Information system software-oriented test sufficiency evaluation method and system

Abstract

The application provides a kind of information system software-oriented test sufficiency evaluation method and system, comprising: identifying evaluation elements for test sufficiency evaluation;Based on the system feature state in evaluation element, information system software state diagram is constructed;Test sequence is generated by traversing information system software state diagram, and test sequence set is constructed based on test sequence;Test sufficiency evaluation index is calculated;Test sufficiency fuzzy comprehensive evaluation parameters are set;According to test sufficiency evaluation index, the membership vector of test sufficiency basic evaluation index is calculated;Test sufficiency fuzzy comprehensive evaluation result is calculated.The test sufficiency evaluation method based on system feature state and fuzzy comprehensive evaluation method can meet the characteristics of large scale, multiple users, various functions and high complexity of information system software, and can comprehensively quantify the sufficiency and completeness of information system software test from multiple angles.

Description

Technical Field

[0001] This invention relates to the field of software testing technology, and more specifically, to a method and system for evaluating the adequacy of testing information system software. Background Technology

[0002] With the development of advanced technologies such as cloud computing, big data, and artificial intelligence, and the rapid and ever-changing application demands, current information system software is evolving towards ubiquitous networks, pervasive computing, artificial intelligence, and system resilience technologies. It exhibits characteristics of increasing complexity, service orientation, networking, and intelligence, featuring massive scale, diverse functions, complex structures, hierarchical system responsibilities, distributed data processing, and frequent information interaction. The overall functionality and performance of information system software are more influenced by the system architecture and the interactions of its components. Typically, when conducting information system software testing, due to the numerous system components, complex and flexible information interactions, it is practically impossible to exhaustively enumerate all possible operating paths to meet sufficiency requirements. Therefore, given the complexity of information system software, how to effectively conduct sufficiency evaluation of information system software testing activities to ensure the sufficiency and completeness of testing and verification has become a pressing problem for software vendors.

[0003] Goodenough and Gerhart introduced the concept of software test adequacy in 1975 when studying whether software testing can guarantee the correctness of software. Generally, software test adequacy is a program-oriented concept, reflecting the degree to which software tests are sufficient. The NSF Safety and Software Engineering Research Center at Systems Ontario, USA, uses Markov chain usage models and sampling to reveal important test paths not covered by heuristic testing, thereby improving test coverage and adequacy. Compared to heuristic sampling, combining coverage and random sampling improves reliability estimation at both the arc (usage event) and path (system) levels. The University of Technology Sydney and the University of Malaya jointly proposed the Test Defect Coverage Analysis Model (TDCAM) for test adequacy assessment, which demonstrates its benefits in helping practitioners make informed test adequacy-related decisions. Scholars from many universities and research institutions in China have also put forward their views on improving software test adequacy, including test adequacy criteria and the use of fault-based analysis techniques to improve test adequacy. Zhu Hong and Jin Lingzi analyzed the advantages and disadvantages of using axioms to measure various sufficiency criteria, enabling software testing to be based on objective measurement of test sufficiency.

[0004] Currently, most research on information system software testing and verification methods, both domestically and internationally, focuses on reliability evaluation, test process management, and comprehensive performance assessment, lacking research specifically on the adequacy of information system software testing. Traditional testing adequacy studies primarily focus on code, data flow, and control flow, which are insufficient to meet the adequacy evaluation requirements of large-scale, rapidly iterating, and highly complex software like information systems. When evaluating the adequacy of information system software testing, evaluations are often conducted from a single perspective, resulting in overly simplistic and limited evaluation results. Furthermore, when using fuzzy comprehensive evaluation methods to calculate the membership degrees of evaluation indicators, traditional membership function calculation methods suffer from overfitting, lack of a unified computational space, and failure to normalize the calculation results.

[0005] Patent application number 201811270209.4 discloses a software testing adequacy measurement method based on system characteristic states, relating to the field of software testing technology. This invention can quantitatively assess system testing adequacy and guide how to improve it. As long as the communication protocol format between systems is obtained and communication data can be collected, this method can be used to guide system-level testing. The method is insensitive to the complexity of the system and can support testing of large and complex systems. It can intuitively indicate which key software characteristic states are not covered. Analogous to statement coverage, branch coverage, and path coverage in white-box testing, this method can be defined as multi-level test coverage statistics such as characteristic state coverage and characteristic state combination coverage, adapting to the termination conditions of system testing with different security and reliability requirements.

[0006] The software testing sufficiency metrics in this invention are mainly system feature state coverage and system feature state combination coverage; the software testing sufficiency metrics in this application are mainly system feature state coverage, system feature state transition edge coverage, and system feature state space variable coverage.

[0007] The invention mainly calculates the cumulative coverage rate (KSAC) of key feature states in a weighted manner for the overall software testing adequacy evaluation process, and the evaluation result is a specific quantitative value. This application uses a fuzzy comprehensive evaluation method to evaluate the overall software testing adequacy, and the evaluation result is a membership vector based on the evaluation set, which is a probability distribution for different evaluation terms.

[0008] Patent document with application number 201610694490.9 discloses a multi-dimensional measurement method and apparatus for test adequacy. The method includes: establishing a test adequacy measurement model using a computer; calculating various metrics of the software under test based on the test adequacy measurement model, wherein the metrics include at least one or more of the following: code coverage distribution of software modules, requirement process coverage distribution, complexity-weighted code coverage distribution, complexity-weighted test case number distribution, test case update ratio distribution at a certain stage, and distribution of the number of new failures corresponding to a certain stage.

[0009] The software testing adequacy metrics in the invention include three dimensions: code coverage, module structure weighting, and test evolution. However, this application designs testing adequacy metrics from the perspective of the system characteristic states of information system software, mainly including system characteristic state coverage, system characteristic state transition edge coverage, and system characteristic state space variable coverage.

[0010] This invention provides multi-dimensional software test adequacy metrics and their calculation methods, but lacks a test adequacy evaluation for the entire system software. In contrast, this application uses fuzzy comprehensive evaluation methods based on test adequacy evaluation results from dimensions such as system characteristic states, system characteristic state transition edges, and system characteristic state space variables to obtain test adequacy evaluation results for the entire software system.

[0011] Patent document CN101710304A (application number: CN200910241609.7) discloses a method and system for evaluating the implementation quality of a software process, comprising: 1) a user selecting a software process evaluation model or standard from an evaluation standard library using an evaluation standard selection module; 2) an indicator system establishment module establishing a measurement indicator system using a goal-problem-measurement method or a practical software measurement method; 3) an indicator measurement data acquisition module collecting data on the software process to be evaluated according to the established measurement indicator system; simultaneously, an indicator weight determination module determining the weight of each measurement indicator according to the established measurement indicator system; 4) a comprehensive evaluation calculation module standardizing and unifying the collected data numerically; and 5) a comprehensive evaluation calculation module evaluating the processed data using a fuzzy comprehensive evaluation method and outputting the evaluation results. However, this invention is based on the user selecting a software process evaluation model or standard, while this application automatically identifies the software modules and functional components of an analysis information system. Summary of the Invention

[0012] In view of the deficiencies in the prior art, the purpose of this invention is to provide a method and system for evaluating the adequacy of testing information system software.

