the page execution sequence, sequentially arranging data stream sub-networks in the pages from top to bottom according to the input symbols, and comparing whether the relative positions of the data stream sub-networks with data dependency relationship before and after modification change in the positive and negative directions.

S6011, if the change occurs, drawing a data dependence position change diagram to obtain a conclusion that the whole group of the data stream sub-network is migrated and the logical functions of the task chains before and after modification are inconsistent; and if the task chain is not changed, the conclusion that the logic functions of the task chain are consistent before and after modification is obtained.

Preferably, the method for confirming the data dependency relationship of the data flow subnetworks across the pages comprises the following steps: and the symbol variable name of the output symbol of the page PageA is the same as the symbol variable name of the input symbol of the page PageB, so that the data dependency relationship exists between the data stream subnetworks to which the two symbols with the same names belong.

Preferably, for a data stream sub-network with data dependency relationship, the criterion for the positive and negative direction change of the relative position is as follows: if data dependency relationship exists between the data stream sub-network and the data stream sub-network (sub-network a and sub-network b, that is, a pair of target data stream sub-networks with data dependency relationship in the foregoing embodiments), the execution order of sub-network a before modification is SeqA1, the execution order of sub-network b is SeqB1, the execution order of sub-network a after modification is SeqA2, and the execution order of sub-network b is SeqB2, if ((SeqA1-SeqB1) <0& & & (SeqA2-SeqB2) >0) is satisfied as TRUE, or ((SeqA1-SeqB1) >0& & (SeqA2-SeqB2) >0) is satisfied as TRUE, the relative position of the data stream sub-network determined to have data dependency relationship is changed in positive and negative directions.

It should be understood that, since the ID of the data stream sub-network is named by the name of the symbol variable of the output symbol, here, for the data stream sub-network having the data dependency relationship, it is also understood that, in determining whether the relative position of the input symbol (e.g., the sub-network serving as the input symbol) in the two data stream sub-networks has a change in the positive or negative direction, the determination method and the determination result are not affected in any way.

When the CRCs of the task chains before and after modification are consistent, the task chains before and after modification respectively traverse the pages according to the execution order of the pages, arrange the data stream subnetworks in the pages according to the order from top to bottom of the input symbols, and compare whether the relative positions of the data stream subnetworks having data dependency relationship before and after modification are changed in the positive and negative directions.

Specifically, referring to fig. 7, a schematic diagram of task chain consistency judgment based on a data flow sub-network according to an embodiment of the present application is shown. As shown in fig. 7, there is no data flow sub-network having data dependency relationship between Page1 and Page2, where sub-networks Var1, Var2, Var3, Var4, Var8, and Var9 are input symbols; subnets Var5, Var6, Var7, and Var10 are output symbols; NOT1, NOT2, XOR2, ADD1, FB1, FB2 and FB3 are functional blocks, where NOT denotes NOT, XOR denotes exclusive or, ADD denotes addition, FB is a shorthand for the functional Block Function Block, denotes a pre-edited or tested program set, and has a specific element. It is understood that there may be other functions and numbers of SUB-networks and function blocks in the pages of the task chain, such as the function block SUB (minus), SEL (select), etc., and the present embodiment is not limited to the examples, and the above exemplary SUB-networks and function blocks do not constitute a limitation of the present application.

In the Page1 before modification, there are four subnetworks, namely Var1, Var2, Var3 and Var4, as input symbols, three subnetworks, namely Var5, Var6 and Var7, as output symbols, and four function blocks, namely NOT1, XOR2, NOT2 and ADD1, which constitute four data stream subnetworks with IDs of Var1, Var2, Var3 and Var 4.

In the Page2 before modification, there are two subnets of Var8 and Var9 as input symbols, one subnetwork of Var10 as output symbols, and function blocks FB1, FB2, and FB3 which constitute two data stream subnets with IDs of Var8 and Var9, respectively.

After depth-first traversal, data chain nodes (data network expressions) such as Var1 → NOT1 → XOR2 → Var5 can be formed, where one data chain node represents one data chain sub-network, and the data chain nodes are arranged in descending order according to the input symbol variable names, so that the data network expressions in the following order can be formed:

Var1→NOT1→XOR2→Var5

Var3→ADD1→Var7

Var4→ADD1→Var7

Var8→FB1→FB3→Var10

Var9→FB2→FB3→Var10

the information texts of the symbols are spliced according to the sequence, and the CRC1 of the task chain before modification can be calculated.

