CN112579454A - Task data processing method, device and equipment - Google Patents
Task data processing method, device and equipment Download PDFInfo
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- CN112579454A CN112579454A CN202011538240.9A CN202011538240A CN112579454A CN 112579454 A CN112579454 A CN 112579454A CN 202011538240 A CN202011538240 A CN 202011538240A CN 112579454 A CN112579454 A CN 112579454A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/36—Preventing errors by testing or debugging software
- G06F11/3668—Software testing
- G06F11/3672—Test management
- G06F11/3684—Test management for test design, e.g. generating new test cases
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/36—Preventing errors by testing or debugging software
- G06F11/3668—Software testing
- G06F11/3672—Test management
- G06F11/3688—Test management for test execution, e.g. scheduling of test suites
Abstract
The application provides a processing method, a processing device and processing equipment of task data, which are used for counting flow data of target test case data obtained through a mind map application environment when an application test is carried out based on a mind map tool, so that the quality of the test case can be better evaluated based on the flow data when the test task is checked subsequently, and powerful data support is provided. The method comprises the following steps: the method comprises the steps that a processing device obtains initial test case data input in a mind map application environment; the processing equipment compiles the initial test case data into target test case data matched with a target test environment according to the self content of the initial test case data and the logical relationship between the initial test case data and other test case data, wherein the target test case data is used for executing a test task on a target application in the target test environment; and the processing equipment counts the flow data of the target test case data and stores the flow data in the task data of the test task.
Description
Technical Field
The present application relates to the field of testing, and in particular, to a method, an apparatus, and a device for processing task data.
Background
In the production environment inside an application development company, how to perform high-speed application development work obviously has little practical significance, and therefore, the demand exists for basic production tools.
In the years, thought mapping tools such as Xmind and the like are generally adopted to compile test cases, compared with the situations that traditional test case management tools such as Testlink and the like are long in compiling time and not high in test case execution, the thought mapping tools have the advantages of being high in visualization, concise and clear, and therefore the thought mapping tools are more suitable for workers to compile test cases, and automatic testing of the test cases output based on the thought mapping tools is achieved.
In the existing research process of the related technology, the inventor finds that after application test is performed based on the mind mapping tool, the quality of the test case of the test itself is difficult to reflect while the test result is counted in the later period, and therefore, data support is lacked for how to perform better application test based on the mind mapping tool.
Disclosure of Invention
The application provides a processing method, a processing device and processing equipment of task data, which are used for counting flow data of target test case data obtained through a mind map application environment when an application test is carried out based on a mind map tool, so that the quality of the test case can be better evaluated based on the flow data when the test task is checked subsequently, and powerful data support is provided.
In a first aspect, the present application provides a method for processing task data, where the method includes:
the method comprises the steps that a processing device obtains initial test case data recorded in a mind map application environment, wherein the test case compiling data is test case data compiled aiming at a test task of a target application;
the processing equipment compiles the initial test case data into target test case data matched with a target test environment according to the self content of the initial test case data and the logical relationship between the initial test case data and other test case data, wherein the target test case data is used for executing a test task on a target application in the target test environment;
and the processing equipment counts the flow data of the target test case data and stores the flow data in the task data of the test task.
With reference to the first aspect of the present application, in a first possible implementation manner of the first aspect of the present application, the processing device counting flow data of a test task includes:
the processing equipment extracts edit data of the initial test case data, wherein the edit data is used for describing the edit state of the initial test case data, and the edit data comprises edit time;
the processing device generates flow data according to the edit data.
With reference to the first possible implementation manner of the first aspect of the present application, in a second possible implementation manner of the first aspect of the present application, the generating, by a processing device, flow data according to edit data includes:
the processing equipment determines the number of different functional nodes in the initial test case data and the editing duration according to the editing data;
the processing equipment determines the processing efficiency of the different functional nodes based on the number of the different functional nodes and the editing duration of the different functional nodes.
With reference to the second possible implementation manner of the first aspect of the present application, in a third possible implementation manner of the first aspect of the present application, the editing state further includes an editing identifier, where the editing identifier is used to identify whether the editing manner is a use case writing manner or a use case executing manner, the processing efficiency specifically includes writing efficiency and execution efficiency, the writing efficiency is determined by the number of functional nodes identified as the use case writing manner in the initial test case data and the editing duration, and the execution efficiency is determined by the number of functional nodes identified as the use case executing manner in the initial test case data and the editing duration.
