CN113282519B - Case data recommendation method, system and medium for software testing - Google Patents
Case data recommendation method, system and medium for software testing Download PDFInfo
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Abstract
The invention provides a case data recommendation method, system and medium for software testing. The method comprises the following steps: step S1, acquiring a test requirement input by a user; step S2, extracting a knowledge argument sub-graph in the test requirement, wherein the knowledge argument sub-graph represents knowledge argument relations of natural language-based phrases and words contained in the test requirement; step S3, inquiring a knowledge base subgraph corresponding to the knowledge argument subgraph in a knowledge base; and step S4, determining the case data recommended to the user based on the inquired knowledge base subgraph. The method can realize the rapid construction of a large amount of test case data meeting the requirements, and can reduce the work of testers in the test case design stage, thereby saving a large amount of time in the test design process.
Description
Technical Field
The invention relates to the field of data analysis and processing, in particular to a case data recommendation method, system and medium for software testing.
Background
Software Testing (Software Testing) describes a process used to facilitate the identification of the correctness, integrity, security, and quality of Software. In other words, software testing is a process of auditing or comparing between actual output and expected output. The classical definition of software testing is: the process of operating a program under specified conditions to discover program errors, to measure software quality, and to evaluate whether it meets design requirements.
Software testing is generated in connection with the generation of software. The software scale in the early software development process is very small and low in complexity, the software development process is disordered and quite random, the test meaning is narrow, a developer is equal to debugging in the test process, the purpose is to correct known faults in the software, and the developer usually completes the part of work. As software and IT industries enter a large development stage, software tends to be large-scale and high in complexity, and the quality of the software is more and more important. Some basic theories and practical technologies of software testing are beginning to be developed, and people begin to design various processes and management methods for software development, and the software development mode gradually transits from a chaotic and unordered development process to a structured development process, and is characterized by structured analysis and design, structured review, structured program design and structured testing. With the concept of quality being integrated into the software testing definition, the software testing definition is changed, the testing is not simply a process of finding errors, and the testing is used as a main function of software quality assurance and comprises the content of software quality evaluation. In the "software testing complete guide", the test is any activity that aims at evaluating an attribute of a program or system; the test is a measure of the quality of the software. This definition is still cited so far. Software developers and testers are beginning to sit together to explore software engineering and testing problems.
The software test is mainly divided into stages of test requirement analysis, test plan, test design, test execution, test evaluation and the like. In the traditional test, the test work is very complicated, and a large amount of test personnel, software and hardware resources are required to be invested in each test stage to carry out the test work. A large amount of resources and time are consumed in the whole testing process.
Disclosure of Invention
The invention aims to provide a case data recommendation scheme for software testing, which aims to solve the technical problems in the prior art. The scheme is based on the intelligent test case recommendation technology of natural language processing, the work of test design can be simplified, the resource investment is reduced, and the test period is shortened.
The intelligent test case recommending technology based on natural language processing is mainly characterized in that a test case recommending model is generated by natural language processing, intelligent word segmentation, knowledge extraction and the like of typical test case data based on the collected typical test case data. When a tester designs a test case, test case data which can adapt to test requirements and functions as much as possible is recommended for the tester intelligently according to the test requirements and the test functions, so that the tester can quickly construct a large amount of test case data meeting the requirements, the work of the tester in the test case design stage is reduced, and a large amount of time is saved in the test design process.
The invention provides a case data recommendation method for software testing in a first aspect, which comprises the following steps: step S1, acquiring a test requirement input by a user; step S2, extracting a knowledge argument sub-graph in the test requirement, wherein the knowledge argument sub-graph represents knowledge argument relations of natural language-based phrases and words contained in the test requirement; step S3, inquiring a knowledge base subgraph corresponding to the knowledge argument subgraph in a knowledge base; and step S4, determining the case data recommended to the user based on the inquired knowledge base subgraph.