It can be seen that the modification here is to migrate the entire group of data flow subnetwork groups "Var 3 → ADD1 → Var7, Var4 → ADD1 → Var 7" from Page1 to Page 2. In fig. 7, a data streaming sub network group composed of two data streaming sub networks is migrated, it is to be understood that a single data streaming sub network may also be migrated, or a data streaming sub network group composed of more data streaming sub networks may also be migrated, which is not specifically limited in the embodiments of the present application, and is only exemplified in fig. 7.

The modified Page1 has two subnetworks of Var1 and Var2 as input symbols, two subnetworks of Var5 and Var6 as output symbols, and three function blocks of NOT1, XOR2 and NOT2, which constitute two data stream subnetworks with IDs of Var1 and Var 2.

The modified Page2 has four sub-networks of Var8, Var9, Var3 and Var4 as input symbols, two sub-networks of Var10 and Var7 as output symbols, and four functional blocks of FB1, FB2, FB3 and ADD1, which constitute four sub-networks of data streams with IDs of Var8, Var9, Var3 and Var4, respectively.

After depth-first traversal, data chain nodes (data network expressions) in the form of Var1 → NOT1 → XOR2 → Var5 are formed, where one data chain node represents one data chain sub-network, and the data chain nodes are arranged in descending order according to the input symbol variable names, so that data network expressions in the following order can be formed, that is, the data network sub-networks after sorting are represented:

Var1→NOT1→XOR2→Var5

Var3→ADD1→Var7

Var4→ADD1→Var7

Var8→FB1→FB3→Var10

Var9→FB2→FB3→Var10

the information texts of the symbols are spliced according to the sequence, and the CRC2 of the task chain before modification can be calculated.

It can be seen that there is no data flow sub-network between Page1 and Page2 where there is a data dependency. For the Page1 and the Page2 before and after modification, the symbols themselves do not have information such as modified attributes, and the information text of the task chain before and after modification is the same, and the computed CRC is also the same. That is, a data sub-chain without data dependency relationship (i.e., a data stream sub-network group including one or more data stream sub-networks) is migrated to other pages, without affecting the logic function of the whole task chain, and it can be evaluated that the logic functions before and after modification are consistent.

Referring to fig. 8, a schematic diagram of task chain consistency judgment based on a data flow sub-network according to an embodiment of the present application is shown, as shown in fig. 8, where there is a data flow sub-network with data dependency between a Page1 and a Page 2. It should be noted that the same names of sub-networks and functional blocks in fig. 8 are the same as or similar to those shown in fig. 7, and are not described again here.

In the Page1 before modification, there are four sub-networks of Var1, Var2, Var3 and Var4 as input symbols, three sub-networks of Var5, Var6 and Var7 as output symbols, and four function blocks of NOT1, XOR2, NOT2 and ADD1, which constitute four sub-networks of data streams with IDs of Var1, Var2, Var3 and Var 4.

The Page2 before modification has Var7 as input symbol sub-network, Var8 as output symbol sub-network, and FB1 as a function block, which constitutes a data stream sub-network with ID Var 7.

After depth-first traversal, data chain nodes (data network expressions) in the form of Var1 → NOT1 → XOR2 → Var5 are formed, and the data network expressions are arranged in descending order according to the input symbol variable names, so that the data network expressions in the following order can be formed:

Var1→NOT1→XOR2→Var5

Var3→ADD1→Var7

Var4→ADD1→Var7

Var8→FB1→FB3→Var10

Var9→FB2→FB3→Var10

It can be seen that the modification here is to migrate the entire group of data flow subnetwork groups "Var 3 → ADD1 → Var7, Var4 → ADD1 → Var 7" from Page1 to Page 2. In fig. 8, a data stream sub-network group composed of two data stream sub-networks is migrated, it is to be understood that a single data stream sub-network may also be migrated, or a data stream sub-network group composed of more data stream sub-networks may also be migrated, which is not specifically limited in the embodiments of the present application, and is only exemplified in fig. 8.

