38 results about "Metamorphic testing" patented technology

The invention relates to an embedded software testing method based on AADL (Architecture Analysis and Design Language) mode transformation relationship, which has the following steps of: constructing a mode transition diagram on the basis of mode information in an AADL model, and converting the diagram into a mode relationship tree required by a transformation test according to the improved depth-first traversing algorithm; constructing a source test case in the mode transformation relationship by traversing the mode relationship tree, generating a subsequent test case by means of the mode transformation relationship in the AADL model, and verifying the mode transformation relationship to obtain the conclusion of the transformation test. The embedded software testing method based on AADL mode transformation relationship solves the 'Oracle' problem existing in the embedded software test, is convenient for a user to test the embedded software at an early stage of software design and ensures the reliability of software at a system architecture level. If the model architecture can not meet corresponding requirements, the architecture of the software can be modified at an early stage of development, thus the development cost is saved, and meanwhile, the development cycle can also be shortened.

The invention discloses a method for generating a metamorphic test case based on an adaptive random strategy, and aims at randomly automatically generating a test case based on an adaptive strategy. The method comprises the steps of randomly generating a first group of original test cases; generating additional test cases according to metamorphic relation; forming a selected test case through the two cases; dividing an input field to obtain a subfield without being covered with the selected test case; generating a plurality of test cases randomly in the subfield; selecting one group of test cases as the candidate original test cases; generating the additional test cases according to the metamorphic relation; then selecting the test cases with the maximum distance as the next group of text cases according to the distance from the candidate test cases to the selected test cases and the distance from the candidate original test cases to the additional test cases. The test case generation method is simple and clear; the dispersion, effectiveness and coverage rate of the test cases in the input field are greatly improved.

The invention discloses a software testing method facing to software upgrading. The method is automatically constructed on the basis of the metamorphic relation of equation description. Before software upgrading, a tester can construct the metamorphic relation of each procedure at the aim of a conventional software; the procedure refers to a procedure code for achieving a special function calculating function; after software upgrading, at the aim of a modified procedure, the tester can produce n random numbers as use cases for testing within a certain range, then substituting each case for testing and corresponding output of the case in the modified procedure into a metamorphic relation expression of the procedure before modification, and checking whether the metamorphic relation expression is tenable or not, and if the modified procedure is not conform to the metamorphic relation constructed before, errors on the software exist during the updating process. Through the method provided by the invention, the tester can apply the metamorphic relation constructed into a metamorphosis process, therefore, the correctness of the software during the version upgrading process can be verified.

The invention belongs to the field of software testing, and particularly discloses a positioning method for a failure test instance in metamorphic testing. The positioning method comprises the following steps of firstly, selecting a testing instance from a testing instance set as an original testing instance; according to the input relation of the metamorphic relation in an metamorphic relation set, enabling the original testing instance to generate an additional testing instance; according to the output result of the tested software, verifying whether the output relation of the metamorphic relation is met or not, and recording the testing instance not meeting the metamorphic relation, and marking by a non-zero value; according to the verification result marking value of the metamorphic relation, calculating the anomaly degree of the testing instance; utilizing the same method to perform gradual traversing verification on other testing instances, and calculating the anomaly degree; finally, determining the testing instance with the maximum anomaly degree as the failure testing instance. The positioning method for the failure test instance in the metamorphic testing has the advantages that the positioning technique is simple and clear, the implementation is easy, and the failure testing instance is accurately and effectively positioned through the quantitative calculating of the anomaly degree.

The invention relates to a metamorphic relation priority ranking method for metamorphic testing of parallel programs. A metamorphic testing technology is applied to software testing of the parallel programs, and priority ranking is firstly performed on constructed metamorphic relations, so that errors in the programs are discovered as early as possible, and the solving efficiency of the Oracle problem in software testing is improved. According to a priority ranking strategy, derivative testing examples and original testing examples, generated on the basis of the metamorphic relations, are adopted, and similarity between the examples are taken as the basis, the similarity of paths covered by executive programs of the examples is estimated, the error detecting range of the metamorphic relations based on the existing testing examples is further estimated, and priority ranking is performed based on the metamorphic relations. The method comprises specific steps as follows: (1) evaluating the error detecting capacity of each process of the metamorphic relations; (2) setting a weight value of each process so as to reflect the error detecting capacity of each process of the metamorphic relations, and evaluating weight of the error detecting capacity of each process to the error detecting capacity of the whole program; (3) evaluating the program error detecting capacity of the metamorphic relations, and determining the priority of each metamorphic relation; (4) detecting the programs.

