CN116340090A - Method, device, equipment and storage medium for identifying software based on interaction sequence - Google Patents
Method, device, equipment and storage medium for identifying software based on interaction sequence Download PDFInfo
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Abstract
The invention belongs to the technical field of computers, and discloses a software identification method, device and equipment based on an interaction sequence and a storage medium. The method comprises the following steps: acquiring an initial interaction sequence of a target interaction transaction in an edge X scene; calculating interaction weights of a plurality of software interaction modes according to the initial interaction sequence; generating a software interaction sequence library according to the interaction weight of each software interaction mode; and completing the software identification of the edge X scene according to the software interaction sequence library. By the method, the software identification of the edge X scene is completed according to the software interaction sequence library, so that an important software module of the edge X in the interaction process of the service scene is obtained, problem software can be rapidly positioned in the face of risks in the edge X service scene, hazards caused by the risks are reduced, and reference guidance is provided for enterprises to find bottlenecks and hidden dangers of dependent software in the edge X service scene.
Description
Technical Field
The present invention relates to the field of computer technologies, and in particular, to a method, an apparatus, a device, and a storage medium for identifying software based on an interaction sequence.
Background
The edge X is an open-source and provider-neutral edge Internet of things middleware platform, is specifically expressed as edge X Foundation, can collect data from edge sensors, completes data sending and receiving among enterprises, cloud and local equipment, is used as a conversion engine of the enterprises between cloud and local Internet of things equipment, and can reduce uncertainty in application development, accelerate deployment time and promote scale. As a highly flexible and expandable open source software framework, the edge X implementation supports access to a variety of physical devices to encourage the Internet of things solution providers to work cooperatively in a unified ecosystem. In the face of such complex physical device conditions and service environments, the EdgeX needs to rely on numerous complex software modules to realize secure docking and interaction of the physical devices so as to complete complex and diverse service scenarios.
As middleware among the edge physical sensing device, the execution device and the cloud information system, the edge X depends on a plurality of complex software modules. The dependent software modules relate to aspects of the Edge X operation, an API interface of a generating, describing, calling and visualizing RESTful style uses a Swaggerhub interface framework, an LF Edge eKuiper completes streaming data processing of an Edge end based on a rule engine with a certain design to realize ultra-light Internet of things Edge data analysis, angularJS builds a brand-new user visual interface to keep consistency with an industry standard and promote maintainability of the visual interface, and besides, the Edge X also relates to Redis, kubernetes, consulACL and other series of software modules to complete functions of data storage, service management, access control and the like. The dependent software modules form a complex software network in the specific application scene of the edge X, and the edge X interacts with different dependent software under different service scenes to form different software interaction sequences. Because the EdgeX needs to interact with massive complex software in the service scene, important software modules in the interaction process need to be identified so as to face the problem software which can be rapidly positioned when risks occur in the EdgeX service scene, and the harm caused by the risks is reduced.
Currently, analysis of key nodes and key modules in software is mainly from the view point of graph theory. Some studies indicate that software systems also exist in complex networks with "small world", "no scale" characteristics, and thus the software system can be mapped into a complex graph for research. Some studies follow this idea, and from different granularities, consider software, packages, components, classes, functions, statements, etc. as nodes, and dependencies, call relationships, etc. as edges between nodes, thereby mapping the software into a complex network. Based on the modeling background, a series of methods such as centrality index, network layering, network clustering and the like in graph theory can be adopted to study the software system. Some researches adopt centrality indexes in graph theory, such as h-index, medium centrality and the like, to describe some key nodes in a software system; some studies measure connectivity in software systems through a cohesive metric of the software network. In recent years, due to the development of artificial intelligence technology, some recent studies have been directed to analysis of software systems in combination with graphic neural networks. However, the researches are all theoretical methods in graph theory, which directly consider the software system as a complex graph structure, and do not combine a series of unique characteristics of dynamic execution, interaction sequence and the like in the software system. Some research methods combined with dynamic execution of software only collect relevant execution information for analysis in the execution process of the software system, and a series of key nodes such as software and classes in the software system are identified through statistical data, so that the characteristics of complex graph structures in the software system are not well combined. Therefore, there is a need to provide a method for identifying key software in the EdgeX service scenario from the perspective of a software interaction sequence.
Disclosure of Invention
The invention mainly aims to provide a software identification method, device, equipment and storage medium based on an interaction sequence, and aims to solve the technical problem of how to identify key software in an edge X service scene based on the software interaction sequence in the prior art.
In order to achieve the above object, the present invention provides a software identification method based on an interaction sequence, the software identification method based on the interaction sequence comprising:
acquiring an initial interaction sequence of a target interaction transaction in an edge X scene;
calculating interaction weights of a plurality of software interaction modes according to the initial interaction sequence;
generating a software interaction sequence library according to the interaction weight of each software interaction mode;
and completing the software identification of the edge X scene according to the software interaction sequence library.