The modified Page1 has two subnets of Var1 and Var2 as input symbols, two subnets of Var5 and Var6 as output symbols, and three function blocks of NOT1, XOR2 and NOT2, which constitute three data stream subnets with IDs of Var7, Var3 and Var 4.

The Page2 has three sub-networks of Var7, Var3 and Var4 as input symbols, two sub-networks of Var8 and Var7 as output symbols, and two function blocks of FB1 and ADD1, which constitute three sub-networks of data streams with IDs of Var7, Var3 and Var 4.

After depth-first traversal, data chain nodes in the form of Var1 → NOT1 → XOR2 → Var5 are formed, and are arranged in descending order according to the input symbol variable names, so that data network expressions in the following order can be formed.

Var1→NOT1→XOR2→Var5

Var3→ADD1→Var7

Var4→ADD1→Var7

Var8→FB1→FB3→Var10

Var9→FB2→FB3→Var10

It can be seen that there is a data flow subnetwork with data dependency relationship between the Page1 and the Page2, that is, in the Page1 data flow subnetwork, the output vars 7 of the vars 3 and the Var4 and the input vars 7 in the data flow subnetwork of the Page2 have the same name, and there is data dependency relationship, that is, there are two pairs of target data flow subnetworks described in the previous embodiment. It is understood that other forms of data dependency relationships between data streaming sub-networks are also possible, and the data dependency relationship is only shown in fig. 8 as an example, and the embodiment of the present application is not limited to this.

For the pages Page1 and Page2 before and after modification, the obtained information texts are the same, and the calculated CRCs are also the same, but after the pages are sequenced from top to bottom in the pages according to the Page execution sequence, the relative position change of the data streaming sub-network with the data dependency relationship can be found. Here, as shown in fig. 8, a data-dependent position change diagram is drawn according to the execution order of the pages, and the data-dependent position change diagram can analyze the execution order of the data streaming sub-networks, where the data-dependent position change diagram is a task chain execution position change diagram of the previous embodiment, and the analysis shows that: in the task chain before modification, according to the execution principle of the pages from top to bottom, the data stream sub-network calls are in the order of Var1, Var2, Var3, Var4 and Var 7. The data stream sub-network execution sequence deviation is SeqVar7₁-SeqVar3₁＝2，SeqVar7₁-SeqVar4 ₁1. In the modified task chain, the data flow sub-network calls are in the order of Var1, Var2, Var7, Var3, and Var 4. Data streaming sub-network execution order bias of SeqVar7₂-SeqVar3₂＝-1，SeqVar7₂-SeqVar4₂-2. That is, in the data flow sub-networks having data dependency relationship, the relative position of the data flow sub-network having data dependency relationship changes in the positive and negative directions, and for the data flow sub-networks having data dependency relationship, the input data and the output data thereof differ by one period value in the periodic task, and it is determined as being influencedAnd the logic function is inconsistent with the logic function of the task chain before and after modification.

In short, in the embodiment of the present application, it is mainly to analyze whether the modification is consistent with the influence of the migration of the data stream sub-network with the task chain as a whole. The data analysis method provided by the embodiment of the application can comprise the following steps:

a) acquiring task chains to be detected and analyzed before and after modification, analyzing configuration differences of the task chains before and after modification, reading pages contained in the task chains before and after modification, and acquiring data connection relations among symbols in the pages;

b) extracting each input symbol in the page, taking the input symbol as an initial symbol, and performing depth-first traversal according to the data connection relation among the symbols to form a single-input-multiple-output/single-input-single-output data stream sub-network, wherein the ID of the data stream sub-network is the symbol variable name of the input symbol;

c) splicing and merging the data stream sub-networks with the same ID across the pages according to the execution sequence of the pages; then, the data flow sub-networks are arranged in a descending order according to the IDs to form a data flow sub-network with the ordered whole task chain;

d) traversing the symbols of the sequenced data flow sub-networks of the task chains before and after modification respectively, extracting symbol information for comparison, summarizing information texts, obtaining the information texts of the task chains before and after modification respectively, calculating CRC (cyclic redundancy check) of the information texts of the task chains before and after modification, and detecting consistency of the task chains before and after modification;

e) if the CRC of the task chain before and after modification is inconsistent, CRC comparison of each page information text is carried out, and difference analysis is carried out on inconsistent pages;

f) if the CRC of the task chain before and after modification is consistent, traversing the pages according to the page execution sequence, arranging sub-networks in each page from top to bottom according to the input symbols, and comparing whether the relative position of the data stream sub-networks with data dependency relationship before and after modification changes in the positive and negative directions; if the data is changed, drawing a data dependence position change diagram to obtain the conclusion that the modification is performed on the whole group of the data stream sub-network and the logic functions before and after the modification are inconsistent. And if the logic function is not changed, the conclusion of the logic function consistency before and after modification is given.