The invention discloses an integer overflow fault detection method based on a metamorphic relation. The integer overflow fault detection method includes employing a static testing tool to perform static testing in a program to be detected, initially determining an integer variable might occurring of integer overflow and marking the integer variable as an integer overflow detection point; according to a 'definition-application' model containing an integer definition statement list and an integer application statement list, determining an integer identifier, referenced by the integer definition statement and integer application statement, of the integer overflow detection point as an overflow integer, and if the overflow integer contains integer dangerous application statement of an integer dangerous application statement list, the overflow integer is marked as a dangerous integer; finally, before the statement of the dangerous integer referenced by the source code of the program detected is executed, adopting the metamorphic relation method to detect whether or not the integer overflow fault occurs to the dangerous integer. The integer overflow fault is detected accurately and efficiently.

The invention discloses a formal description and decomposition method for a metamorphic relation. The method includes the following steps: (1) according to targeted tested software, extracting and designing the metamorphic relation that the software mush satisfy to create the metamorphic relation; (2) performing formal modeling on the obtained metamorphic relation on the basis of symbolic logic, determining constraint conditions under which the metamorphic relation is established, performing formal description, then describing input parameters and output parameters of the metamorphic relation on the basis of the symbolic logic, and establishing a formal description model of the metamorphic relation; (3) on the basis of the formal model, respectively extracting subrelations forming the metamorphic relation and a set description form of a metamorphic relation composition model, and establishing a metamorphic relation decomposition model. The method is simple and clear, description capacity and application range of the formal model are guaranteed through symbolic logic description, the accurate, standard and effective method is provided for description of the metamorphic relation, and the method is more conducive to automated implementation of subsequent metamorphic testing.

The invention belongs to the technical field of image region growth algorithm testing, and particularly relates to a metamorphic testing method for an image region growth algorithm. Image region growth is one of important functions of real-time image processing. However, due to the factor of operation uncertainty, the test judgment of the image region growth algorithm is difficult to obtain in theactual test. Based on this, the metamorphic test method is applied to the test of the image region growth algorithm; A series of metamorphic relations are extracted by analyzing geometric attributes,numerical attributes and algorithm characteristics of the algorithm, and the metamorphic test method of the image region growth algorithm is formed based on the metamorphic relations, so that the test judgment problem of the image region growth algorithm can be effectively solved.

The invention discloses an unmanned aerial vehicle intelligent airway planning test method based on metamorphic test technology, comprising the following steps: (1) analyzing an unmanned aerial vehicle intelligent airway planning algorithm, defining a metamorphic relationship, and designing a subsequent test case generator and a result comparator; (2) generating an initial test case set by utilizing a random value method under a certain constraint rule and inputting the initial test case set into the algorithm to obtain initial output of test cases; (3) taking the initial test case set and theinitial output as inputs and obtaining a subsequent test case set and a corresponding subsequent output through a subsequent test case generator; and (4) inputting an initial output result and a subsequent output result into a result comparator. If a corresponding metamorphic relation is met, the test is passed, and no defect is found; otherwise, an unmanned aerial vehicle intelligent route planning algorithm has defects. According to the invention, the problem of lack of Oracle in unmanned aerial vehicle intelligent route algorithm testing can be alleviated, the generation of test cases canbe guided, and the utilization rate of the test cases can be improved.

The invention belongs to the technical field of image region growth algorithm test, in particular to a metamorphosis test system of an image region growth algorithm. Image region growth is one of theimportant functions of real-time image processing. However, due to the uncertainty of the operation, it is difficult to obtain the test results of the image region growth algorithm in the actual test.Based on this, the invention applies the metamorphosis test system to the test of the image region growth algorithm, a series of metamorphic relations are extracted by analyzing the geometric attributes, numerical attributes and algorithm characteristics of the algorithm. Based on these metamorphic relations, the metamorphic testing method of image region growth algorithm is formed, which can effectively solve the problem of testing and judging the image region growth algorithm.