Optionally, the calculating the interaction weights of the plurality of software interaction modes according to the initial interaction sequence includes:
performing software deduplication on the initial interaction sequence to obtain a target interaction sequence;
determining a plurality of software interaction modes, the interaction times of each software interaction mode, the interaction length of each software interaction mode and the sequence length of the target interaction sequence according to the target interaction sequence;
Calculating the mode weight of each software interaction mode according to the interaction times of each software interaction mode, the interaction length of each software interaction mode and the sequence length;
and calculating the interaction weight of each software interaction mode according to the mode weight of each software interaction mode and the total number of interaction sequences.
Optionally, the generating a software interaction sequence library according to the interaction weight of each software interaction mode includes:
acquiring a preset weight threshold;
screening each software interaction mode according to the interaction weight of each software interaction mode and the preset weight threshold value to obtain a target interaction mode;
and generating a software interaction sequence library according to the target interaction mode.
Optionally, the software identifying the EdgeX scene according to the software interaction sequence library includes:
initializing the length of the software interaction mode to obtain an initial interaction length;
determining candidate interaction modes according to the initial interaction length and the software interaction sequence library;
determining a spliced interaction mode according to the interaction weight of the candidate interaction mode;
and updating the software interaction sequence library according to the splicing interaction mode to obtain an updated interaction sequence library.
Optionally, the determining the stitching interaction mode according to the interaction weight of the candidate interaction mode includes:
sorting according to the interaction weights of the candidate interaction modes to obtain a sorting result;
determining a first interaction mode according to the sorting result and a preset screening condition;
determining a second interaction mode according to the initial interaction length and the software interaction sequence library;
splicing according to the first interaction mode, the second interaction mode and a preset splicing mode, and determining a plurality of third interaction modes;
and calculating the interaction weight of each third interaction mode, and determining a spliced interaction mode in the plurality of third interaction modes according to a preset weight threshold and the interaction weight of each third interaction mode.
Optionally, after updating the software interaction sequence library according to the splicing interaction mode to obtain the updated interaction sequence library, the method further includes:
determining a key interaction mode according to the updated interaction sequence library;
calculating the adjacent transition probability of each software node in the edge X scene according to the interaction weight of the key interaction mode;
constructing a transition probability matrix of each software node according to the adjacent transition probability of each software node;
Calculating the stay probability of each software node according to the transition probability matrix of each software node;
node division is carried out according to the stay probability of each software node, and a division result is obtained;
and generating a software community according to the division result.
Optionally, the constructing a transition probability matrix of each software node according to the adjacent transition probability of each software node includes:
determining the adjacency influence weight of each software node according to the number of the interactive interfaces and the number of the external interfaces of each software node;
calculating the structural influence weight of each software node according to the input degree, the output degree and the dependence uniformity of each software node;
determining target transition probability of each software node according to preset transition weight, adjacent influence weight of each software node, structure influence weight of each software node and adjacent transition probability of each software node;
and constructing a transition probability matrix of each software node according to the target transition probability of each software node.
In addition, in order to achieve the above object, the present invention also provides a software identification device based on an interaction sequence, where the software identification device based on the interaction sequence includes:
the acquisition module is used for acquiring an initial interaction sequence of a target interaction transaction in the edge X scene;
The computing module is used for computing interaction weights of a plurality of software interaction modes according to the initial interaction sequence;
the generating module is used for generating a software interaction sequence library according to the interaction weight of each software interaction mode;
and the completion module is used for completing the software identification of the edge X scene according to the software interaction sequence library.
In addition, to achieve the above object, the present invention also proposes an interactive sequence-based software identification device, including: the system comprises a memory, a processor, and an interactive sequence based software identification program stored on the memory and executable on the processor, the interactive sequence based software identification program configured to implement the interactive sequence based software identification method as described above.
In addition, in order to achieve the above object, the present invention also proposes a storage medium having stored thereon an interactive sequence based software identification program which, when executed by a processor, implements the interactive sequence based software identification method as described above.
The method comprises the steps of obtaining an initial interaction sequence of a target interaction transaction in an edge X scene; calculating interaction weights of a plurality of software interaction modes according to the initial interaction sequence; generating a software interaction sequence library according to the interaction weight of each software interaction mode; and completing the software identification of the edge X scene according to the software interaction sequence library. By the method, the interaction weights of a plurality of software interaction modes are calculated based on the initial interaction sequence of the target interaction transaction in the edge X scene, a software interaction sequence library is generated according to the interaction weights of the software interaction modes, and the software identification of the edge X scene is completed according to the software interaction sequence library, so that important software modules of the edge X in the interaction process of the service scene are obtained, risk-bearing problem software in the edge X service scene can be rapidly located, risks caused by the risks are reduced, and reference guidance is provided for enterprises to find bottlenecks and hidden dangers depending on the software in the edge X service scene.