According to the method provided by the first aspect of the present invention, each knowledge base sub-graph in the knowledge base is constructed by: extracting knowledge arguments in the use case data based on a deep neural network; and determining the relation among a plurality of knowledge arguments by using dependency analysis or semantic analysis according to a grammatical structure, and determining an event role corresponding to the knowledge arguments based on the relation, thereby constructing the knowledge base subgraph of the use case data.
According to the method provided by the first aspect of the present invention, in the step S3, querying a knowledge base sub-graph corresponding to the argument of knowledge sub-graph in the knowledge base by determining the position of each argument included in the argument of knowledge sub-graph in the knowledge base.
According to the method provided by the first aspect of the present invention, the step S4 further includes: obtaining a plurality of candidate answers from the knowledge base subgraph; determining a plurality of paths in the knowledge base subgraph through a TRANSE algorithm; extracting feature vectors representing the candidate answer features from the paths; and taking the feature vector as an input of a classifier to acquire the case data recommended to the user.
The second aspect of the present invention provides a case data recommendation system for software testing, the system comprising: an acquisition unit configured to acquire a test requirement input by a user; an extracting unit, configured to extract a knowledge element sub-graph in the test requirement, wherein the knowledge element sub-graph represents knowledge element relations of natural language-based phrases and words contained in the test requirement; the query unit is configured to query a knowledge base subgraph corresponding to the knowledge argument subgraph in a knowledge base; and the determining unit is configured to determine the case data recommended to the user based on the queried knowledge base subgraph.
According to the system provided by the second aspect of the present invention, the knowledge base is included in the use case data recommendation system or is connected to the use case data recommendation system through an external connection; each of the knowledge base sub-graphs in the knowledge base is constructed by: extracting knowledge arguments in the use case data based on a deep neural network; and determining the relation among a plurality of knowledge arguments by using dependency analysis or semantic analysis according to a grammatical structure, and determining an event role corresponding to the knowledge arguments based on the relation, thereby constructing the knowledge base subgraph of the use case data.
According to the system provided by the second aspect of the present invention, the query unit is further configured to query the knowledge base sub-graph corresponding to the argument of knowledge sub-graph in the knowledge base by determining the position of each argument contained in the argument of knowledge sub-graph in the knowledge base.
According to the system provided by the second aspect of the present invention, the determining unit is further configured to: obtaining a plurality of candidate answers from the knowledge base subgraph; determining a plurality of paths in the knowledge base subgraph through a TRANSE algorithm; extracting feature vectors representing the candidate answer features from the paths; and taking the feature vector as an input of a classifier to acquire the case data recommended to the user.
A third aspect of the present invention provides a non-transitory computer readable medium storing instructions which, when executed by a processor, perform the steps of a use case data recommendation method for software testing according to the first aspect of the present invention.
By adopting the technical scheme, the invention has the following beneficial effects: the method can realize the rapid construction of a large amount of test case data meeting the requirements, and can reduce the work of testers in the test case design stage, thereby saving a large amount of time in the test design process.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the embodiments or the description in the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a schematic diagram illustrating a flow of a case data recommendation method for software testing according to an embodiment of the present invention;
FIG. 2 is a block diagram of a use case data recommendation system for software testing according to an embodiment of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the accompanying drawings, and it should be understood that the described embodiments are some, but not all embodiments of the present invention. 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 invention.
The invention provides a case data recommendation method for software testing, which can realize the rapid construction of a large amount of test case data meeting requirements, and can reduce the work of testers in the test case design stage, thereby saving a large amount of time in the test design process.
Fig. 1 is a schematic diagram of a flow of a case data recommendation method for software testing according to an embodiment of the present invention. As shown in fig. 1, the process 100 begins with step S1, where the test requirement input by the user is obtained. In some embodiments, in the step S1, the test requirement may be obtained based on a user input, or may be obtained by other methods, including but not limited to: through configuration of the test platform, or through external data import, etc.
Next, in step S2, a knowledgerelated sub-graph in the test requirement is extracted, wherein the knowledgerelated sub-graph represents knowledgerelated relations of natural language-based phrases and words contained in the test requirement.