[0013] A test adequacy evaluation method for information system software provided by the present invention includes:

[0014] Step S1: Identify the evaluation elements used for testing adequacy assessment;

[0015] Step S2: Construct an information system software state diagram based on the system characteristic states in the evaluation elements;

[0016] Step S3: Traverse the information system software state diagram to generate test sequences, and construct a test sequence set based on the test sequences;

[0017] Step S4: Calculate the test adequacy evaluation index;

[0018] Step S5: Set the parameters for fuzzy comprehensive evaluation of test adequacy;

[0019] Step S6: Calculate the membership vector of the basic evaluation index of test adequacy based on the test adequacy evaluation index;

[0020] Step S7: Calculate the fuzzy comprehensive evaluation results of test adequacy.

[0021] Preferably, in step S1:

[0022] The evaluation elements used for adequacy assessment are identified, including the system characteristic states, system characteristic state transition edges, and system characteristic state space variables of the information system software. The specific steps are as follows:

[0023] Step S1.1: By analyzing the software modules and functional components of the information system, identify the system characteristic state set CS={s1,s2,…,sn} of the information system software. The system characteristic state is determined by the attributes or values ​​of the software function-related variables. It is the functional state of the information system software in the variable space, including normal state and abnormal state.

[0024] Step S1.2: By analyzing the migration relationships between the software functions of the information system, and combining the defined system characteristic state set CS, the system characteristic state migration edge set CE = {e1,e2,…,en} is identified. The system characteristic state migration edge set CE is a total order relation on the system characteristic state set CS, representing the temporal order of the system characteristic states.

[0025] Step S1.3: By analyzing the variables in the information system software that are periodically triggered or event-driven, the system characteristic state space variable set CP = {p1, p2, ..., pn} is identified. The system characteristic state space variable set CP is a set of variables that determine the system characteristic state and cause changes in the system characteristic state.

[0026] Preferably, in step S2:

[0027] Based on the system's characteristic states, a software state diagram of the information system is constructed. Statistical metrics include the total number of system characteristic states, the system characteristic state transition edges, and the system characteristic state space variables. The specific steps are as follows:

[0028] Step S2.1: Use a state diagram to formally express the system characteristic states, transition edges, and spatial variables of the information system software. The system characteristic states are the nodes in the state diagram, the system characteristic state transition edges are the directed edges in the state diagram, and the system characteristic state spatial variables are the transition conditions between nodes in the state diagram.

[0029] Step S2.2: Perform data statistics on all nodes, directed edges, and transition conditions in the state graph to obtain the total number of system characteristic states TS, the total number of system characteristic state transition edges TE, and the total number of system characteristic state space variables TP.

[0030] Preferably, in step S3:

[0031] The Depth-First Search (DFS) algorithm is used to traverse the state graph to generate a set of test sequences. A test sequence set is constructed based on the test sequences of a preset size. Statistical metrics include the number of activations of system characteristic states, the number of activations of system characteristic state transition edges, and the number of activations of system characteristic state space variables. The specific steps are as follows:

[0032] Step S3.1: Use the DFS algorithm to traverse all nodes, directed edges and transition conditions in the state graph to form a test sequence set CT = {t1, t2, ..., tn} of a preset size;

[0033] Step S3.2: Perform data statistics on the nodes, directed edges, and transition conditions activated by the CT traversal of the test sequence set to obtain the number of system characteristic state activations AS, the number of system characteristic state transition edge activations AE, and the number of system characteristic state space variable activations AP.

[0034] Preferably, in step S4:

[0035] The basic evaluation indicators for test adequacy are calculated, including the evaluation indicators for the adequacy of system characteristic state tests, the evaluation indicators for the adequacy of system characteristic state transition edge tests, and the evaluation indicators for the adequacy of system characteristic state space variable tests.

[0036] The calculation formula for the sufficiency evaluation index of system characteristic state testing is as follows:

[0037]

[0038] The calculation formula for the sufficiency evaluation index of the system characteristic state transition edge test is as follows:

[0039]

[0040] The calculation formula for the sufficiency evaluation index of the system characteristic state-space variables is as follows:

[0041]

[0042] Preferably, in step S5:

[0043] To set up fuzzy comprehensive evaluation parameters for test adequacy, the fuzzy comprehensive evaluation method is used to evaluate the test adequacy of information system software. First, evaluation parameters are set, including an influencing factor set U, an evaluation set V, and an influencing weight set W, where: the influencing factor set U = {system characteristic state coverage, system characteristic state transition edge coverage, system characteristic state space variable coverage}; the evaluation set V = {insufficient, basically sufficient, sufficient, very sufficient}; and the influencing weight set W = {w1, w2, w3}, where the values ​​of w1, w2, and w3 are configured according to the test adequacy evaluation requirements and actual conditions of the information system software.

[0044] Preferably, in step S6:

[0045] The membership vector calculation for the basic evaluation index of test adequacy adopts a K-order parabolic membership function based on a unified spatial threshold distance to determine each factor in the influencing factor set U. The resulting test adequacy evaluation index includes system characteristic states, system characteristic state transition edges, and system characteristic state spatial variables. The processing procedure for the membership degree of all evaluation terms in the evaluation set V is as follows:

[0046] Step S6.1: Perform a unified benchmark computational space mapping transformation on the input basic metric values ​​and membership interval thresholds based on the average linear interpolation technique to form the transformed basic metric values ​​x and membership interval threshold set T;

[0047] Step S6.2: Assuming the evaluation set V has n elements, obtain all interval threshold pairs (UTi DTi), i∈n;

[0048] Step S6.3: For each evaluation element v in the evaluation set V i Calculate the spatial distance Dist between the basic metric value x and the upper threshold UTi and the lower threshold DTi when the x reaches the corresponding interval threshold. i Dist i The formula for calculating it is ((x-UTi)). 2 +(x-DTi) 2 ) 2 ;

[0049] Step S6.4: Use spatial distance Dist iThe reciprocal of the value is used as the result of calculating the membership function of the Kth order parabola to obtain the basic metric value x for the evaluation element v. i membership value s i ;

[0050] Step S6.5: Repeat steps S6.3 to S6.4 to obtain the membership values ​​of the basic metric value x to all evaluation set elements, forming a vector (s1 s2 … s n );

[0051] Step S6.6: For vectors (s1 s2 … s n Normalization is performed, and calculations are performed. Obtain the normalized membership vectors (ns1 ns2 … ns) of the basic metric evaluation set. n ).

[0052] Preferably, in step S7:

[0053] The fuzzy comprehensive evaluation results for test adequacy are calculated. After calculating the evaluation set membership vectors for each basic metric using a K-order parabolic membership function based on a unified spatial threshold distance, the fuzzy evaluation results r for each single factor are obtained. i =(a i1 a i2 … a in For i∈1…n, these single-factor fuzzy evaluation results are combined to construct a single-factor fuzzy evaluation matrix. Combined with the pre-set weight set of influencing factors W = (w1 w2 … w m ), through calculation The results of the adequacy evaluation of the entire information system software were obtained.