With reference to the third possible implementation manner of the first aspect of the present application, in the fourth possible implementation manner of the first aspect of the present application, the editing state further includes an editor, where the editor is configured to identify whether the editor is a user side, a server side, or a client side, the editing efficiency corresponds to the editor, the execution efficiency includes server execution efficiency and client execution efficiency, the server execution efficiency is determined by the number of functional nodes and the editing duration, which are identified as the use case execution manner and the editor is the server side in the initial test case data, and the client execution efficiency is determined by the number of functional nodes and the editing duration, which are identified as the use case execution manner and the editor is the client side in the initial test case data.
With reference to the first aspect of the present application, in a fifth possible implementation manner of the first aspect of the present application, the method further includes:
the processing equipment receives a query request, wherein the query request is used for requesting to query target process data corresponding to the initial test case data, and the query request comprises a target date range;
the processing equipment extracts target process data in a target date range from the task data;
and the processing equipment feeds back target process data to the initiator of the query request.
With reference to the first aspect of the present application, in a sixth possible implementation manner of the first aspect of the present application, the acquiring, by a processing device, initial test case data entered in a mind map application environment includes:
the processing device runs a mind map application environment;
the processing device receives initial test case data entered by a user in a mind map application environment.
In a second aspect, the present application provides an apparatus for processing task data, the apparatus comprising:
the system comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring initial test case data input in a mind map application environment, and the test case compiling data is test case data compiled aiming at a test task of a target application;
the compiling unit is used for compiling the initial test case data into target test case data matched with a target test environment according to the self content of the initial test case data and the logical relationship between the initial test case data and other test case data, wherein the target test case data is used for executing a test task on a target application in the target test environment;
and the counting unit is used for counting the flow data of the target test case data and storing the flow data in the task data of the test task.
With reference to the second aspect of the present application, in a first possible implementation manner of the second aspect of the present application, the statistical unit is specifically configured to:
extracting edit data of the initial test case data, wherein the edit data is used for describing the edit state of the initial test case data and comprises edit time;
and generating flow data according to the editing data.
With reference to the first possible implementation manner of the second aspect of the present application, in a second possible implementation manner of the second aspect of the present application, the statistical unit is specifically configured to:
determining the number of different functional nodes in the initial test case data and the editing time length according to the editing data;
and determining the processing efficiency of the different functional nodes based on the number of the different functional nodes and the editing time length of the different functional nodes.
In combination with the second possible implementation manner of the second aspect of the present application, in a third possible implementation manner of the second aspect of the present application, the editing state further includes an editing identifier, where the editing identifier is used to identify whether the editing mode is a use case compiling mode or a use case executing mode, the processing efficiency specifically includes compiling efficiency and execution efficiency, the compiling efficiency is determined by the number of functional nodes identified as the use case compiling mode in the initial test case data and the compiling duration, and the execution efficiency is determined by the number of functional nodes identified as the use case executing mode in the initial test case data and the compiling duration.
In combination with the third possible implementation manner of the second aspect of the present application, in the fourth possible implementation manner of the second aspect of the present application, the editing state further includes an editor, where the editor is used to identify whether the editor is a user side, a server side, or a client side, and the editing efficiency corresponds to the editor, and the execution efficiency includes server execution efficiency and client execution efficiency, where the server execution efficiency is determined by the number of functional nodes identified as use case execution manners and the editor is the server side and the editing duration in the initial test case data, and the client execution efficiency is determined by the number of functional nodes identified as use case execution manners and the editor is the client side and the editing duration in the initial test case data.
With reference to the second aspect of the present application, in a fifth possible implementation manner of the second aspect of the present application, the apparatus further includes a query unit, configured to:
receiving a query request, wherein the query request is used for requesting to query target process data corresponding to the initial test case data, and the query request comprises a target date range;
extracting target process data in a target date range from the task data;
and feeding back target process data to the initiator of the query request.
With reference to the second aspect of the present application, in a sixth possible implementation manner of the second aspect of the present application, the obtaining unit is specifically configured to:
running a mind map application environment;
and receiving initial test case data input by a user in the mind map application environment.
In a third aspect, the present application provides a task data processing device, including a processor and a memory, where the memory stores a computer program, and the processor executes the method provided by the first aspect of the present application or any one of the possible implementation manners of the first aspect of the present application when calling the computer program in the memory.
In a fourth aspect, the present application provides a computer-readable storage medium storing a plurality of instructions adapted to be loaded by a processor to perform the method provided in the first aspect of the present application or any one of the possible implementations of the first aspect of the present application.