Further, the configuration difference of the task chain before and after modification is analyzed, including whether the task cycle and the task level of the task chain before and after modification are modified, whether each page on the task chain is increased or decreased, and whether the execution calling sequence of each page is changed.

Further, the symbol information for comparison includes: the symbol type, the symbol variable name, the symbol variable value, the symbol variable description, the symbol variable type, the source output symbol type corresponding to the symbol input point and the source output point variable name. The information text of the single-input-multiple-output data stream sub-network is symbol information spliced in the sub-network according to the sequence formed by the data stream dependence.

Further, the page information text is formed by splicing the information texts of the data flow subnetworks arranged in the page according to the descending order of the ID, and the page information text CRC is calculated and used for judging the consistency of the pages with the same name.

Further, the method for confirming the data dependency relationship of the data flow sub-network across the page comprises the following steps: the output symbol name of the page PageA is the same as the input symbol name of the page PageB, and then a data dependency relationship exists between the data stream streaming sub-networks to which the two symbols with the same name belong.

Further, the criterion that the relative position of the data flow sub-network with the data dependency relationship changes in the positive and negative directions is as follows: if the data dependency relationship exists between the data flow sub-network Subnet A and the data flow sub-network Subnet B, the execution sequence of Subnet A is SeqA1 and the execution sequence of Subnet B is SeqB1 in a task chain before modification, the execution sequence of Subnet A is SeqA2 and the execution sequence of Subnet B is SeqB2 in the task chain after modification, and if the conditions that ((SeqA1-SeqB1) <0& & (SeqA2-SeqB2) >0) is TRUE or ((SeqA1-SeqB1) >0& & (SeqA2-SeqB2) <0) is TRUE) are met, it is determined that the relative position of the data flow with the data dependency relationship has a positive and negative direction change of the sub-networks.

Furthermore, the consistency of the logic functions before and after the task chain modification is not influenced by the change of the relative position of the data flow sub-networks without data dependency relationship.

The embodiment provides a data analysis method, and the specific implementation of the foregoing embodiment is elaborated through the foregoing embodiment, and it can be seen that in the technical solution of the embodiment of the present application, a task chain is used as an analysis unit, a graph program of pages included in the task chain is divided and compared according to input variables, whether a relative position of a data stream sub-network having a data dependency relationship in the task chain changes before and after modification is analyzed according to a page execution sequence and a position sequence of input symbols from top to bottom, whether a whole group of movement of the data stream sub-network between pages affects a logic function of the task chain can be accurately determined, a conclusion whether a substantial influence exists is obtained, and a problem that whether a whole group of migration part visualization networks between pages in a task chain at the same level are affected by a simple page CRC comparison method is solved, the visual page comparison and analysis technology is further improved, and the accuracy of visual engineering upgrade and maintenance is improved.

In yet another embodiment of the present application, referring to fig. 9, a schematic structural diagram of a data analysis apparatus 90 provided in the embodiment of the present application is shown. As shown in fig. 9, the data analysis apparatus includes: an acquisition unit 901, a determination unit 902, and an analysis unit 903, wherein,

the acquiring unit 901 is configured to acquire a first task chain and a second task chain to be detected;

the determining unit 902 is configured to determine CRC1 of the first task chain based on the first data flow network of the first task chain; and determining a CRC2 for the second task chain based on a second data stream network of the second task chain;

the analysis unit 903 is configured to, if the CRC1 is consistent with the CRC2, analyze data dependencies existing in the first data stream network and the second data stream network to determine whether logical functions of the first task chain and the second task chain are consistent.

In some embodiments, the obtaining unit 901 is further configured to obtain, based on an initial page included in the first task chain, a data connection relationship between at least one symbol of the initial page; extracting input symbols in the initial page, and performing depth-first traversal according to a data connection relation between at least one symbol of the initial page by taking the input symbols as initial symbols to obtain at least one first data stream sub-network; and performing descending order arrangement on the at least one first data stream sub-network according to the symbol variable name of the input symbol to obtain the first data stream network.