[0054] A test adequacy evaluation system for information system software, provided by the present invention, includes:

[0055] Module M1: Identifies evaluation elements used for testing adequacy assessment;

[0056] Module M2: Constructs a software state diagram of the information system based on the system characteristic states in the evaluation elements;

[0057] Module M3: Traverses the information system software state diagram to generate test sequences, and constructs a test sequence set based on the test sequences;

[0058] Module M4: Calculates the adequacy evaluation index for testing;

[0059] Module M5: Set parameters for fuzzy comprehensive evaluation of test adequacy;

[0060] Module M6: Calculates the membership vectors of the basic evaluation indicators for test adequacy based on the test adequacy evaluation indicators;

[0061] Module M7: Calculate the fuzzy comprehensive evaluation results of test adequacy.

[0062] Preferably, in module M1:

[0063] The evaluation elements used for adequacy assessment are identified, including the system characteristic states, system characteristic state transition edges, and system characteristic state space variables of the information system software. The specific steps are as follows:

[0064] Module M1.1: By analyzing the software modules and functional components of the information system, the system characteristic state set CS={s1,s2,…,sn} of the information system software is identified. The system characteristic state is determined by the attributes or values ​​of the software function-related variables. It is the functional state of the information system software in the variable space, including normal state and abnormal state.

[0065] Module M1.2: By analyzing the migration relationships between software functions of the information system, and combining the defined system characteristic state set CS, the system characteristic state migration edge set CE = {e1,e2,…,en} is identified. The system characteristic state migration edge set CE is a total order relation on the system characteristic state set CS, representing the temporal order of system characteristic states.

[0066] Module M1.3: By analyzing the variables that cause changes in the characteristic state of the system through periodic triggering or event stimulation in the information system software, the system characteristic state space variable set CP = {p1, p2, ..., pn} is identified. The system characteristic state space variable set CP is a set of variables that determine the system characteristic state and cause changes in the system characteristic state.

[0067] In module M2:

[0068] Based on the system's characteristic states, a software state diagram of the information system is constructed. Statistical metrics include the total number of system characteristic states, the system characteristic state transition edges, and the system characteristic state space variables. The specific steps are as follows:

[0069] Module M2.1: It uses a state diagram to formally express the system characteristic states, transition edges, and spatial variables of information system software. The system characteristic states are the nodes in the state diagram, the system characteristic state transition edges are the directed edges in the state diagram, and the system characteristic state spatial variables are the transition conditions between nodes in the state diagram.

[0070] Module M2.2: Performs data statistics on all nodes, directed edges, and transition conditions in the state graph to obtain the total number of system characteristic states TS, the total number of system characteristic state transition edges TE, and the total number of system characteristic state space variables TP.

[0071] In module M3:

[0072] The Depth-First Search (DFS) algorithm is used to traverse the state graph to generate a set of test sequences. A test sequence set is constructed based on the test sequences of a preset size. Statistical metrics include the number of activations of system characteristic states, the number of activations of system characteristic state transition edges, and the number of activations of system characteristic state space variables. The specific steps are as follows:

[0073] Module M3.1: The DFS algorithm is used to traverse all nodes, directed edges and transition conditions in the state graph to form a test sequence set CT = {t1, t2, ..., tn} of a preset size;

[0074] Module M3.2: Performs data statistics on the nodes, directed edges, and transition conditions activated by traversing the test sequence set CT to obtain the number of system characteristic state activations AS, the number of system characteristic state transition edge activations AE, and the number of system characteristic state space variable activations AP;

[0075] In module M4:

[0076] The basic evaluation indicators for test adequacy are calculated, including the evaluation indicators for the adequacy of system characteristic state tests, the evaluation indicators for the adequacy of system characteristic state transition edge tests, and the evaluation indicators for the adequacy of system characteristic state space variable tests.

[0077] The calculation formula for the sufficiency evaluation index of system characteristic state testing is as follows:

[0078]

[0079] The calculation formula for the sufficiency evaluation index of the system characteristic state transition edge test is as follows:

[0080]

[0081] The calculation formula for the sufficiency evaluation index of the system characteristic state-space variables is as follows:

[0082]

[0083] In module M5:

[0084] To evaluate the adequacy of testing for information system software using a fuzzy comprehensive evaluation method, the following parameters are set: First, the evaluation parameters are defined, including an influencing factor set U, an evaluation set V, and an influencing weight set W. Specifically: the influencing factor set U = {system characteristic state coverage, system characteristic state transition edge coverage, system characteristic state spatial variable coverage}; the evaluation set V = {insufficient, basically sufficient, sufficient, very sufficient}; and the influencing weight set W = {w1, w2, w3}, where the values ​​of w1, w2, and w3 are configured according to the requirements of the information system software's testing adequacy evaluation and the actual situation.

[0085] In module M6:

[0086] The membership vector calculation for the basic evaluation index of test adequacy adopts a K-order parabolic membership function based on a unified spatial threshold distance to determine each factor in the influencing factor set U. The resulting test adequacy evaluation index includes system characteristic states, system characteristic state transition edges, and system characteristic state spatial variables. The processing procedure for the membership degree of all evaluation terms in the evaluation set V is as follows:

[0087] Module M6.1: Performs a unified benchmark computational space mapping transformation on the input basic metric values ​​and membership interval thresholds based on average linear interpolation techniques to form the transformed basic metric values ​​x and membership interval threshold set T;

[0088] Module M6.2: Assuming the evaluation set V has n elements, obtain all interval threshold pairs (UTi DTi), i∈n;

[0089] Module M6.3: For each evaluation element v in the evaluation set V i Calculate the spatial distance Dist between the basic metric value x and the upper threshold UTi and the lower threshold DTi when the x reaches the corresponding interval threshold. i Dist i The formula for calculating it is ((x-UTi)). 2 +(x-DTi) 2 ) 2 ;

[0090] Module M6.4: Using spatial distance Dist i The reciprocal of the value is used as the result of calculating the membership function of the Kth order parabola to obtain the basic metric value x for the evaluation element v. i membership value s i ;

[0091] Module M6.5: Repeat modules M6.3 to M6.4 to obtain the membership values ​​of the basic metric value x to all elements of the evaluation set, forming a vector (s1 s2 … s n );

[0092] Module M6.6: For vectors (s1 s2 … s n Normalization is performed, and calculations are performed. Obtain the normalized membership vectors (ns1 ns2 … ns) of the basic metric evaluation set. n );

[0093] In module M7:

[0094] The fuzzy comprehensive evaluation results for test adequacy are calculated. After calculating the evaluation set membership vectors for each basic metric using a K-order parabolic membership function based on a unified spatial threshold distance, the fuzzy evaluation results r for each single factor are obtained. i =(a i1 a i2 … a in For i∈1…n, these single-factor fuzzy evaluation results are combined to construct a single-factor fuzzy evaluation matrix. Combined with the pre-set weight set of influencing factors W = (w1 w2 … w m ), through calculation The results of the adequacy evaluation of the entire information system software were obtained.