From the above, the present application has the following advantageous effects:
in the application test background realized based on a mind-leading tool, the application provides additional task data acquisition and processing, after acquiring initial test case data recorded in a mind-leading application environment, processing equipment compiles the initial test case data into target test case data matched with a target test environment according to the self content of the initial test case data and the logical relationship between the initial test case data and other test case data, the target test case data is used for executing a test task on a target application in the target test environment, on the other hand, the processing equipment also counts the flow data of the target test case data and stores the flow data in the task data of the test task, so that the quality of the test case can be better evaluated based on the flow data stored in the task data when the test task is checked later, powerful data support is provided.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
FIG. 1 is a schematic flow chart of a method for processing task data according to the present application;
FIG. 2 is a schematic flow chart illustrating the process of acquiring initial test case data according to the present application;
FIG. 3 is a schematic flow chart illustrating the generation of flow data according to the present application;
FIG. 4 is a schematic diagram of a structure of a task data processing device according to the present application;
fig. 5 is a schematic structural diagram of a task data processing device according to the present application.
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, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The terms "first," "second," and the like in the description and in the claims of the present application and in the above-described drawings are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged under appropriate circumstances such that the embodiments described herein may be practiced otherwise than as specifically illustrated or described herein. Moreover, the terms "comprises," "comprising," and any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or modules is not necessarily limited to those steps or modules explicitly listed, but may include other steps or modules not expressly listed or inherent to such process, method, article, or apparatus. The naming or numbering of the steps appearing in the present application does not mean that the steps in the method flow have to be executed in the chronological/logical order indicated by the naming or numbering, and the named or numbered process steps may be executed in a modified order depending on the technical purpose to be achieved, as long as the same or similar technical effects are achieved.
The division of the modules presented in this application is a logical division, and in practical applications, there may be another division, for example, multiple modules may be combined or integrated into another system, or some features may be omitted, or not executed, and in addition, the shown or discussed coupling or direct coupling or communication connection between each other may be through some interfaces, and the indirect coupling or communication connection between the modules may be in an electrical or other similar form, which is not limited in this application. The modules or sub-modules described as separate components may or may not be physically separated, may or may not be physical modules, or may be distributed in a plurality of circuit modules, and some or all of the modules may be selected according to actual needs to achieve the purpose of the present disclosure.
Before describing the task data processing method provided by the present application, the background related to the present application will be described first.
The method and the device for processing the task data and the computer readable storage medium can be applied to processing equipment of the task data, and are used for counting the process data of the target test case data obtained through the thinking guide diagram application environment when application testing is carried out based on the thinking guide diagram tool, so that the quality of the test case can be better evaluated based on the process data when the test task is checked subsequently, and powerful data support is provided.
In the method for processing task data, an execution main body may be a device that is a processing party of the task data, or a processing device of the task data, such as a server, a physical host, or User Equipment (UE) that is integrated with the device that is the processing party of the task data. The task data processing device may be implemented in a hardware or software manner, the UE may specifically be a terminal device such as a smart phone, a tablet computer, a notebook computer, a desktop computer, or a Personal Digital Assistant (PDA), and the task data processing device may be set in a device cluster manner.
Next, a method for processing task data provided by the present application will be described.
First, referring to fig. 1, fig. 1 shows a schematic flow chart of a processing method of task data in the present application, and the processing method of task data in the present application may specifically include the following steps:
step S101, acquiring initial test case data recorded in a mind map application environment by processing equipment, wherein the data compiled by the test case is the test case data compiled aiming at a test task of a target application;
step S102, compiling the initial test case data into target test case data matched with a target test environment by the processing equipment according to the self content of the initial test case data and the logical relationship between the initial test case data and other test case data, wherein the target test case data is used for executing a test task on a target application in the target test environment;
step S103, the processing equipment counts the flow data of the target test case data and stores the flow data in the task data of the test task.
As can be seen from the embodiment shown in fig. 1, in the context of application testing implemented based on a mind-map tool, the present application provides an additional task data collection process, after acquiring initial test case data recorded in a mind-map application environment, a processing device compiles the initial test case data into target test case data matched with a target test environment according to the content of the initial test case data and the logical relationship between the initial test case data and other test case data, the target test case data is used for executing a test task on a target application in the target test environment, on the other hand, the processing device also counts flow data of the target test case data and stores the flow data in the task data of the test task, and subsequently, when viewing the test task, can better evaluate the quality of the test case based on the flow data stored in the task data, powerful data support is provided.