Drawings
FIG. 1 is a schematic diagram of an interactive sequence based software identification device of a hardware runtime environment in accordance with an embodiment of the present invention;
FIG. 2 is a flowchart of a first embodiment of a software identification method based on an interaction sequence according to the present invention;
FIG. 3 is a flowchart of a second embodiment of the interactive sequence based software identification method of the present invention;
FIG. 4 is a schematic overall flow chart of an embodiment of a software identification method based on an interaction sequence according to the present invention;
fig. 5 is a block diagram of a first embodiment of the software identification device based on the interactive sequence according to the present invention.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Referring to fig. 1, fig. 1 is a schematic structural diagram of a software identification device based on an interaction sequence in a hardware running environment according to an embodiment of the present invention.
As shown in fig. 1, the interactive sequence-based software identification device may include: a processor 1001, such as a central processing unit (Central Processing Unit, CPU), a communication bus 1002, a user interface 1003, a network interface 1004, a memory 1005. Wherein the communication bus 1002 is used to enable connected communication between these components. The user interface 1003 may include a Display, an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may further include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a Wireless interface (e.g., a Wireless-Fidelity (Wi-Fi) interface). The Memory 1005 may be a high-speed random access Memory (Random Access Memory, RAM) Memory or a stable nonvolatile Memory (NVM), such as a disk Memory. The memory 1005 may also optionally be a storage device separate from the processor 1001 described above.
It will be appreciated by those skilled in the art that the structure shown in fig. 1 does not constitute a limitation of the interactive sequence based software recognition device, and may include more or fewer components than shown, or may combine certain components, or may be arranged in different components.
As shown in fig. 1, an operating system, a network communication module, a user interface module, and an interactive sequence-based software recognition program may be included in the memory 1005 as one storage medium.
In the interactive sequence-based software identification device shown in fig. 1, the network interface 1004 is mainly used for data communication with a network server; the user interface 1003 is mainly used for data interaction with a user; the processor 1001 and the memory 1005 in the interactive sequence-based software identification device of the present invention may be disposed in the interactive sequence-based software identification device, where the interactive sequence-based software identification device invokes the interactive sequence-based software identification program stored in the memory 1005 through the processor 1001, and executes the interactive sequence-based software identification method provided by the embodiment of the present invention.
The embodiment of the invention provides a software identification method based on an interaction sequence, and referring to fig. 2, fig. 2 is a flow diagram of a first embodiment of the software identification method based on the interaction sequence.
The software identification method based on the interaction sequence comprises the following steps:
step S10: and acquiring an initial interaction sequence of the target interaction transaction in the edge X scene.
It should be noted that, the execution body of the embodiment is a terminal device, and the terminal device may be an intelligent terminal such as a computer, a tablet, etc., which is not limited in this embodiment. The terminal equipment obtains an initial interaction sequence of a target interaction transaction in the EdgeX (EdgeX Foundry) scene, calculates interaction weights of a plurality of software interaction modes according to the initial interaction sequence, generates a software interaction sequence library according to the interaction weights of the software interaction modes, completes software identification of the edge X scene according to the software interaction sequence library, and the edge X in the follow-up embodiment is specifically expressed as edge X foundation.
It is understood that the target interactive transaction refers to all interactive transactions within a preset time period. For example, for a continuous period of time
Has->
An interactive transaction, consecutive periods->
Is provided with->
The individual interaction transaction is the target interaction transaction. The initial interaction sequence is a continuous period +.>
Is provided with->
Sequence set consisting of software interaction sequences of individual interaction transactions +.>
Wherein->
Representing +. >
A software interaction sequence, a software interaction sequence->
By->
A software node composition with dependency or call relationship, expressed as +.>
，/>
Expressed as +.>
And software nodes.
Step S20: and calculating interaction weights of a plurality of software interaction modes according to the initial interaction sequence.
It should be noted that, according to the initial interaction sequence, the occurrence weight of each software interaction mode in the EdgeX service scene is calculated, and the occurrence weight of each software interaction mode in the EdgeX service scene is the interaction weight of each software interaction mode.
It may be appreciated that, to obtain accurate interaction weights according to an initial interaction sequence, further, the calculating the interaction weights of a plurality of software interaction modes according to the initial interaction sequence includes: performing software deduplication on the initial interaction sequence to obtain a target interaction sequence; determining a plurality of software interaction modes, the interaction times of each software interaction mode, the interaction length of each software interaction mode and the sequence length of the target interaction sequence according to the target interaction sequence; calculating the mode weight of each software interaction mode according to the interaction times of each software interaction mode, the interaction length of each software interaction mode and the sequence length; and calculating the interaction weight of each software interaction mode according to the mode weight of each software interaction mode and the total number of interaction sequences.