In some embodiments, when the number of the initial pages is at least two, the obtaining unit 901 is further configured to, if a first input symbol with the same symbol variable name across pages exists in the at least two initial pages, splice and merge a first data stream subnetwork to which the first input symbol belongs according to an execution sequence of the at least two initial pages.

In some embodiments, the obtaining unit 901 is further configured to obtain, based on a target page included in the second task chain, a data connection relationship between at least one symbol of the target page; extracting an input symbol in the target page, and performing depth-first traversal according to a data connection relation between at least one symbol of the target page by taking the input symbol as an initial symbol to obtain at least one second data stream sub-network; and performing descending order arrangement on the at least one second data stream sub-network according to the symbol variable name of the input symbol to obtain the second data stream network.

In some embodiments, when the number of the target pages is at least two, the obtaining unit 901 is further configured to, if a second input symbol with the same symbol variable name across pages exists in the at least two target pages, splice and merge the second data stream subnetworks to which the second input symbol across pages belongs according to the execution sequence of the at least two target pages.

In some embodiments, the obtaining unit 901 is further configured to traverse at least one symbol in the first data stream network, and extract first symbol information; and determining a first information text of the first task chain based on the first symbol information; the data analysis device 900 further comprises a calculation unit 904 for calculating a CRC1 of the first task chain based on the first information text.

In some embodiments, the obtaining unit 901 is further configured to traverse at least one symbol in the second data stream network, and extract second symbol information; and determining a second information text of the second task chain based on the second symbol information; the calculating unit 904 is further configured to calculate, based on the second information text, CRC2 of the second task chain.

In some embodiments, the symbol information comprises at least one of: the symbol type, the symbol variable name, the symbol variable value, the symbol variable description, the symbol variable type, the source output symbol type corresponding to the symbol input point and the source output point variable name.

In some embodiments, the obtaining unit 901 is further configured to obtain, in a case that a data dependency relationship exists between the first data stream network and the second data stream network, a first relative position of at least one pair of target data stream subnetworks in the first task chain, where the data dependency relationship exists; and obtaining a second relative position of the at least one pair of target sub-data stream networks with data dependency relationship in the second task chain; the determining unit 902 is further configured to determine whether the logical functions of the first task chain and the second task chain are consistent based on the first relative position of the at least one pair of target sub-data stream networks and the second relative position of the at least one pair of target sub-data stream networks.

In some embodiments, the determining unit 902 is further configured to determine that the logical functions of the first task chain and the second task chain are inconsistent if there is a positive-negative direction change between the first relative position and the second relative position corresponding to one pair of target data streaming subnetworks; and if no positive and negative direction change exists between the first relative position and the second relative position corresponding to any pair of target data stream sub-networks, determining that the logic functions of the first task chain and the second task chain are consistent.

In some embodiments, the determining unit 902 is further configured to determine a first execution order and a first second execution order of each of the pair of target data stream subnetworks in the first task chain, and a second first execution order and a second execution order of each of the pair of target data stream subnetworks in the second task chain; and if the difference between the first execution sequence and the first second execution sequence is less than zero and the difference between the second execution sequence and the second execution sequence is greater than zero, or the difference between the first execution sequence and the first second execution sequence is greater than zero and the difference between the second execution sequence and the second execution sequence is less than zero, determining that a positive-negative direction change exists between the first relative position and the second relative position corresponding to one of the pair of target data stream subnetworks.

In some embodiments, the determining unit 902 is further configured to determine that the logical functions of the first task chain and the second task chain are consistent if no data dependency exists between the first data stream network and the second data stream network.

In some embodiments, the determining unit 902 is further configured to determine that the logical functions of the first task chain and the second task chain are not consistent if the CRC1 is not consistent with the CRC 2.

In some embodiments, the analysis unit 903 is further configured to perform comparison analysis on the configuration information of the first task chain and the configuration information of the second task chain; the determining unit 902 is further configured to determine that the logic functions of the first task chain and the second task chain are inconsistent if there is a configuration difference between the first task chain and the second task chain.