The steps of the embodiment shown in fig. 1 and the possible implementation manner thereof in practical applications are described in detail below.
In the present application, the mind map application environment may be understood as a writing environment in which test case data is written by the mind map application.
Acquiring initial test case data compiled in the mind map application environment, wherein the initial test case data can be understood as test case data which is compiled in the mind map application environment before being fetched, for example, the initial test case data can be fetched from other equipment; or, the process of writing the test case data in real time in the mind map application environment may be understood as the process of writing the test case data in real time, which may be specifically adjusted according to actual needs, and is not limited herein.
When the test case data is written in real time in the mind map application environment, referring to a flow diagram of the application for acquiring initial test case data shown in fig. 2, the acquiring of test case data may include:
step S201, the processing equipment runs a mind map application environment;
it can be understood that the processing device runs the mind map application environment as a premise for writing initial test case data in real time.
For example, the processing device may run an Xmind-like mind map application for a user, or a tester, to enter and write initial test case data.
Step S202, the processing equipment receives initial test case data which is input by a user in the mind map application environment.
Correspondingly, in the process of running the mind map application environment, the processing device can receive initial test case data which is input by a user in the environment.
The application related to the mind map application environment can be concretely mind map applications such as Xmind, and the like, and the application can express the relationship of themes of each level by using hierarchical graphs which belong to each other and are related to each other in the canvas of the application, and establishes memory links between theme keywords and images, colors and the like to form function nodes with connection relationships.
For application developers, test logics of corresponding test cases can be compiled through the connection relation between the functional nodes, and each functional node can be compiled into corresponding data to be processed according to the test requirements of the target application.
The initial case test data is written for the test task of the target application after the test task of the target application is determined, and the test case data is compiled subsequently according to the target test environment to form target test case data which can execute the application test on the target application in the target test environment.
In the application, after the initial test case data recorded in the mind map application environment is obtained, a plurality of logical connection relation chains formed by the functional nodes included in the initial test case data can be extracted so as to compile the test case.
In the compiling process, the test task is considered, and other test case data which is compiled already can exist, in other words, the currently acquired initial test case data is only a part of the test case data in the test task, and the test case data related to the test task data can also include historical test case data recorded in the thought guide diagram application environment, compiled historical test case data and even test case data which is not acquired yet (which can be understood as test case data which is not recorded in the thought guide diagram application environment or test case data which is not retrieved yet), so that the current initial test case data and the logical relationship between the other test case data can be considered at present, and the current initial test case data and the other test case data are compiled into target test case data matched with the target test environment.
Of course, in practical applications, the currently obtained initial test case data may be complete test case data in the test task, or there may not be other test case data that has been written yet, so in the compiling process, the compiling may be completed only by considering the content of the initial test case itself.
In the present application, for the current test task, additional task data collection processing is configured, and the task data is specifically flow data of the target test case data.
The flow data can be understood to reflect the data related to the flow of the target test case data in the generation link and the execution link, so that the side content of the target test case data can be reflected specifically, the quality of the test case can be better evaluated in the flow when the test task is evaluated subsequently, powerful data support is provided, the work supervision is facilitated, and the work quality of the development work of the target application can be guaranteed.
In the statistical process, starting from the editing state of the data, specifically, editing data can be configured for the target test case data, and the editing data can describe the editing state of the target test case, so that the flow data is counted from the state content described by the editing state.
For example, the time when the target test case data is updated, such as at least one modification time, can be recorded according to the described editing time
Note that the flow data of the target test case data may be not only the flow data of the target test case data itself, but also the flow data of the initial test case data compiled into the target test case data.
At this time, the flow data counted by the present application is flow data of both the target test case data and the initial test case data.
In consideration of the requirement of convenience of statistics, in practical application, the statistical processing of the flow data can also consider starting from the initial test case data, and in the programming data of the initial test case data, the described editing state can also indicate the state content of the compiled target test case data.
Correspondingly, the statistical processing of the process data in the present application may include:
the processing equipment extracts edit data of the initial test case data, wherein the edit data is used for describing the edit state of the initial test case data, and the edit state comprises edit time;
the processing device generates flow data according to the edit data.
As an exemplary implementation, the process data targeted by the present application may be reflected in process efficiency in particular.
Referring to fig. 3, a schematic flow chart of the flow data generation method according to the present application may specifically include the following steps when generating the flow data based on the edit data:
step S301, the processing equipment determines the number of different functional nodes and the editing time length in the initial test case data according to the editing data;
it is understood that, in the present application, the flow data may react in units of functional nodes in the test case data.