In a specific implementation, the interaction software deduplication is performed on the collected initial interaction sequence, and the initial interaction sequence after deduplication is the target interaction sequence. Each of the software interaction sequences in the target interaction sequence
An interactive software set can be formed +.>
Corresponding to a software interaction mode, so that the occurrence times of each software interaction mode in each software interaction sequence of the target interaction sequence, the length of each software interaction mode and the length of each software interaction sequence in the target interaction sequence are determined according to the target interaction sequence, wherein the length of each software interaction sequence in the target interaction sequence is the sequence length of the target interaction sequence>
The length of each software interaction mode is the interaction length of each software interaction mode>
The occurrence frequency of each software interaction mode in each software interaction sequence is the interaction frequency of each software interaction mode +.>
。
It should be noted that, the weight of each software interaction set is calculated according to the interaction times of each software interaction mode, the interaction length of each software interaction mode and the sequence length
Weights of the respective software interaction sets +.>
I.e. the mode weight of each software interaction mode, wherein +.>
。
It will be appreciated that the total number of interaction sequences refers to the number of software interaction sequences in the initial interaction sequence, i.e. the total number of all software interaction sequences in a continuous period 
. For an interaction software set->
Possibly in multiple EdgeX business interaction scenarios, so that the software interaction mode corresponding to the interaction software set needs to be calculated to have the weight of occurrence in multiple interaction transactions of EdgeX +.>
Obtained->
And the occurrence probability weight of the software interaction mode in the edge X service scene is represented, namely the interaction weight of each software interaction mode. Wherein (1)>
For interacting software sets
In->
And the corresponding mode weight in the secondary service interaction scene.
Step S30: and generating a software interaction sequence library according to the interaction weight of each software interaction mode.
It should be noted that, in determining the interaction weight of each software interaction mode
Thereafter, based on each software interactionThe interaction weight of the mode filters the software interaction mode, the software interaction mode after screening is the software interaction mode frequently appearing in the EdgeX service scene, and a software interaction sequence library is generated based on the software interaction mode after screening.
It may be appreciated that, to generate an accurate software interaction sequence library based on the interaction weights of the software interaction modes, further, the generating a software interaction sequence library according to the interaction weights of the software interaction modes includes: acquiring a preset weight threshold; screening each software interaction mode according to the interaction weight of each software interaction mode and the preset weight threshold value to obtain a target interaction mode; and generating a software interaction sequence library according to the target interaction mode.
In a specific implementation, the preset weight threshold refers to a preset screening weight threshold
Screening different interaction software sets according to a preset weight threshold and the interaction weight of each software interaction mode to obtain the frequently occurring software interaction modes in the EdgeX interaction process, wherein the software interaction modes are +>
，/>
Is a software interaction pattern (target interaction pattern) frequently appearing in the edge X business scene, and is according to the target interaction pattern +.>
A library of software interaction sequences may be generated.
Step S40: and completing the software identification of the edge X scene according to the software interaction sequence library.
It should be noted that, identification of key software in the edge service scene can be completed according to the generated software interaction sequence library, and data support is provided for further mining of key software interaction modes.
In the embodiment, network information of an edge X network is obtained; calculating node bridging weights of all nodes according to the network information; determining a bridging target node according to the node bridging weight of each node; and finishing node detection of the edge X network according to the bridging target node. By the method, the node bridging weight of each node is calculated according to the network information of the edge X network, the bridging target node is determined according to the node bridging weight of each node, the node detection of the edge X network is completed according to the bridging target node, the rationality of static network design and the dynamically changing service scene in the edge X are fully considered, the nodes in the edge X network can be objectively evaluated in a multi-scale and real-time manner, the bridging target node is obtained, the business scene can be better helped by enterprises to find the optimization direction, and the overall performance of the system is improved.
Referring to fig. 3, fig. 3 is a flowchart of a second embodiment of a software identification method based on an interaction sequence according to the present invention.
Based on the first embodiment, the step S40 in the software identification method based on the interaction sequence according to the present embodiment includes:
step S41: initializing the length of the software interaction mode to obtain the initial interaction length.
It should be noted that, initializing the software interaction pattern length to obtain the initial interaction length
。
Step S42: and determining candidate interaction modes according to the initial interaction length and the software interaction sequence library.
It should be noted that, the software interaction sequence library is scanned, the frequently occurring software interaction mode with the length being the initial interaction length is used as the software interaction mode of candidate splicing, and the software interaction mode of candidate splicing is the candidate interaction mode
。
Step S43: and determining a spliced interaction mode according to the interaction weight of the candidate interaction mode.
It should be noted that, the interaction weights of the candidate interaction modes are obtained, and the newly simplified spliced software interaction mode is determined according to the interaction weights of the candidate interaction modes, and is the spliced interaction mode.
It may be appreciated that, in order to obtain an accurate spliced interaction mode according to the interaction weight of the candidate interaction mode, further, determining the spliced interaction mode according to the interaction weight of the candidate interaction mode includes: sorting according to the interaction weights of the candidate interaction modes to obtain a sorting result; determining a first interaction mode according to the sorting result and a preset screening condition; determining a second interaction mode according to the initial interaction length and the software interaction sequence library; splicing according to the first interaction mode, the second interaction mode and a preset splicing mode, and determining a plurality of third interaction modes; and calculating the interaction weight of each third interaction mode, and determining a spliced interaction mode in the plurality of third interaction modes according to a preset weight threshold and the interaction weight of each third interaction mode.