[0095] Compared with the prior art, the present invention has the following beneficial effects:

[0096] 1. The present invention provides a test sufficiency evaluation method based on system characteristic states and fuzzy comprehensive evaluation method, which can meet the characteristics of information system software such as large scale, many users, diverse functions and high complexity, and comprehensively and quantitatively characterize the sufficiency and completeness of information system software testing from multiple perspectives;

[0097] 2. In this invention, the test adequacy evaluation results can be fed back to the information system software state diagram. By analyzing the test sequences that affect test adequacy, errors such as missing states, conflicting transition conditions, or illegal probability information in the test sequences are checked. From the perspective of graph theory, problems such as islands, cycles, and conflicts between system characteristic states, transition edges, and spatial variables in the information system software state diagram are identified, thereby further exploring and developing information system software requirements.

[0098] 3. In this invention, the test adequacy evaluation results can guide the development of test sequences and the design of test cases based on the information system software state diagram by setting thresholds, taking into account both test efficiency and test effectiveness, and achieving a balance between test scale and test adequacy. Attached Figure Description

[0099] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0100] Figure 1 Flowchart for testing adequacy evaluation methods. Detailed Implementation

[0101] The present invention will now be described in detail with reference to specific embodiments. These embodiments will help those skilled in the art to further understand the present invention, but do not limit the invention in any way. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all fall within the protection scope of the present invention.

[0102] Example 1:

[0103] In view of the existing problems and current situation, the technical problems to be solved by the present invention are reflected in the following points:

[0104] 1) To address the problem of the lack of a scientific and effective evaluation index system for the adequacy of testing, given the characteristics of information system software such as large scale, rapid iteration, and high complexity;

[0105] 2) Address the issue that existing software test adequacy evaluations often assess test adequacy from different, localized perspectives, lacking a holistic approach to evaluating test adequacy;

[0106] 3) Address the problems in the fuzzy comprehensive evaluation method, such as overfitting of the general membership function, lack of a unified computational space, and failure to normalize the computational results.

[0107] According to the present invention, a test adequacy evaluation method for information system software is provided, such as... Figure 1 As shown, it includes:

[0108] Step S1: Identify the evaluation elements used for testing adequacy assessment;

[0109] Specifically, in step S1:

[0110] The evaluation elements used for adequacy assessment are identified, including the system characteristic states, system characteristic state transition edges, and system characteristic state space variables of the information system software. The specific steps are as follows:

[0111] Step S1.1: By analyzing the software modules and functional components of the information system, identify the system characteristic state set CS={s1,s2,…,sn} of the information system software. The system characteristic state is determined by the attributes or values ​​of the software function-related variables. It is the functional state of the information system software in the variable space, including normal state and abnormal state.

[0112] Step S1.2: By analyzing the migration relationships between the software functions of the information system, and combining the defined system characteristic state set CS, the system characteristic state migration edge set CE = {e1,e2,…,en} is identified. The system characteristic state migration edge set CE is a total order relation on the system characteristic state set CS, representing the temporal order of the system characteristic states.

[0113] Step S1.3: By analyzing the variables in the information system software that are periodically triggered or event-driven, the system characteristic state space variable set CP = {p1, p2, ..., pn} is identified. The system characteristic state space variable set CP is a set of variables that determine the system characteristic state and cause changes in the system characteristic state.

[0114] Step S2: Construct an information system software state diagram based on the system characteristic states in the evaluation elements;

[0115] Specifically, in step S2:

[0116] Based on the system's characteristic states, a software state diagram of the information system is constructed. Statistical metrics include the total number of system characteristic states, the system characteristic state transition edges, and the system characteristic state space variables. The specific steps are as follows:

[0117] Step S2.1: Use a state diagram to formally express the system characteristic states, transition edges, and spatial variables of the information system software. The system characteristic states are the nodes in the state diagram, the system characteristic state transition edges are the directed edges in the state diagram, and the system characteristic state spatial variables are the transition conditions between nodes in the state diagram.

[0118] Step S2.2: Perform data statistics on all nodes, directed edges, and transition conditions in the state graph to obtain the total number of system characteristic states TS, the total number of system characteristic state transition edges TE, and the total number of system characteristic state space variables TP.

[0119] Step S3: Traverse the information system software state diagram to generate test sequences, and construct a test sequence set based on the test sequences;

[0120] Specifically, in step S3:

[0121] The Depth-First Search (DFS) algorithm is used to traverse the state graph to generate a set of test sequences. A test sequence set is constructed based on the test sequences of a preset size. Statistical metrics include the number of activations of system characteristic states, the number of activations of system characteristic state transition edges, and the number of activations of system characteristic state space variables. The specific steps are as follows:

[0122] Step S3.1: Use the DFS algorithm to traverse all nodes, directed edges and transition conditions in the state graph to form a test sequence set CT = {t1, t2, ..., tn} of a preset size;

[0123] Step S3.2: Perform data statistics on the nodes, directed edges, and transition conditions activated by the CT traversal of the test sequence set to obtain the number of system characteristic state activations AS, the number of system characteristic state transition edge activations AE, and the number of system characteristic state space variable activations AP.

[0124] Step S4: Calculate the test adequacy evaluation index;

[0125] Specifically, in step S4:

[0126] The basic evaluation indicators for test adequacy are calculated, including the evaluation indicators for the adequacy of system characteristic state tests, the evaluation indicators for the adequacy of system characteristic state transition edge tests, and the evaluation indicators for the adequacy of system characteristic state space variable tests.

[0127] The calculation formula for the sufficiency evaluation index of system characteristic state testing is as follows:

[0128]

[0129] The calculation formula for the sufficiency evaluation index of the system characteristic state transition edge test is as follows:

[0130]

[0131] The calculation formula for the sufficiency evaluation index of the system characteristic state-space variables is as follows:

[0132]

[0133] Step S5: Set the parameters for fuzzy comprehensive evaluation of test adequacy;

[0134] Specifically, in step S5:

[0135] To set up fuzzy comprehensive evaluation parameters for test adequacy, the fuzzy comprehensive evaluation method is used to evaluate the test adequacy of information system software. First, evaluation parameters are set, including an influencing factor set U, an evaluation set V, and an influencing weight set W, where: the influencing factor set U = {system characteristic state coverage, system characteristic state transition edge coverage, system characteristic state space variable coverage}; the evaluation set V = {insufficient, basically sufficient, sufficient, very sufficient}; and the influencing weight set W = {w1, w2, w3}, where the values ​​of w1, w2, and w3 are configured according to the test adequacy evaluation requirements and actual conditions of the information system software.