In contrast, for the processing efficiency, the number of different functional nodes and the editing time length in the initial test case data can be determined in the editing state content described in the editing data.
The editing time can be directly recorded in the editing state content.
Alternatively, in the case of the modification time point described in the edit status content, the edit time length may be determined based on the time length between the earliest modification time point and the latest modification time point.
Step S302, the processing device determines the processing efficiency of the different functional nodes based on the number of the different functional nodes and the editing duration of the different functional nodes.
Under the condition of determining the number of different functional nodes and the editing time of the different functional nodes, the processing efficiency of the functional nodes can be reflected on the whole.
Specifically, the processing efficiency is the editing duration of the function node and/or the number of function nodes.
Further, corresponding to the above-mentioned flow data reflecting both the initial test case data and the target test case data from the initial test case data side, the processing efficiency mentioned here may be not only the compiling efficiency of the initial test case data itself but also the compiling efficiency of the target test case data, and secondly, when the application test is executed based on the target test case data in the actual application, it is considered that there may be a case where the application test is executed first after the test case data of the functional node is compiled into the target test case data, and therefore, the compiling efficiency of the target test case data may also be regarded as the executing efficiency of the target test case data.
Correspondingly, in addition to the editing time, the editing state described by the editing data can also comprise an editing identifier, and the editing mode of the test case data of the functional node is identified to be a use case writing mode or a use case executing mode through the editing identifier.
The processing efficiency obtained above may specifically be writing efficiency and execution efficiency corresponding to the writing aspect and the execution aspect (also referred to as the compiling aspect), where the writing efficiency is determined by the number of functional nodes identified as the use case writing manner in the initial test case data and the editing duration, and the execution efficiency is determined by the number of functional nodes identified as the use case execution manner in the initial test case data and the editing duration.
In this case, the writing efficiency of the initial test case data involved in the writing process can be reflected, and the execution efficiency of the target test case data in the execution process reflect the flow contents of two links in the test task from the aspect of the two processing efficiencies, if the processing efficiency is relatively too slow, obviously, influence factors exist in the aspects of writing conditions of the related mind map application environment, compiling of target test case data, executing of the target test case data, the target test environment, running of the target application, even related workers and the like, so that backtracking can be intuitively carried out when flow data carried in task data is checked, after determining that some influence factors do not cause influence or neglecting some influence factors, it can be quickly determined which link has slower working efficiency, and there is a need to improve the working efficiency.
In addition, for the target application, in practical application, there is a case that the application relates to a front end and a back end, namely a client (client) and a server (server), specifically, this reverse side can be reflected in an execution link of an application test, and flow data can be distinguished according to the test of the front end and the back end, for example, the processing efficiency described above.
Therefore, in the editing state described in the above editing data, an editing party may be further included, where the editing party is used to identify whether the editing party is a user party, a server party, or a client party, and at this time, the obtained writing efficiency corresponds to the editing party, and the execution efficiency includes server execution efficiency and client execution efficiency.
The server execution efficiency is determined by the number of the functional nodes marked in the initial test case data as the case execution mode and the editor as the server side, the editing time length, and the client side execution efficiency is determined by the number of the functional nodes marked in the initial test case data as the case execution mode and the editor as the client side, the editing time length, and the editing time length.
After the flow data is obtained through statistics, the flow data can be stored in the task data of the test task, and specifically, the flow data can be stored in a classified manner according to classification factors such as different working links or functional nodes.
After the storage, the data can be used for subsequent inquiry, so that the backtracking of the test task is performed on the flow.
For example, the processing device may receive a query request, where the query request is used to request to query target process data corresponding to the initial test case data, and the query request includes a target date range;
it can be understood that the target process data is the process data which the initiator of the query request desires to query currently, and correspondingly, the target date range carried in the query request is the date range of the target process data which the initiator of the query request desires to query in units of dates.
At this time, the processing device may extract target flow data in a target date range from the task data of the current test task, and feed back the target flow data to the initiator of the query request.
In the query scenario, through the process data query in the date range, the process data can be traced back in time units, for example, the work efficiency is traced back, so that various work links on different dates, for example, the compiling efficiency, the server side execution efficiency and the client side execution efficiency, can be visually checked.
The above is an introduction of a method for processing task data provided by the present application, and the present application also provides a device for processing task data, in order to better implement the method for processing task data provided by the present application.