In a specific implementation, the candidate interaction pattern is selected according to
And (3) carrying out reverse order sequencing on the interaction weights to obtain a corresponding sequencing result. The preset screening condition refers to a preset screening proportion +.>
. After the sorting result is obtained, selecting the front +.>
% software interaction pattern as candidate software interaction pattern for subsequent splice aggregation +.>
Candidate software interaction mode of subsequent splicing aggregation +.>
I.e. the first interaction pattern.
It should be noted that, determining the scan screening length according to the initial interaction length,scanning and screening length of
Scanning in a software interaction sequence library to obtain a scanning screening length>
Software interaction mode->
Scanning screening Length->
Software interaction mode->
Namely a second interaction mode.
It can be understood that the preset splicing mode refers to a preset mode of splicing and aggregating the first interaction mode and the second interaction mode. Splicing and polymerizing the first interaction mode and the second interaction mode according to a preset splicing mode: if the first interaction mode
Suffix of (2) and second interaction pattern->
Before->
Bit anastomosis, i.e.
The software interaction mode of the new splice aggregation is +.>
. If the first interaction pattern->
Before- >
Suffix of bit and second interaction pattern +.>
Before->
Bit anastomosis, i.e.
And->
And->
If the direct or indirect dependency relationship exists, the software interaction mode of the new splicing aggregation is +.>
Splicing and polymerizing the first interaction mode and the second interaction mode according to a preset splicing mode to obtain a new splicing and polymerizing software interaction mode ∈>
Namely a third interaction mode.
In a specific implementation, a plurality of third interaction patterns are calculated
Appearance weight in edge X service scene, third interaction mode +.>
The occurrence weight in the edge X service scene is the interaction weight of the third interaction mode
Wherein->
Representing the number of times the third interaction pattern appears in the whole EdgeX business interaction scene, +.>
Indicate->
The software node length of the secondary software interaction sequence.
It should be noted that, after determining the interaction weight of the third interaction mode, according to the preset weight threshold value
Screening the third interaction mode according to the interaction weight of the third interaction mode, and if the interaction weight of the third interaction mode is +.>
Not less than a preset weight threshold +.>
It is determined to be a splice interaction pattern and otherwise the third interaction pattern is directly discarded. Increase the software interaction length to be spliced +.>
Continuing to iterate the step of determining the spliced interaction mode according to the interaction weight of the candidate interaction mode until the candidate interaction mode meeting the condition cannot be found in the software interaction sequence library +. >
。
Step S44: and updating the software interaction sequence library according to the splicing interaction mode to obtain an updated interaction sequence library.
It should be noted that, after determining the splicing interaction mode, the splicing interaction mode is added to the software interaction sequence library to update the software interaction sequence library, so as to obtain an updated software interaction sequence library, and the updated software interaction sequence library is the updated interaction sequence library.
It can be appreciated that a suitable software interaction sequence is selected from the software interaction sequence library, a series of operations such as aggregation and splicing are performed to generate a software interaction pattern which may not be involved in the edge x service scene, and then the generated third interaction pattern is evaluated based on the whole edge x service scene and added into the software interaction sequence library to further generate other software interaction patterns.
In a specific implementation, in order to face the problem software that risks in the edge x service scene can be rapidly located, and reduce the harm caused by the risks, a key software community in the edge x scene can be further discovered, and further, after the software interaction sequence library is updated according to the splicing interaction mode, the method further includes: determining a key interaction mode according to the updated interaction sequence library; calculating the adjacent transition probability of each software node in the edge X scene according to the interaction weight of the key interaction mode; constructing a transition probability matrix of each software node according to the adjacent transition probability of each software node; calculating the stay probability of each software node according to the transition probability matrix of each software node; node division is carried out according to the stay probability of each software node, and a division result is obtained; and generating a software community according to the division result.
It should be noted that, the key software interaction mode is extracted by using the constructed updated interaction sequence library, and the key software interaction mode is the key interaction mode. For each node in the EdgeX dependent software graph, the interaction weight according to the key interaction mode
Normalizing to obtain the adjacent transition probability of each software node in the dependent software graph of the edge X scene
Wherein->
The interactive sequence library contains nodes for updating>
And node->
And node->
，/>
Software interaction mode with dependency>
For updating the nodes +.>
Is provided.
It can be appreciated that, according to the adjacent transition probabilities of the software nodes, a transition probability matrix W of each node in the EdgeX dependent software graph can be constructed. The probability of finally converging and staying at other nodes from each node can be calculated according to the transition probability matrix of each software node
Probability of finally converging to stay at other nodes starting from each node +.>
I.e. the stay probability of each software node.