[0136] Step S6: Calculate the membership vector of the basic evaluation index of test adequacy based on the test adequacy evaluation index;

[0137] Specifically, in step S6:

[0138] The membership vector calculation for the basic evaluation index of test adequacy adopts a K-order parabolic membership function based on a unified spatial threshold distance to determine each factor in the influencing factor set U. The resulting test adequacy evaluation index includes system characteristic states, system characteristic state transition edges, and system characteristic state spatial variables. The processing procedure for the membership degree of all evaluation terms in the evaluation set V is as follows:

[0139] Step S6.1: Perform a unified benchmark computational space mapping transformation on the input basic metric values ​​and membership interval thresholds based on the average linear interpolation technique to form the transformed basic metric values ​​x and membership interval threshold set T;

[0140] Step S6.2: Assuming the evaluation set V has n elements, obtain all interval threshold pairs (UTi DTi), i∈n;

[0141] Step S6.3: For each evaluation element v in the evaluation set V i Calculate the spatial distance Dist between the basic metric value x and the upper threshold UTi and the lower threshold DTi when the x reaches the corresponding interval threshold. i Dist i The formula for calculating it is ((x-UTi)). 2 +(x-DTi) 2 ) 2 ;

[0142] Step S6.4: Use spatial distance Dist i The reciprocal of the value is used as the result of calculating the membership function of the Kth order parabola to obtain the basic metric value x for the evaluation element v. i membership value s i ;

[0143] Step S6.5: Repeat steps S6.3 to S6.4 to obtain the membership values ​​of the basic metric value x to all evaluation set elements, forming a vector (s1 s2 … s n );

[0144] Step S6.6: For vectors (s1 s2 … s n Normalization is performed, and calculations are performed. Obtain the normalized membership vectors (ns1 ns2 … ns) of the basic metric evaluation set. n ).

[0145] Step S7: Calculate the fuzzy comprehensive evaluation results of test adequacy.

[0146] Specifically, in step S7:

[0147] The fuzzy comprehensive evaluation results for test adequacy are calculated. After calculating the evaluation set membership vectors for each basic metric using a K-order parabolic membership function based on a unified spatial threshold distance, the fuzzy evaluation results r for each single factor are obtained. i =(a i1 a i2 … a in For i∈1…n, these single-factor fuzzy evaluation results are combined to construct a single-factor fuzzy evaluation matrix. Combined with the pre-set weight set of influencing factors W = (w1 w2 … w m ), through calculation The results of the adequacy evaluation of the entire information system software were obtained.

[0148] Example 2:

[0149] Example 2 is a preferred example of Example 1, and is used to illustrate the present invention in more detail.

[0150] The present invention also provides a test adequacy evaluation system for information system software. The test adequacy evaluation system for information system software can be implemented by executing the process steps of the test adequacy evaluation method for information system software. That is, those skilled in the art can understand the test adequacy evaluation method for information system software as a preferred embodiment of the test adequacy evaluation system for information system software.

[0151] A test adequacy evaluation system for information system software, provided by the present invention, includes:

[0152] Module M1: Identifies evaluation elements used for testing adequacy assessment;

[0153] Specifically, in module M1:

[0154] The evaluation elements used for adequacy assessment are identified, including the system characteristic states, system characteristic state transition edges, and system characteristic state space variables of the information system software. The specific steps are as follows:

[0155] Module M1.1: By analyzing the software modules and functional components of the information system, the system characteristic state set CS={s1,s2,…,sn} of the information system software is identified. The system characteristic state is determined by the attributes or values ​​of the software function-related variables. It is the functional state of the information system software in the variable space, including normal state and abnormal state.

[0156] Module M1.2: By analyzing the migration relationships between software functions of the information system, and combining the defined system characteristic state set CS, the system characteristic state migration edge set CE = {e1,e2,…,en} is identified. The system characteristic state migration edge set CE is a total order relation on the system characteristic state set CS, representing the temporal order of system characteristic states.

[0157] Module M1.3: By analyzing the variables that cause changes in the characteristic state of the system through periodic triggering or event stimulation in the information system software, the system characteristic state space variable set CP = {p1, p2, ..., pn} is identified. The system characteristic state space variable set CP is a set of variables that determine the system characteristic state and cause changes in the system characteristic state.

[0158] Module M2: Constructs a software state diagram of the information system based on the system characteristic states in the evaluation elements;

[0159] In module M2:

[0160] Based on the system's characteristic states, a software state diagram of the information system is constructed. Statistical metrics include the total number of system characteristic states, the system characteristic state transition edges, and the system characteristic state space variables. The specific steps are as follows:

[0161] Module M2.1: It uses a state diagram to formally express the system characteristic states, transition edges, and spatial variables of information system software. The system characteristic states are the nodes in the state diagram, the system characteristic state transition edges are the directed edges in the state diagram, and the system characteristic state spatial variables are the transition conditions between nodes in the state diagram.

[0162] Module M2.2: Performs data statistics on all nodes, directed edges, and transition conditions in the state graph to obtain the total number of system characteristic states TS, the total number of system characteristic state transition edges TE, and the total number of system characteristic state space variables TP.

[0163] Module M3: Traverses the information system software state diagram to generate test sequences, and constructs a test sequence set based on the test sequences;

[0164] In module M3:

[0165] The Depth-First Search (DFS) algorithm is used to traverse the state graph to generate a set of test sequences. A test sequence set is constructed based on the test sequences of a preset size. Statistical metrics include the number of activations of system characteristic states, the number of activations of system characteristic state transition edges, and the number of activations of system characteristic state space variables. The specific steps are as follows:

[0166] Module M3.1: The DFS algorithm is used to traverse all nodes, directed edges and transition conditions in the state graph to form a test sequence set CT = {t1, t2, ..., tn} of a preset size;

[0167] Module M3.2: Performs data statistics on the nodes, directed edges, and transition conditions activated by traversing the test sequence set CT to obtain the number of system characteristic state activations AS, the number of system characteristic state transition edge activations AE, and the number of system characteristic state space variable activations AP;

[0168] Module M4: Calculates the adequacy evaluation index for testing;

[0169] In module M4:

[0170] The basic evaluation indicators for test adequacy are calculated, including the evaluation indicators for the adequacy of system characteristic state tests, the evaluation indicators for the adequacy of system characteristic state transition edge tests, and the evaluation indicators for the adequacy of system characteristic state space variable tests.

[0171] The calculation formula for the sufficiency evaluation index of system characteristic state testing is as follows:

[0172]

[0173] The calculation formula for the sufficiency evaluation index of the system characteristic state transition edge test is as follows:

[0174]

[0175] The calculation formula for the sufficiency evaluation index of the system characteristic state-space variables is as follows:

[0176]

[0177] Module M5: Set parameters for fuzzy comprehensive evaluation of test adequacy;

[0178] In module M5:

[0179] To evaluate the adequacy of testing for information system software using a fuzzy comprehensive evaluation method, the following parameters are set: First, the evaluation parameters are defined, including an influencing factor set U, an evaluation set V, and an influencing weight set W. Specifically: the influencing factor set U = {system characteristic state coverage, system characteristic state transition edge coverage, system characteristic state spatial variable coverage}; the evaluation set V = {insufficient, basically sufficient, sufficient, very sufficient}; and the influencing weight set W = {w1, w2, w3}, where the values ​​of w1, w2, and w3 are configured according to the requirements of the information system software's testing adequacy evaluation and the actual situation.