Referring to fig. 4, fig. 4 is a schematic structural diagram of a task data processing device according to the present application, in which the task data processing device 400 may specifically include the following structure:
an obtaining unit 401, configured to obtain initial test case data entered in a mind map application environment, where the test case programming data is test case data written for a test task of a target application;
the compiling unit 402 is configured to compile the initial test case data into target test case data matched with a target test environment according to the self content of the initial test case data and a logical relationship between the initial test case data and other test case data, where the target test case data is used to execute a test task on a target application in the target test environment;
the counting unit 403 is configured to count flow data of the target test case data, and store the flow data in task data of the test task.
In an exemplary implementation manner, the statistics unit 403 may specifically be configured to:
extracting edit data of the initial test case data, wherein the edit data is used for describing the edit state of the initial test case data and comprises edit time;
and generating flow data according to the editing data.
In another exemplary implementation manner, the statistical unit 403 may be specifically configured to:
determining the number of different functional nodes in the initial test case data and the editing time length according to the editing data;
and determining the processing efficiency of the different functional nodes based on the number of the different functional nodes and the editing time length of the different functional nodes.
In yet another exemplary implementation manner, the edit status may further include an edit identifier, where the edit identifier is used to identify whether the edit mode is a use case writing mode or a use case executing mode, and the processing efficiency specifically includes writing efficiency and execution efficiency, where the writing efficiency is determined by the number of functional nodes identified as the use case writing mode in the initial test case data and the edit duration, and the execution efficiency is determined by the number of functional nodes identified as the use case executing mode in the initial test case data and the edit duration.
In yet another exemplary implementation, the editing state may further include an editor, where the editor is configured to identify whether the editor is a user side, a server side, or a client side, the writing efficiency corresponds to the editor, the execution efficiency includes server execution efficiency and client execution efficiency, the server execution efficiency is determined by the sum of the number of function nodes identified in the initial test case data as a use case execution manner, the editor is the server side, and the editing duration, and the client-side execution efficiency is determined by the sum of the number of function nodes identified in the initial test case data as a use case execution manner, the editor is the client side, and the editing duration.
In yet another exemplary implementation, the apparatus may further include a querying unit 404 configured to:
receiving a query request, wherein the query request is used for requesting to query target process data corresponding to the initial test case data, and the query request comprises a target date range;
extracting target process data in a target date range from the task data;
and feeding back target process data to the initiator of the query request.
In another exemplary implementation manner, the obtaining unit 401 may specifically be configured to:
running a mind map application environment;
and receiving initial test case data input by a user in the mind map application environment.
Referring to fig. 5, fig. 5 shows a schematic structural diagram of a processing device for task data of the present application, specifically, the processing device for task data of the present application may include a processor 501, a memory 502, and an input/output device 503, where when the processor 501 is used to execute a computer program stored in the memory 502, each step of the processing method for task data in any embodiment corresponding to fig. 1 to fig. 3 is implemented; alternatively, the processor 501 is configured to implement the functions of the units in the embodiment corresponding to fig. 4 when executing the computer program stored in the memory 502, and the memory 502 is configured to store the computer program required by the processor 501 to execute the processing method of the task data in any of the embodiments corresponding to fig. 1 to 3.
Illustratively, a computer program may be partitioned into one or more modules/units, which are stored in memory 502 and executed by processor 501 to accomplish the present application. One or more modules/units may be a series of computer program instruction segments capable of performing certain functions, the instruction segments being used to describe the execution of a computer program in a computer device.
The processing device of the task data may include, but is not limited to, a processor 501, a memory 502, and an input-output device 503. Those skilled in the art will appreciate that the illustration is merely an example of a processing device for task data, and does not constitute a limitation of the processing device for task data, and may include more or less components than those illustrated, or combine some components, or different components, for example, the processing device for task data may also include a network access device, a bus, etc., and the processor 501, the memory 502, the input output device 503, and the network access device, etc., are connected via the bus.
The Processor 501 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, discrete hardware component, etc. The general purpose processor may be a microprocessor or the processor may be any conventional processor or the like, the processor being the control center for the processing device of task data, with various interfaces and lines connecting the various parts of the overall device.
The memory 502 may be used to store computer programs and/or modules, and the processor 501 may implement various functions of the computer device by running or executing the computer programs and/or modules stored in the memory 502, as well as invoking data stored in the memory 502. The memory 502 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required for at least one function, and the like; the storage data area may store data created according to use of the processing device of the task data, and the like. In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), at least one magnetic disk storage device, a Flash memory device, or other volatile solid state storage device.