In the specific implementation, the stay probability of each software node is ordered in a reverse order, and node division is carried out at the position where the difference of the arrival stay probabilities is the maximum value, so that other software nodes similar to the initial node are obtained and combined into a software community.
It should be noted that, determining a main software interaction sequence path in the EdgeX service scene by using a software interaction mode in the updated interaction sequence library; combining graph structures of the EdgeX dependent software to synthesize probability weights of different software interaction modes; determining key software communities in the edge X dependent software network from the software nodes according to a random walk method with a certain probability distribution, wherein the obtained software communities correspond to the software nodes actually operated in the edge X service scene, and the software nodes in the same software communities can be called together in the process of interaction of the edge X in one service scene. Based on the software community, maintenance personnel can predict the called software module in the edge service scene in advance, and the expansion scheduling task is done in advance.
It may be appreciated that, in order to accurately construct a transition probability matrix of each software node according to the adjacent transition probability of each software node, further, the constructing a transition probability matrix of each software node according to the adjacent transition probability of each software node includes: determining the adjacency influence weight of each software node according to the number of the interactive interfaces and the number of the external interfaces of each software node; calculating the structural influence weight of each software node according to the input degree, the output degree and the dependence uniformity of each software node; determining target transition probability of each software node according to preset transition weight, adjacent influence weight of each software node, structure influence weight of each software node and adjacent transition probability of each software node; and constructing a transition probability matrix of each software node according to the target transition probability of each software node.
In a specific implementation, in order to avoid updating only partial dependent software nodes or only partial software interaction sequences in the interaction sequence library, the graph structure information in the EdgeX dependent software graph is introduced to the nodes
And node->
The transition probability between the two is adjusted, the dependence influence of each software node on adjacent software is considered according to the number of the interaction interfaces and the number of the external interfaces of each software node, the influence weight of the adjacent node is calculated, and the influence weight of the adjacent node is the adjacent influence weight
Wherein->
Refers to the software node ++in the EdgeX dependent software graph>
Relying on software node->
The number of interactive interfaces, < >>
Refers to software node->
Is>
，/>
Refers to software node->
Is software node->
Dependent interactive interface number, ++>
Refers to software node->
Is provided.
It should be noted that, considering the external structure influence of the software, the external structure influence weight of the software is calculated, and the external structure influence weight of the software node is the structure influence weight of each software node. The structural influence weight is as follows
Wherein->
Refers to software node->
Degree of penetration of->
Refers to software node->
Degree of emergence of->
Refers to the variance of the number of nodes at both ends of the dependent edge, < > >
Can represent software node +.>
，/>
Is dependent on uniformity.
It will be appreciated that after determining the adjacency impact weight of each software node, the structure impact weight of each software node, and the adjacency transition probability of each software node, the nodes can be aligned
And node->
The transition probability between the two is adjusted:
wherein->
For the preset weight, satisfy +.>
，/>
The larger the representation, the more emphasis is placed on the corresponding transition probabilities in the sequence of software interactions, +.>
The larger the representation, the more emphasis is placed on the network topology information in the software map, the resulting +.>
Namely, the target transition probability of each software node is used for constructing the transition probability of each software node in the software dependency graph according to the target transition probability of each software nodeAnd a matrix W.
In a specific implementation, as shown in fig. 4, the duplication is removed according to an initial interaction sequence, the interaction weight of each software interaction mode is calculated, a key software interaction mode is determined, a software interaction sequence library is generated according to the key software interaction mode, the key software interaction mode is further mined based on the software interaction sequence library, the software interaction sequence library is updated based on the mined spliced interaction mode to obtain an updated interaction sequence library, the transition probability adjacent influence weight, the structure influence weight and the adjacent transition probability of each software node are calculated based on the software interaction mode in the updated interaction sequence library, the target capture transition probability of each software node is determined, the construction of a transition probability matrix is performed, the stay probability of each software node is calculated in an iterative manner, and finally a key software community is formed based on the stay probability of each software.
In the embodiment, the initial interaction length is obtained by initializing the length of the software interaction mode; determining candidate interaction modes according to the initial interaction length and the software interaction sequence library; determining a spliced interaction mode according to the interaction weight of the candidate interaction mode; and updating the software interaction sequence library according to the splicing interaction mode to obtain an updated interaction sequence library. By the method, candidate interaction modes are determined according to the initial interaction length and the software interaction sequence library, splicing interaction modes are determined according to the interaction weights of the candidate interaction modes, finally, the software interaction sequence library is updated based on the splicing interaction modes to obtain an updated interaction sequence library, key software interaction modes are further mined through splicing and aggregation of different software interaction modes, and the situation that only part of key software interaction modes are identified due to sampling deviation of an edge X operation service scene is avoided.
In addition, referring to fig. 5, an embodiment of the present invention further provides an interaction sequence-based software identification device, where the interaction sequence-based software identification device includes:
the acquiring module 10 is configured to acquire an initial interaction sequence of a target interaction transaction in the EdgeX scene.