In some embodiments, when a tester performs test case design, the information description of the current test requirement is subjected to learning of distributed expression by a deep learning method, phrases and words based on natural language contained in the requirement description are mapped to argument or argument relation of a knowledge base, and then the requirement description is converted into a requirement argument subgraph which can be understood by the knowledge base.
Subsequently, in step S3, the knowledge base sub-graph corresponding to the knowledge argument sub-graph is queried in the knowledge base.
In some embodiments, the test case collection in the knowledge base refers to the unified collection management of test case data generated in the full life cycle test process of application software in the system. And classifying, summarizing, warehousing and storing according to different test requirements, functions, test item information and the like to realize test case data accumulation.
In some embodiments, each of the knowledge-base subgraphs in the knowledge-base is constructed by: extracting knowledge arguments in the use case data based on a deep neural network; and determining the relation among a plurality of knowledge arguments by using dependency analysis or semantic analysis according to a grammatical structure, and determining an event role corresponding to the knowledge arguments based on the relation, thereby constructing the knowledge base subgraph of the use case data. For a test case to be stored in a stock, extracting knowledge arguments in test case data by constructing a deep neural network, determining the relation between different arguments by utilizing dependency analysis or semantic analysis based on a syntactic structure, simultaneously acquiring sentences correspondingly described by events according to trigger words of the events, identifying roles of the events corresponding to the arguments in the sentences described by the events, and constructing a complete knowledge graph, namely a knowledge base subgraph of the test case.
In some embodiments, a knowledge base sub-graph corresponding to the knowledge argument sub-graph in the knowledge base is queried by determining the location in the knowledge base of each argument contained in the knowledge argument sub-graph. That is, the position of the argument of knowledge in the argument of knowledge subgraph is inquired in the knowledge base to obtain the knowledge base subgraph with the argument at the position as the center.
Finally, in step S4, based on the queried knowledge base sub-graph, the use case data recommended to the user is determined. Specifically, a plurality of candidate answers are obtained from the knowledge base subgraph; determining a plurality of paths in the knowledge base subgraph through a TRANSE algorithm; extracting feature vectors representing the candidate answer features from the paths; and taking the feature vector as an input of a classifier to acquire the case data recommended to the user.
In some embodiments, the relation of different path deletions in the knowledge base subgraph is complemented through a TRANSE algorithm, then different paths in the knowledge base subgraph are solved, information extraction is carried out according to rules or templates, feature vectors representing the features of the problems and the candidate answers are obtained, a classifier is established, the candidate answers are screened through inputting the feature vectors, therefore, test case information possibly suitable for the current test requirements is screened out, and the test case information is recommended to a tester to complete test case design.
To sum up, the case data recommendation method for software testing in the first aspect of the present invention accumulates a large amount of test case data for natural language processing and learning by collecting and storing typical test case data designed by a tester according to test requirements during a test process. And carrying out deep processing according to the collected typical test case data to generate an intelligent case recommendation model. When the test is carried out, the test case data used by the tester is recommended through the intelligent recommendation model according to the test requirements and functions. Meanwhile, the accuracy and pertinence of intelligent recommendation of test cases are improved by learning a large amount of test case data.
A second aspect of the present invention provides a case data recommendation system for software testing, and fig. 2 is a structural diagram of a case data recommendation system for software testing according to an embodiment of the present invention. As shown in fig. 2, the system includes: an acquisition unit configured to acquire a test requirement input by a user; an extracting unit, configured to extract a knowledge element sub-graph in the test requirement, wherein the knowledge element sub-graph represents knowledge element relations of natural language-based phrases and words contained in the test requirement; the query unit is configured to query a knowledge base subgraph corresponding to the knowledge argument subgraph in a knowledge base; and the determining unit is configured to determine the case data recommended to the user based on the queried knowledge base subgraph.
In some embodiments, the knowledge base is contained in the use case data recommendation system or is connected to the use case data recommendation system through an external connection; each of the knowledge base sub-graphs in the knowledge base is constructed by: extracting knowledge arguments in the use case data based on a deep neural network; and determining the relation among a plurality of knowledge arguments by using dependency analysis or semantic analysis according to a grammatical structure, and determining an event role corresponding to the knowledge arguments based on the relation, thereby constructing the knowledge base subgraph of the use case data.