The processor 501, when executing the computer program stored in the memory 502, may specifically implement the following functions:
acquiring initial test case data input in a mind map application environment, wherein the test case compiling and writing data is test case data compiled aiming at a test task of a target application;
compiling the initial test case data into target test case data matched with a target test environment according to the self content of the initial test case data and the logical relationship between the initial test case data and other test case data, wherein the target test case data is used for executing a test task on a target application in the target test environment;
and counting the flow data of the target test case data, and storing the flow data in the task data of the test task.
It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the processing apparatus and the processing device for task data and the corresponding units thereof described above may refer to the descriptions of the processing method for task data in any embodiment corresponding to fig. 1 to fig. 3, and are not described herein again in detail.
It will be understood by those skilled in the art that all or part of the steps of the methods of the above embodiments may be performed by instructions or by associated hardware controlled by the instructions, which may be stored in a computer readable storage medium and loaded and executed by a processor.
Therefore, the present application provides a computer-readable storage medium, in which a plurality of instructions are stored, and the instructions can be loaded by a processor to execute steps in the processing method of task data in any embodiment corresponding to fig. 1 to 3 in the present application, and specific operations may refer to descriptions of the processing method of task data in any embodiment corresponding to fig. 1 to 3, which are not described herein again.
Wherein the computer-readable storage medium may include: read Only Memory (ROM), Random Access Memory (RAM), magnetic or optical disks, and the like.
Since the instructions stored in the computer-readable storage medium can execute the steps in the method for processing task data in any embodiment of the present application, such as that shown in fig. 1 to fig. 3, the beneficial effects that can be achieved by the method for processing task data in any embodiment of the present application, such as that shown in fig. 1 to fig. 3, can be achieved, for details, see the foregoing description, and are not repeated herein.
The foregoing detailed description has provided a method, an apparatus, a processing device, and a computer-readable storage medium for processing task data provided by the present application, and a specific example is applied in the present application to explain the principles and embodiments of the present application, and the description of the foregoing embodiment is only used to help understand the method and the core idea of the present application; meanwhile, for those skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.
Claims (10)
1. A method for processing task data, the method comprising:
the method comprises the steps that a processing device obtains initial test case data input in a mind map application environment, wherein the test case compiling data is test case data compiled aiming at a test task of a target application;
the processing equipment compiles the initial test case data into target test case data matched with a target test environment according to the self content of the initial test case data and the logical relationship between the initial test case data and other test case data, wherein the target test case data is used for executing the test task on the target application in the target test environment;
and the processing equipment counts the flow data of the target test case data and stores the flow data in the task data of the test task.
2. The method of claim 1, wherein the processing device counts flow data of the test tasks, comprising:
the processing equipment extracts edit data of the initial test case data, wherein the edit data is used for describing an edit state of the initial test case data, and the edit data comprises edit time;
and the processing equipment generates the flow data according to the editing data.
3. The method of claim 2, wherein the processing device generates the flow data from the edit data, comprising:
the processing equipment determines the number of different functional nodes in the initial test case data and the editing duration according to the editing data;
and the processing equipment determines the processing efficiency of the different functional nodes based on the number of the different functional nodes and the editing duration of the different functional nodes.
4. The method according to claim 3, wherein the edit status further includes an edit identifier, the edit identifier is used to identify whether the edit mode is a use case writing mode or a use case execution mode, the processing efficiency specifically includes writing efficiency and execution efficiency, the writing efficiency is determined by the number of functional nodes identified as the use case writing mode in the initial test case data and the edit duration, and the execution efficiency is determined by the number of functional nodes identified as the use case execution mode in the initial test case data and the edit duration.
5. The method according to claim 4, wherein the edit status further includes an editor for identifying whether the editor is a user side, a server side or a client side, the edit efficiency corresponds to the editor, the execution efficiency includes a server execution efficiency and a client execution efficiency, the server execution efficiency is determined by the number of the function nodes identified in the initial test case data as the example execution mode and the editor as the server side and the edit duration, and the client execution efficiency is determined by the number of the function nodes identified in the initial test case data as the example execution mode and the editor as the client side and the edit duration.
6. The method of claim 1, further comprising:
the processing equipment receives a query request, wherein the query request is used for requesting to query target process data corresponding to the initial test case data, and the query request comprises a target date range;
the processing device extracts the target process data in the target date range from the task data;
and the processing equipment feeds back the target process data to the initiator of the query request.