[0180] Module M6: Calculates the membership vectors of the basic evaluation indicators for test adequacy based on the test adequacy evaluation indicators;

[0181] In module M6:

[0182] The membership vector calculation for the basic evaluation index of test adequacy adopts a K-order parabolic membership function based on a unified spatial threshold distance to determine each factor in the influencing factor set U. The resulting test adequacy evaluation index includes system characteristic states, system characteristic state transition edges, and system characteristic state spatial variables. The processing procedure for the membership degree of all evaluation terms in the evaluation set V is as follows:

[0183] Module M6.1: Performs a unified benchmark computational space mapping transformation on the input basic metric values ​​and membership interval thresholds based on average linear interpolation techniques to form the transformed basic metric values ​​x and membership interval threshold set T;

[0184] Module M6.2: Assuming the evaluation set V has n elements, obtain all interval threshold pairs (UTi DTi), i∈n;

[0185] Module M6.3: For each evaluation element v in the evaluation set V i Calculate the spatial distance Dist between the basic metric value x and the upper threshold UTi and the lower threshold DTi when the x reaches the corresponding interval threshold. i Dist i The formula for calculating it is ((x-UTi)). 2 +(x-DTi) 2 ) 2 ;

[0186] Module M6.4: Using spatial distance Dist i The reciprocal of the value is used as the result of calculating the membership function of the Kth order parabola to obtain the basic metric value x for the evaluation element v. i membership value s i ;

[0187] Module M6.5: Repeat modules M6.3 to M6.4 to obtain the membership values ​​of the basic metric value x to all elements of the evaluation set, forming a vector (s1 s2 … s n );

[0188] Module M6.6: For vectors (s1 s2 … s n Normalization is performed, and calculations are performed. Obtain the normalized membership vectors (ns1 ns2 … ns) of the basic metric evaluation set. n );

[0189] Module M7: Calculate the fuzzy comprehensive evaluation results of test adequacy.

[0190] In module M7:

[0191] The fuzzy comprehensive evaluation results for test adequacy are calculated. After calculating the evaluation set membership vectors for each basic metric using a K-order parabolic membership function based on a unified spatial threshold distance, the fuzzy evaluation results r for each single factor are obtained. i =(a i1 a i2 … a in For i∈1…n, these single-factor fuzzy evaluation results are combined to construct a single-factor fuzzy evaluation matrix. Combined with the pre-set weight set of influencing factors W = (w1 w2 … w m ), through calculation The results of the adequacy evaluation of the entire information system software were obtained.

[0192] Example 3:

[0193] Example 3 is a preferred example of Example 1, and is used to illustrate the present invention in more detail.

[0194] The method or approach to implementing this invention is as follows: A method and system for evaluating the adequacy of testing information system software, specifically including the following steps:

[0195] Step S1: Identify the evaluation elements used for adequacy evaluation, including the system characteristic states of the information system software, the system characteristic state transition edges, and the system characteristic state space variables. The specific sub-steps are as follows.

[0196] Step S11: By analyzing the software modules and functional components of the information system, identify the system characteristic state set CS={s1,s2,…,sn} of the information system software. The system characteristic state is determined by the attributes or values ​​of the software function-related variables. It is the functional state of the information system software in the variable space, including normal state and abnormal state.

[0197] Step S12: By analyzing the migration relationships between the software functions of the information system, and combining the defined system characteristic state set CS, identify the system characteristic state migration edge set CE = {e1,e2,…,en}. The system characteristic state migration edge set CE is a total order relation on the system characteristic state set CS, representing the temporal order of the system characteristic states.

[0198] Step S13: By analyzing the variables in the information system software that are periodically triggered or event-driven, the system characteristic state space variable set CP = {p1, p2, ..., pn} is identified. The system characteristic state space variable set CP is a set of variables that determine the system characteristic state and cause changes in the system characteristic state.

[0199] Step S2: Construct the information system software state diagram based on the system characteristic states, and count the total number of system characteristic states, the system characteristic state transition edges, and the system characteristic state space variables, etc. The specific sub-steps are as follows.

[0200] Step S21: Use a state diagram to formally express the system characteristic states, transition edges, and spatial variables of the information system software. The system characteristic states are the nodes in the state diagram, the system characteristic state transition edges are the directed edges in the state diagram, and the system characteristic state spatial variables are the transition conditions between nodes in the state diagram.

[0201] Step S22: Perform data statistics on all nodes, directed edges, and transition conditions in the state graph to obtain the total number of system characteristic states TS, the total number of system characteristic state transition edges TE, and the total number of system characteristic state space variables TP.

[0202] To facilitate the demonstration of the calculation methods and processes involved in this invention, the total number of system feature states TS is set to 45, the total number of system feature state transition edges TE is set to 70, and the total number of system feature state space variables TP is set to 128.

[0203] Step S3: Use the DFS algorithm to traverse the state graph to generate a set of test sequences. Construct a test sequence set based on a certain size of test sequences, and count the system feature state activation number, system feature state transition edge activation number, and system feature state space variable activation number, etc. The specific sub-steps are as follows.

[0204] Step S31: Use the depth-first search (DFS) algorithm to traverse all nodes, directed edges, and transition conditions in the state graph to form a test sequence set CT = {t1, t2, ..., tn} of a certain size;

[0205] Step S32: Perform data statistics on the nodes, directed edges, and transition conditions activated by traversing the test sequence set CT to obtain the number of system characteristic state activations AS, the number of system characteristic state transition edge activations AE, and the number of system characteristic state space variable activations AP.

[0206] To facilitate the demonstration of the calculation methods and processes involved in this invention, the number of system feature state activations AS is set to 42, the number of system feature state transition edge activations AE is set to 65, and the number of system feature state space variable activations AP is set to 98.

[0207] Step S4: Calculate the basic evaluation indicators for test adequacy, including three indicators: the evaluation indicator for the adequacy of system characteristic state tests, the evaluation indicator for the adequacy of system characteristic state transition edge tests, and the evaluation indicator for the adequacy of system characteristic state space variable tests.

[0208] The calculation formula for the sufficiency evaluation index of system characteristic state testing is as follows:

[0209]

[0210] The calculation formula for the sufficiency evaluation index of the system characteristic state transition edge test is as follows:

[0211]

[0212] The calculation formula for the sufficiency evaluation index of the system characteristic state-space variables is as follows:

[0213]

[0214] To facilitate the demonstration of the calculation method and process involved in this invention, the above calculation formula is used. Based on the test data such as the total number of system characteristic states TS, the total number of system characteristic state transition edges TE, the total number of system characteristic state space variables TP, the number of system characteristic state activations AS, the number of system characteristic state transition edge activations AE, and the number of system characteristic state space variable activations AP, the three basic evaluation index values ​​of test sufficiency are calculated, as shown in the table below.