In some embodiments, the configuration information includes at least one of: task period, task level, page number and page execution calling sequence; the determining unit 902 is further configured to determine that a configuration difference exists between the first task chain and the second task chain if any one of the configuration information changes.

It is understood that in this embodiment, a "unit" may be a part of a circuit, a part of a processor, a part of a program or software, etc., and may also be a module, or may also be non-modular. Moreover, each component in the embodiment may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware or a form of a software functional module.

Based on the understanding that the technical solution of the present embodiment essentially or a part contributing to the prior art, or all or part of the technical solution may be embodied in the form of a software product stored in a storage medium, and include several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) or a processor (processor) to execute all or part of the steps of the method of the present embodiment. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.

Correspondingly, an embodiment of the present application provides an electronic device, which includes: a memory and a processor; wherein,

the memory for storing a computer program operable on the processor;

the processor is configured to execute the steps of the data analysis method as in the previous embodiments when the computer program is run.

Correspondingly, the present embodiment provides a computer storage medium storing a computer program which, when executed by at least one processor, implements the steps of the data analysis method as in the previous embodiments.

Exemplarily, refer to fig. 10, which shows a specific hardware structure diagram of an electronic device 1000 provided in an embodiment of the present application. As shown in fig. 10, may include: a communication interface 1001, a memory 1002, and a processor 1003; the various components are coupled together by a bus system 1004. It is understood that the bus system 1004 is used to enable communications among the components. The bus system 1004 includes a power bus, a control bus, and a status signal bus in addition to a data bus. But for the sake of clarity the various busses are labeled in fig. 10 as the bus system 1004. The communication interface 1001 is used for receiving and transmitting signals during information transmission and reception with other external network elements.

It is to be appreciated that the memory 1002 in the subject embodiment can be either volatile memory or nonvolatile memory, or can include both volatile and nonvolatile memory. The non-volatile Memory may be a Read-Only Memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an Electrically Erasable PROM (EEPROM), or a flash Memory. Volatile Memory can be Random Access Memory (RAM), which acts as external cache Memory. By way of example, but not limitation, many forms of RAM are available, such as Static random access memory (Static RAM, SRAM), Dynamic Random Access Memory (DRAM), Synchronous Dynamic random access memory (Synchronous DRAM, SDRAM), Double Data Rate Synchronous Dynamic random access memory (ddr Data Rate SDRAM, ddr SDRAM), Enhanced Synchronous SDRAM (ESDRAM), Synchronous chained SDRAM (Synchronous link DRAM, SLDRAM), and Direct memory bus RAM (DRRAM). The memory 1002 of the systems and methods described herein is intended to comprise, without being limited to, these and any other suitable types of memory.

And the processor 1003 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be implemented by integrated logic circuits of hardware or instructions in the form of software in the processor 1003. The Processor 1003 may be a general-purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, or discrete hardware components. The various methods, steps, and logic blocks disclosed in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present application may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in the memory 1002, and the processor 1003 reads the information in the memory 1002 and performs the steps of the above method in combination with the hardware thereof.

It is to be understood that the embodiments described herein may be implemented in hardware, software, firmware, middleware, microcode, or any combination thereof. For a hardware implementation, the Processing units may be implemented within one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), general purpose processors, controllers, micro-controllers, microprocessors, other electronic units configured to perform the functions described herein, or a combination thereof.

For a software implementation, the techniques described herein may be implemented with modules (e.g., procedures, functions, and so on) that perform the functions described herein. The software codes may be stored in a memory and executed by a processor. The memory may be implemented within the processor or external to the processor.

Optionally, as another embodiment, the processor 1003 is further configured to execute the steps of the method in any one of the preceding embodiments when running the computer program.

The above description is only a preferred embodiment of the present application, and is not intended to limit the scope of the present application.

It should be noted that, in the present application, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.

The above-mentioned serial numbers of the embodiments of the present application are merely for description and do not represent the merits of the embodiments.

The methods disclosed in the several method embodiments provided in the present application may be combined arbitrarily without conflict to obtain new method embodiments.

Features disclosed in several of the product embodiments provided in the present application may be combined in any combination to yield new product embodiments without conflict.

The features disclosed in the several method or apparatus embodiments provided in the present application may be combined arbitrarily, without conflict, to arrive at new method embodiments or apparatus embodiments.