A calculation module 20, configured to calculate interaction weights of a plurality of software interaction modes according to the initial interaction sequence.
The generating module 30 is configured to generate a software interaction sequence library according to the interaction weights of the software interaction modes.
And a completing module 40, configured to complete software identification of the EdgeX scene according to the software interaction sequence library.
The method comprises the steps of obtaining an initial interaction sequence of a target interaction transaction in an edge X scene; calculating interaction weights of a plurality of software interaction modes according to the initial interaction sequence; generating a software interaction sequence library according to the interaction weight of each software interaction mode; and completing the software identification of the edge X scene according to the software interaction sequence library. By the method, the interaction weights of a plurality of software interaction modes are calculated based on the initial interaction sequence of the target interaction transaction in the edge X scene, a software interaction sequence library is generated according to the interaction weights of the software interaction modes, and the software identification of the edge X scene is completed according to the software interaction sequence library, so that important software modules of the edge X in the interaction process of the service scene are obtained, risk-bearing problem software in the edge X service scene can be rapidly located, risks caused by the risks are reduced, and reference guidance is provided for enterprises to find bottlenecks and hidden dangers depending on the software in the edge X service scene.
In an embodiment, the computing module 20 is further configured to perform software deduplication on the initial interaction sequence to obtain a target interaction sequence;
determining a plurality of software interaction modes, the interaction times of each software interaction mode, the interaction length of each software interaction mode and the sequence length of the target interaction sequence according to the target interaction sequence;
calculating the mode weight of each software interaction mode according to the interaction times of each software interaction mode, the interaction length of each software interaction mode and the sequence length;
and calculating the interaction weight of each software interaction mode according to the mode weight of each software interaction mode and the total number of interaction sequences.
In an embodiment, the generating module 30 is further configured to obtain a preset weight threshold;
screening each software interaction mode according to the interaction weight of each software interaction mode and the preset weight threshold value to obtain a target interaction mode;
and generating a software interaction sequence library according to the target interaction mode.
In an embodiment, the completion module 40 is further configured to initialize the length of the software interaction mode to obtain an initial interaction length;
determining candidate interaction modes according to the initial interaction length and the software interaction sequence library;
Determining a spliced interaction mode according to the interaction weight of the candidate interaction mode;
and updating the software interaction sequence library according to the splicing interaction mode to obtain an updated interaction sequence library.
In an embodiment, the completing module 40 is further configured to sort according to the interaction weights of the candidate interaction modes, so as to obtain a sorting result;
determining a first interaction mode according to the sorting result and a preset screening condition;
determining a second interaction mode according to the initial interaction length and the software interaction sequence library;
splicing according to the first interaction mode, the second interaction mode and a preset splicing mode, and determining a plurality of third interaction modes;
and calculating the interaction weight of each third interaction mode, and determining a spliced interaction mode in the plurality of third interaction modes according to a preset weight threshold and the interaction weight of each third interaction mode.
In an embodiment, the completion module 40 is further configured to determine a key interaction pattern according to the updated interaction sequence library;
calculating the adjacent transition probability of each software node in the edge X scene according to the interaction weight of the key interaction mode;
constructing a transition probability matrix of each software node according to the adjacent transition probability of each software node;
Calculating the stay probability of each software node according to the transition probability matrix of each software node;
node division is carried out according to the stay probability of each software node, and a division result is obtained;
and generating a software community according to the division result.
In an embodiment, the completion module 40 is further configured to determine an adjacency impact weight of each software node according to the number of interaction interfaces and the number of external interfaces of each software node;
calculating the structural influence weight of each software node according to the input degree, the output degree and the dependence uniformity of each software node;
determining target transition probability of each software node according to preset transition weight, adjacent influence weight of each software node, structure influence weight of each software node and adjacent transition probability of each software node;
and constructing a transition probability matrix of each software node according to the target transition probability of each software node.
Because the device adopts all the technical schemes of all the embodiments, the device at least has all the beneficial effects brought by the technical schemes of the embodiments, and the description is omitted here.
In addition, the embodiment of the invention also provides a storage medium, wherein the storage medium is stored with a software identification program based on the interaction sequence, and the software identification program based on the interaction sequence realizes the steps of the software identification method based on the interaction sequence when being executed by a processor.
Because the storage medium adopts all the technical schemes of all the embodiments, the storage medium has at least all the beneficial effects brought by the technical schemes of the embodiments, and the description is omitted here.
It should be noted that the above-described working procedure is merely illustrative, and does not limit the scope of the present invention, and in practical application, a person skilled in the art may select part or all of them according to actual needs to achieve the purpose of the embodiment, which is not limited herein.
In addition, technical details not described in detail in this embodiment may refer to the software identification method based on the interaction sequence provided in any embodiment of the present invention, which is not described herein.
Furthermore, it should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system 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 system. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. Read Only Memory)/RAM, magnetic disk, optical disk) and including several instructions for causing a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the method according to the embodiments of the present invention.