[0215] Table 1 Basic evaluation indicators for test adequacy

[0216]

[0217] Step S5: Setting Parameters for Fuzzy Comprehensive Evaluation of Test Adequacy. The fuzzy comprehensive evaluation method is used to evaluate the test adequacy of information system software. First, evaluation parameters need to be set, mainly including the influencing factor set U, the evaluation set V, and the influence weight set W. The influencing factor set U = {system characteristic state coverage, system characteristic state transition edge coverage, system characteristic state space variable coverage}, the evaluation set V = {insufficient, basically sufficient, sufficient, very sufficient}, and the influence weight set W = {w1, w2, w3}. The values ​​of w1, w2, and w3 can be flexibly configured according to the test adequacy evaluation requirements and actual conditions of the information system software.

[0218] To facilitate the demonstration of the calculation methods and processes involved in this invention, an influence weight set W = {0.2, 0.2, 0.6} is set.

[0219] Step S6: Calculate the membership vector of the basic evaluation index of test sufficiency. Use the K-order parabolic membership function based on the unified spatial threshold distance to determine the membership degree of each factor in the influencing factor set U, that is, the system characteristic state, system characteristic state transition edge, system characteristic state spatial variable and other test sufficiency evaluation indexes calculated in step S4, with respect to all evaluation terms in the evaluation set V. The processing procedure is as follows.

[0220] Step S61: Perform a unified benchmark computational space mapping transformation on the input basic metric values ​​and membership interval thresholds based on the average linear interpolation technique to form the transformed basic metric values ​​x and membership interval threshold set T;

[0221] Step 62: Assuming the evaluation set V has n elements, obtain all interval threshold pairs (UT). i DT i ), i∈n;

[0222] Step 63: For each evaluation element v in the evaluation set V i Calculate the basic metric value x reaching the corresponding interval threshold and the upper threshold UT. i and lower threshold DT i Spatial distance Dist i Dist i The formula for calculating it is ((x-UTi)). 2 +(x-DTi) 2 ) 2 ;

[0223] Step 64: Use spatial distance Dist i The reciprocal of the value is used as the result of calculating the membership function of the Kth order parabola to obtain the basic metric value x for the evaluation element v. i membership value s i ;

[0224] Step 65: Repeat steps 63 and 64 to obtain the membership values ​​of the basic metric value x to all evaluation set elements, forming a vector (s1 s2 … s n );

[0225] Step 66: For vectors (s1 s2 … s n Normalization is performed, and calculations are performed. Obtain the normalized membership vectors (ns1 ns2 … ns) of the basic metric evaluation set. n ).

[0226] To facilitate the demonstration of the calculation method and process involved in this invention, the membership interval thresholds for system characteristic states are set to {0, 0.8, 0.9, 0.98, 1}, the membership interval thresholds for system characteristic state transition edges are set to {0, 0.7, 0.85, 0.96, 1}, and the membership interval thresholds for system characteristic state space variables are set to {0, 0.6, 0.8, 0.92, 1}. Based on the calculated basic evaluation index values ​​for test adequacy, the membership vectors of each basic evaluation index for test adequacy can be calculated using a K-order parabolic membership function, as shown in the table below.

[0227] Table 2 Membership vectors of basic evaluation indicators for test adequacy

[0228]

[0229]

[0230] Step S7: Calculate the sufficiency fuzzy comprehensive evaluation results. Using a K-order parabolic membership function based on a unified spatial threshold distance, calculate the evaluation set membership vectors for each basic metric, and then obtain the fuzzy evaluation results r for each single factor. i =(a i1 a i2 … a in For i∈1…n, these single-factor fuzzy evaluation results are combined to construct a single-factor fuzzy evaluation matrix. Combined with the pre-set weight set of influencing factors W = (w1 w2 … w m ), through calculation This allows us to obtain the adequacy evaluation results for the entire information system software.

[0231] Assuming the calculated adequacy evaluation results for the information system software testing are (0.003, 0.024, 0.709, 0.264), and based on the defined evaluation set V = {Insufficient, Basically Adequate, Adequate, Very Adequate}, then 0.3% represents insufficient, 3.4% represents basically adequate, 70.9% represents adequate, and 26.4% represents very adequate. Therefore, it can be determined that the adequacy evaluation result is the most adequate, with a confidence level of 70.9%.

[0232] To facilitate the demonstration of the calculation methods and processes involved in this invention, using the calculated membership vectors of each basic evaluation index for test adequacy and the pre-set weight set of influencing factors, the test adequacy evaluation result of the entire information system software can be calculated as (0.0159 0.4749 0.4766 0.0326). Based on the defined evaluation set V = {Insufficient, Basically Adequate, Adequate, Very Adequate}, the test adequacy evaluation result of the information system software is characterized as follows: 1.59% is insufficient, 47.49% is basically adequate, 47.66% is adequate, and 3.26% is very adequate. Therefore, it can be judged that the test adequacy evaluation result is the most adequate, with a confidence level of 47.66%.

[0233] Those skilled in the art will understand that, in addition to implementing the system, apparatus, and their modules provided by this invention in purely computer-readable program code, the same program can be implemented in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, the system, apparatus, and their modules provided by this invention can be considered a hardware component, and the modules included therein for implementing various programs can also be considered structures within the hardware component; alternatively, modules for implementing various functions can be considered both software programs implementing the method and structures within the hardware component.

[0234] Specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art can make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention. Unless otherwise specified, the embodiments and features described in this application can be arbitrarily combined with each other.

Claims

1. A method for evaluating the adequacy of testing information system software, characterized in that, include: Step S1: Identify the evaluation elements used for testing adequacy assessment; Step S2: Construct an information system software state diagram based on the system characteristic states in the evaluation elements; Step S3: Traverse the information system software state diagram to generate test sequences, and construct a test sequence set based on the test sequences; Step S4: Calculate the test adequacy evaluation index; Step S5: Set the parameters for fuzzy comprehensive evaluation of test adequacy; Step S6: Calculate the membership vector of the basic evaluation index of test adequacy based on the test adequacy evaluation index; Step S7: Calculate the fuzzy comprehensive evaluation result of test adequacy; In step S2: Based on the system's characteristic states, a software state diagram of the information system is constructed. Statistical metrics include the total number of system characteristic states, the system characteristic state transition edges, and the system characteristic state space variables. The specific steps are as follows: Step S2.1: Use a state diagram to formally express the system characteristic states, transition edges, and spatial variables of the information system software. The system characteristic states are the nodes in the state diagram, the system characteristic state transition edges are the directed edges in the state diagram, and the system characteristic state spatial variables are the transition conditions between nodes in the state diagram. Step S2.2: Perform data statistics on all nodes, directed edges, and transition conditions in the state graph to obtain the total number of system characteristic states TS, the total number of system characteristic state transition edges TE, and the total number of system characteristic state space variables TP.