7. The method of claim 1, wherein the processing device obtains initial test case data entered in a mind map application environment, comprising:
the processing device runs the mind map application environment;
the processing device receives the initial test case data entered by a user in the mind map application environment.
8. An apparatus for processing task data, the apparatus comprising:
the system comprises an acquisition unit, a processing unit and a processing unit, wherein the acquisition unit is used for acquiring initial test case data input in a mind map application environment, and the test case compiling data is test case data compiled aiming at a test task of a target application;
the compiling unit is used for compiling the initial test case data into target test case data matched with a target test environment according to the self content of the initial test case data and the logical relationship between the initial test case data and other test case data, wherein the target test case data is used for executing the test task on the target application in the target test environment;
and the counting unit is used for counting the flow data of the target test case data and storing the flow data in the task data of the test task.
9. A device for processing task data, comprising a processor and a memory, in which a computer program is stored, the processor executing the method according to any one of claims 1 to 7 when calling the computer program in the memory.
10. A computer-readable storage medium storing a plurality of instructions adapted to be loaded by a processor to perform the method of any one of claims 1 to 7.
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Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20050261859A1 (en) * | 2004-05-24 | 2005-11-24 | Jeremy Petsinger | Systems and methods for evaluating a test case |
| US20120254660A1 (en) * | 2011-03-30 | 2012-10-04 | International Business Machines Corporation | Processing test cases for applications to be tested |
| CN107678972A (en) * | 2017-10-27 | 2018-02-09 | 郑州云海信息技术有限公司 | The appraisal procedure and relevant apparatus of a kind of test case |
| CN108845933A (en) * | 2018-05-24 | 2018-11-20 | 广东睿江云计算股份有限公司 | The method and device that software test case is write and evaluated |
| CN109740122A (en) * | 2018-12-11 | 2019-05-10 | 中国联合网络通信集团有限公司 | The conversion method and device of mind map use-case file |
| CN109885474A (en) * | 2018-12-14 | 2019-06-14 | 平安万家医疗投资管理有限责任公司 | Test case edit methods and device, terminal and computer readable storage medium |
| CN111104317A (en) * | 2019-12-09 | 2020-05-05 | 紫光云(南京)数字技术有限公司 | Method for realizing efficient editing and execution management of test cases |
| CN111290956A (en) * | 2020-02-17 | 2020-06-16 | 贵阳货车帮科技有限公司 | Brain graph-based testing method and device, electronic equipment and storage medium |
| CN111338936A (en) * | 2020-02-17 | 2020-06-26 | 贵阳货车帮科技有限公司 | Brain graph data processing method and device, electronic equipment and storage medium |
| CN112069062A (en) * | 2020-08-21 | 2020-12-11 | 苏州浪潮智能科技有限公司 | Method and device for editing and generating software test bug module |
-
2020
- 2020-12-23 CN CN202011538240.9A patent/CN112579454B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20050261859A1 (en) * | 2004-05-24 | 2005-11-24 | Jeremy Petsinger | Systems and methods for evaluating a test case |
| US20120254660A1 (en) * | 2011-03-30 | 2012-10-04 | International Business Machines Corporation | Processing test cases for applications to be tested |
| CN107678972A (en) * | 2017-10-27 | 2018-02-09 | 郑州云海信息技术有限公司 | The appraisal procedure and relevant apparatus of a kind of test case |
| CN108845933A (en) * | 2018-05-24 | 2018-11-20 | 广东睿江云计算股份有限公司 | The method and device that software test case is write and evaluated |
| CN109740122A (en) * | 2018-12-11 | 2019-05-10 | 中国联合网络通信集团有限公司 | The conversion method and device of mind map use-case file |
| CN109885474A (en) * | 2018-12-14 | 2019-06-14 | 平安万家医疗投资管理有限责任公司 | Test case edit methods and device, terminal and computer readable storage medium |
| CN111104317A (en) * | 2019-12-09 | 2020-05-05 | 紫光云(南京)数字技术有限公司 | Method for realizing efficient editing and execution management of test cases |
| CN111290956A (en) * | 2020-02-17 | 2020-06-16 | 贵阳货车帮科技有限公司 | Brain graph-based testing method and device, electronic equipment and storage medium |
| CN111338936A (en) * | 2020-02-17 | 2020-06-26 | 贵阳货车帮科技有限公司 | Brain graph data processing method and device, electronic equipment and storage medium |
| CN112069062A (en) * | 2020-08-21 | 2020-12-11 | 苏州浪潮智能科技有限公司 | Method and device for editing and generating software test bug module |
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|---|---|
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