In some embodiments, the querying unit is further configured to query a knowledge base sub-graph corresponding to the argument of knowledge sub-graph in the knowledge base by determining the position of each argument contained in the argument of knowledge sub-graph in the knowledge base. In some embodiments, the determining unit is further configured to: obtaining a plurality of candidate answers from the knowledge base subgraph; determining a plurality of paths in the knowledge base subgraph through a TRANSE algorithm; extracting feature vectors representing the candidate answer features from the paths; and taking the feature vector as an input of a classifier to acquire the case data recommended to the user.
A third aspect of the present invention provides a non-transitory computer readable medium storing instructions which, when executed by a processor, perform the steps of a use case data recommendation method for software testing according to the first aspect of the present invention.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (5)
1. A case data recommendation method for software testing is characterized by comprising the following steps:
step S1, acquiring a test requirement input by a user;
step S2, extracting a knowledge argument sub-graph in the test requirement, wherein the knowledge argument sub-graph represents knowledge argument relations of natural language-based phrases and words contained in the test requirement;
step S3, inquiring a knowledge base subgraph corresponding to the knowledge argument subgraph in a knowledge base; and
step S4, determining the case data recommended to the user based on the inquired knowledge base subgraph;
wherein each of the knowledge base sub-graphs in the knowledge base is constructed by:
extracting knowledge arguments in the use case data based on a deep neural network;
determining relationships between a plurality of said knowledgeable arguments using dependency analysis or semantic parsing based on a syntactic structure, an
Determining an event role corresponding to the argument of knowledge based on the relationship, thereby constructing the knowledge base subgraph of the use case data;
wherein the step S4 further includes:
obtaining a plurality of candidate answers from the knowledge base subgraph;
determining a plurality of paths in the knowledge base subgraph through a TRANSE algorithm;
extracting feature vectors representing the candidate answer features from the paths; and
and taking the feature vector as an input of a classifier to acquire the use case data recommended to the user.
2. The use case data recommendation method for software testing according to claim 1, wherein in said step S3, querying a knowledge base sub-graph corresponding to said argument of knowledge sub-graph in said knowledge base by determining the position of each argument contained in said argument of knowledge sub-graph in said knowledge base.
3. A use case data recommendation system for software testing, the system comprising:
an acquisition unit configured to acquire a test requirement input by a user;
an extracting unit, configured to extract a knowledge element sub-graph in the test requirement, wherein the knowledge element sub-graph represents knowledge element relations of natural language-based phrases and words contained in the test requirement;
the query unit is configured to query a knowledge base subgraph corresponding to the knowledge argument subgraph in a knowledge base; and
a determining unit configured to determine the use case data recommended to the user based on the queried knowledge base sub-graph;
wherein the knowledge base is contained in the use case data recommendation system or is connected to the use case data recommendation system through an external connection, and each knowledge base sub-graph in the knowledge base is constructed in the following way:
extracting knowledge arguments in the use case data based on a deep neural network;
determining relationships between a plurality of said knowledgeable arguments using dependency analysis or semantic parsing based on a syntactic structure, an
Determining an event role corresponding to the argument of knowledge based on the relationship, thereby constructing the knowledge base subgraph of the use case data;
the determining unit is further configured to:
obtaining a plurality of candidate answers from the knowledge base subgraph;
determining a plurality of paths in the knowledge base subgraph through a TRANSE algorithm;
extracting feature vectors representing the candidate answer features from the paths; and
and taking the feature vector as an input of a classifier to acquire the use case data recommended to the user.
4. The use case data recommendation system for software testing according to claim 3, wherein said query unit is further configured to query a knowledge base sub-graph corresponding to said argument of knowledge sub-graph in said knowledge base by determining a location of each argument contained in said argument of knowledge sub-graph in said knowledge base.
5. A non-transitory computer readable medium storing instructions which, when executed by a processor, perform the steps in the use case data recommendation method for software testing of any of claims 1-2.
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