2. The test adequacy evaluation method for information system software according to claim 1, characterized in that, In step S1: The evaluation elements used for adequacy assessment are identified, including the system characteristic states, system characteristic state transition edges, and system characteristic state space variables of the information system software. The specific steps are as follows: Step S1.1: By analyzing the software modules and functional components of the information system, identify the system characteristic state set CS of the information system software. The system characteristic state is determined by the attributes or values ​​of the software function-related variables. It is the functional state of the information system software in the variable space, including normal state and abnormal state. Step S1.2: By analyzing the migration relationships between the software functions of the information system, and combining the defined system characteristic state set CS, the system characteristic state migration edge set CE is identified. The system characteristic state migration edge set CE is a total order relation on the system characteristic state set CS, representing the temporal order of the system characteristic states. Step S1.3: By analyzing the variables in the information system software that are periodically triggered or event-driven, the system characteristic state space variable set CP is identified. The system characteristic state space variable set CP is a set of variables that determine the system characteristic state and cause changes in the system characteristic state.

3. The method for evaluating the adequacy of testing information system software according to claim 1, characterized in that, In step S3: The Depth-First Search (DFS) algorithm is used to traverse the state graph to generate a set of test sequences. A test sequence set is constructed based on the test sequences of a preset size. Statistical metrics include the number of activations of system characteristic states, the number of activations of system characteristic state transition edges, and the number of activations of system characteristic state space variables. The specific steps are as follows: Step S3.1: Use the DFS algorithm to traverse all nodes, directed edges and transition conditions in the state graph to form a test sequence set CT of a preset size; Step S3.2: Perform data statistics on the nodes, directed edges, and transition conditions activated by the CT traversal of the test sequence set to obtain the number of system characteristic state activations AS, the number of system characteristic state transition edge activations AE, and the number of system characteristic state space variable activations AP.

4. The test adequacy evaluation method for information system software according to claim 1, characterized in that, In step S4: The basic evaluation indicators for test adequacy are calculated, including the evaluation indicators for the adequacy of system characteristic state tests, the evaluation indicators for the adequacy of system characteristic state transition edge tests, and the evaluation indicators for the adequacy of system characteristic state space variable tests. The calculation formula for the sufficiency evaluation index of system characteristic state testing is as follows: The calculation formula for the sufficiency evaluation index of the system characteristic state transition edge test is as follows: The calculation formula for the sufficiency evaluation index of the system characteristic state-space variables is as follows:

5. The method for evaluating the adequacy of testing information system software according to claim 1, characterized in that, In step S5: To set up fuzzy comprehensive evaluation parameters for test adequacy, the fuzzy comprehensive evaluation method is used to evaluate the test adequacy of information system software. First, evaluation parameters are set, including an influencing factor set U, an evaluation set V, and an influencing weight set W, where: the influencing factor set U = {system characteristic state coverage, system characteristic state transition edge coverage, system characteristic state space variable coverage}; the evaluation set V = {insufficient, basically sufficient, sufficient, very sufficient}; and the influencing weight set W = {w1, w2, w3}, where the values ​​of w1, w2, and w3 are configured according to the test adequacy evaluation requirements and actual conditions of the information system software.

6. A test adequacy evaluation system for information system software, characterized in that, include: Module M1: Identifies evaluation elements used for testing adequacy assessment; Module M2: Constructs a software state diagram of the information system based on the system characteristic states in the evaluation elements; Module M3: Traverses the information system software state diagram to generate test sequences, and constructs a test sequence set based on the test sequences; Module M4: Calculates the adequacy evaluation index for testing; Module M5: Set parameters for fuzzy comprehensive evaluation of test adequacy; Module M6: Calculates the membership vector of the basic evaluation index of test adequacy based on the test adequacy evaluation index; Module M7: Calculate the fuzzy comprehensive evaluation results of test adequacy; In module M2: Based on the system's characteristic states, a software state diagram of the information system is constructed. Statistical metrics include the total number of system characteristic states, the system characteristic state transition edges, and the system characteristic state space variables. The specific steps are as follows: Module M2.1: It uses a state diagram to formally express the system characteristic states, transition edges, and spatial variables of information system software. The system characteristic states are the nodes in the state diagram, the system characteristic state transition edges are the directed edges in the state diagram, and the system characteristic state spatial variables are the transition conditions between nodes in the state diagram. Module M2.2: Performs data statistics on all nodes, directed edges, and transition conditions in the state graph to obtain the total number of system characteristic states TS, the total number of system characteristic state transition edges TE, and the total number of system characteristic state space variables TP.

7. The test adequacy evaluation system for information system software according to claim 6, characterized in that: In module M1: The evaluation elements used for adequacy assessment are identified, including the system characteristic states, system characteristic state transition edges, and system characteristic state space variables of the information system software. The specific steps are as follows: Module M1.1: By analyzing the software modules and functional components of the information system, the system characteristic state set CS of the information system software is identified. The system characteristic state is determined by the attributes or values ​​of the software function-related variables. It is the functional state of the information system software in the variable space, including normal state and abnormal state. Module M1.2: By analyzing the migration relationships between information system software functions and combining the defined system characteristic state set CS, the system characteristic state migration edge set CE is identified. The system characteristic state migration edge set CE is a total order relation on the system characteristic state set CS, representing the temporal order of system characteristic states. Module M1.3: By analyzing the variables that cause changes in the characteristic state of the system through periodic triggering or event stimulation in the information system software, the system characteristic state space variable set CP is identified. The system characteristic state space variable set CP is a set of variables that determine the system characteristic state and cause changes in the system characteristic state. In module M3: The Depth-First Search (DFS) algorithm is used to traverse the state graph to generate a set of test sequences. A test sequence set is constructed based on the test sequences of a preset size. Statistical metrics include the number of activations of system characteristic states, the number of activations of system characteristic state transition edges, and the number of activations of system characteristic state space variables. The specific steps are as follows: Module M3.1: Uses the DFS algorithm to traverse all nodes, directed edges and transition conditions in the state graph to form a test sequence set CT of a preset size; Module M3.2: Performs data statistics on the nodes, directed edges, and transition conditions activated by traversing the test sequence set CT to obtain the number of system characteristic state activations AS, the number of system characteristic state transition edge activations AE, and the number of system characteristic state space variable activations AP; In module M4: The basic evaluation indicators for test adequacy are calculated, including the evaluation indicators for the adequacy of system characteristic state tests, the evaluation indicators for the adequacy of system characteristic state transition edge tests, and the evaluation indicators for the adequacy of system characteristic state space variable tests. The calculation formula for the sufficiency evaluation index of system characteristic state testing is as follows: The calculation formula for the sufficiency evaluation index of the system characteristic state transition edge test is as follows: The calculation formula for the sufficiency evaluation index of the system characteristic state-space variables is as follows: In module M5: To set up fuzzy comprehensive evaluation parameters for test adequacy, the fuzzy comprehensive evaluation method is used to evaluate the test adequacy of information system software. First, evaluation parameters are set, including an influencing factor set U, an evaluation set V, and an influencing weight set W, where: the influencing factor set U = {system characteristic state coverage, system characteristic state transition edge coverage, system characteristic state space variable coverage}; the evaluation set V = {insufficient, basically sufficient, sufficient, very sufficient}; and the influencing weight set W = {w1, w2, w3}, where the values ​​of w1, w2, and w3 are configured according to the test adequacy evaluation requirements and actual conditions of the information system software.

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