The foregoing description is only of the preferred embodiments of the present invention, and is not intended to limit the scope of the invention, but rather is intended to cover any equivalents of the structures or equivalent processes disclosed herein or in the alternative, which may be employed directly or indirectly in other related arts.
Claims (10)
1. The software identification method based on the interaction sequence is characterized by comprising the following steps of:
acquiring an initial interaction sequence of a target interaction transaction in an edge X scene;
calculating interaction weights of a plurality of software interaction modes according to the initial interaction sequence;
generating a software interaction sequence library according to the interaction weight of each software interaction mode;
and completing the software identification of the edge X scene according to the software interaction sequence library.
2. The method for identifying software based on an interaction sequence according to claim 1, wherein the calculating the interaction weights of a plurality of software interaction modes according to the initial interaction sequence comprises:
performing software deduplication on the initial interaction sequence to obtain a target interaction sequence;
determining a plurality of software interaction modes, the interaction times of each software interaction mode, the interaction length of each software interaction mode and the sequence length of the target interaction sequence according to the target interaction sequence;
calculating the mode weight of each software interaction mode according to the interaction times of each software interaction mode, the interaction length of each software interaction mode and the sequence length;
and calculating the interaction weight of each software interaction mode according to the mode weight of each software interaction mode and the total number of interaction sequences.
3. The method for identifying software based on interactive sequences according to claim 1, wherein the generating a software interactive sequence library according to the interactive weights of the respective software interactive modes comprises:
acquiring a preset weight threshold;
screening each software interaction mode according to the interaction weight of each software interaction mode and the preset weight threshold value to obtain a target interaction mode;
and generating a software interaction sequence library according to the target interaction mode.
4. The interactive sequence-based software identification method according to claim 1, wherein the software identification of the EdgeX scene is completed according to the software interactive sequence library, comprising:
initializing the length of the software interaction mode to obtain an initial interaction length;
determining candidate interaction modes according to the initial interaction length and the software interaction sequence library;
determining a spliced interaction mode according to the interaction weight of the candidate interaction mode;
and updating the software interaction sequence library according to the splicing interaction mode to obtain an updated interaction sequence library.
5. The method for identifying software based on an interaction sequence according to claim 4, wherein determining a stitched interaction pattern based on the interaction weights of the candidate interaction patterns comprises:
Sorting according to the interaction weights of the candidate interaction modes to obtain a sorting result;
determining a first interaction mode according to the sorting result and a preset screening condition;
determining a second interaction mode according to the initial interaction length and the software interaction sequence library;
splicing according to the first interaction mode, the second interaction mode and a preset splicing mode, and determining a plurality of third interaction modes;
and calculating the interaction weight of each third interaction mode, and determining a spliced interaction mode in the plurality of third interaction modes according to a preset weight threshold and the interaction weight of each third interaction mode.
6. The method for identifying software based on interactive sequences according to claim 4, wherein after updating the software interactive sequence library according to the spliced interactive mode to obtain an updated interactive sequence library, further comprising:
determining a key interaction mode according to the updated interaction sequence library;
calculating the adjacent transition probability of each software node in the edge X scene according to the interaction weight of the key interaction mode;
constructing a transition probability matrix of each software node according to the adjacent transition probability of each software node;
calculating the stay probability of each software node according to the transition probability matrix of each software node;
Node division is carried out according to the stay probability of each software node, and a division result is obtained;
and generating a software community according to the division result.
7. The interactive sequence-based software identification method according to claim 6, wherein constructing a transition probability matrix of each software node according to the adjacent transition probabilities of each software node comprises:
determining the adjacency influence weight of each software node according to the number of the interactive interfaces and the number of the external interfaces of each software node;
calculating the structural influence weight of each software node according to the input degree, the output degree and the dependence uniformity of each software node;
determining target transition probability of each software node according to preset transition weight, adjacent influence weight of each software node, structure influence weight of each software node and adjacent transition probability of each software node;
and constructing a transition probability matrix of each software node according to the target transition probability of each software node.
8. An interactive sequence based software identification device, characterized in that the interactive sequence based software identification device comprises:
the acquisition module is used for acquiring an initial interaction sequence of a target interaction transaction in the edge X scene;
the computing module is used for computing interaction weights of a plurality of software interaction modes according to the initial interaction sequence;
The generating module is used for generating a software interaction sequence library according to the interaction weight of each software interaction mode;
and the completion module is used for completing the software identification of the edge X scene according to the software interaction sequence library.
9. A software identification device based on an interaction sequence, the device comprising: a memory, a processor, and an interaction sequence based software identification program stored on the memory and executable on the processor, the interaction sequence based software identification program configured to implement the interaction sequence based software identification method of any one of claims 1 to 7.
10. A storage medium having stored thereon an interactive sequence based software identification program which when executed by a processor implements the interactive sequence based software identification method of any one of claims 1 to 7.
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