The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A method of data analysis, the method comprising:

acquiring a first task chain and a second task chain to be detected;

2. The method of claim 1, wherein after the obtaining the first task chain to be detected, the method further comprises:

acquiring a data connection relation between at least one symbol of an initial page based on the initial page contained in the first task chain;

extracting input symbols in the initial page, and performing depth-first traversal according to a data connection relation between at least one symbol of the initial page by taking the input symbols as starting symbols to obtain at least one first data stream subnetwork;

and performing descending order arrangement on the at least one first data stream sub-network according to the symbol variable name of the input symbol to obtain the first data stream network.

3. The method of claim 2, wherein when the number of initial pages is at least two, the method further comprises:

4. The method of claim 1, wherein after said obtaining the second task chain to be detected, the method further comprises:

acquiring a data connection relation between at least one symbol of a target page based on the target page contained in the second task chain;

extracting input symbols in the target page, and performing depth-first traversal according to a data connection relation between at least one symbol of the target page by taking the input symbols as starting symbols to obtain at least one second data stream sub-network;

and performing descending order arrangement on the at least one second data stream sub-network according to the symbol variable name of the input symbol to obtain the second data stream network.

5. The method of claim 4, wherein when the number of target pages is at least two, the method further comprises:

and if second input symbols with the same symbol variable names across the pages exist in the at least two target pages, splicing and merging the second data stream sub-networks to which the second input symbols belong according to the execution sequence of the at least two target pages.

6. The method of claim 2, wherein determining the CRC1 for the first task chain based on the first data flow network for the first task chain comprises:

traversing at least one symbol in the first data flow network, and extracting first symbol information;

determining a first information text of the first task chain based on the first symbol information;

based on the first information text, a CRC1 of the first task chain is calculated.

7. The method of claim 4, wherein determining the CRC2 for the second task chain based on the second data stream network for the second task chain comprises:

traversing at least one symbol in the second data stream network, and extracting second symbol information;

determining a second information text of the second task chain based on the second symbol information;

based on the second information text, a CRC2 of the second task chain is calculated.

8. The method according to claim 6 or 7, wherein the symbol information comprises at least one of: the symbol type, the symbol variable name, the symbol variable value, the symbol variable description, the symbol variable type, the source output symbol type corresponding to the symbol input point and the source output point variable name.

9. The method of claim 1, wherein, in the case that the CRC1 is consistent with the CRC2, the analyzing data dependencies existing in the first data stream network and the second data stream network to determine whether logical functions of the first task chain and the second task chain are consistent comprises:

under the condition that the first data stream network and the second data stream network have data dependency relationship, acquiring first relative positions of at least one pair of target data stream sub-networks with the data dependency relationship in the first task chain; and obtaining a second relative position of the at least one pair of target data stream sub-networks having data dependency relationship in the second task chain;

determining whether the logical functions of the first task chain and the second task chain are consistent based on a first relative position of the at least one pair of target data flow subnetworks and a second relative position of the at least one pair of target data flow subnetworks.

10. The method of claim 9, wherein determining whether the logical functionality of the first task chain and the second task chain is consistent based on the first relative location of the at least one pair of target data flow subnetworks and the second relative location of the at least one pair of target data flow subnetworks comprises:

11. The method of claim 10, further comprising:

12. The method of claim 9, further comprising:

13. The method of claim 1, further comprising:

14. The method of claim 1, further comprising:

comparing and analyzing the configuration information of the first task chain and the configuration information of the second task chain;

and if the first task chain and the second task chain have configuration difference, determining that the logic functions of the first task chain and the second task chain are inconsistent.

15. The method of claim 14, wherein the configuration information comprises at least one of: task period, task level, page number and page execution calling sequence;

accordingly, the method further comprises:

16. A data analysis apparatus, characterized in that the data analysis apparatus comprises: an acquisition unit, a determination unit, and an analysis unit, wherein,

17. An electronic device, characterized in that the electronic device comprises: a memory and a processor; wherein,

the memory for storing a computer program operable on the processor;

the processor, when running the computer program, is configured to perform the steps of the data analysis method of any of claims 1 to 15.

18. A computer storage medium, characterized in that the computer storage medium stores a computer program which, when executed by at least one processor, implements the steps of the data analysis method according to any one of claims 1 to 15.