According to the invention, a metamorphic test technology is used to carry out correctness test on the intelligent traffic model; a metamorphic relation applied to the intelligent traffic model is designed, the correctness of a program function is judged from multiple aspects, the intelligent traffic model is tested by using the original use case and a derivative use case generated based on the metamorphic relation, whether the output of the original use case and the derivative use case meets the corresponding metamorphic relation or not is judged, and a test result is obtained. According to the method, the correctness of the intelligent traffic model can be reasonably measured and evaluated by adopting a new software testing method.

The invention discloses a transformation test case generation method based on an adaptive random strategy, that is, the test case is randomly and automatically generated based on the adaptive strategy. First, the first group of original test cases is randomly generated, and additional test cases are generated according to the metamorphic relationship, and the two constitute the selected test cases; secondly, the input domain is divided to obtain the sub-domains that are not covered by the selected test cases; thirdly, Randomly generate multiple test cases in this subdomain, select a group of test cases as candidate original test cases, and generate additional test cases according to the metamorphic relationship; finally, according to the distance between the candidate test cases and the selected test cases, and The distance between the candidate original test case and its additional test cases, the test case with the largest distance is selected as the next set of test cases. The test case generation method of the invention is simple and clear, and greatly improves the dispersion, effectiveness and coverage of the test case in the input field.

The embodiment of the invention provides a program testing method, a program testing device, electronic equipment and a storage medium. The program testing method specifically comprises the steps of acquiring a block generation node random algorithm program, wherein the block generation node random algorithm program comprises a random function and a random seed; running a block generation node random algorithm program to obtain a first test result; generating a test program according to the random function and the random seed, and running the test program to obtain a second test result; and determining the program performance of the block generation node random algorithm program according to the first test result and the second test result. The embodiment of the invention provides a program testing method. According to the method, a metamorphic test idea is adopted, an automatic framework is introduced, random functions and random seeds in a blockchain project program are automaticallymined, a corresponding test program is automatically generated, and the problem of test prediction of randomness of a block generation node selection algorithm is solved, so that the randomness and reliability of the metamorphic test node selection algorithm are improved.

The invention provides an automatic driving laser radar data amplification method based on rule variation, so as to obtain enhanced point cloud data, and finally perform quality evaluation on the enhanced data, and the method comprises the following steps: designing a variation rule and an automatic variation technology which accord with the point cloud data, and performing variation on seed pointcloud data to serve as a theoretical support for point cloud data amplification; based on the open-source large-scale point cloud data set data and the PCL point cloud operation library, further integrating the enhanced data to form an open-source point cloud test data set, and selecting an industrial-grade automatic driving software system for experimental verification; finally, introducing a metamorphic relation into variation amplification data evaluation, and evaluating and verifying the effectiveness of the laser radar point cloud test data generation technology based on a metamorphic test verification process and an actual system feedback result.

The invention belongs to the field of primary and secondary peak value ratio calculation algorithm testing, and particularly relates to a metamorphic testing system of a primary and secondary peak value ratio calculation algorithm. The system comprises a metamorphic relation extraction module, an additional test case generation module and a verification module. The metamorphic relation extractionmodule is used for extracting a metamorphic relation according to a regional image and a neighborhood image input by a primary-secondary peak ratio calculation algorithm; the additional test case generation module is used for combining the original test case with the metamorphic relationship to generate an additional test case, and outputting the additional test case to the verification module; and the verification module is used for inputting the original test case and the additional test case into the tested program and verifying whether the tested program has defects or not. Compared with the prior art, the metamorphic testing system is derived from geometric attributes, numerical attributes and algorithm characteristics in the algorithm, so that an absolutely accurate expected result does not need to be obtained, and the problem of test judgment uncertainty of a reconstructed standard model can be well solved.

The invention discloses a method of utilizing metamorphic testing to evaluate correctness of a commodity searching system. The method includes the following steps: initializing a searching keyword A,wherein A is a commodity bought on a shopping platform; utilizing the keyword A for searching in the to-be-evaluated commodity searching system, and denoting a searching result set by FR1; constructing subsequent querying keywords B according to construction methods of carrying out position exchange on the keyword, associating the keyword with titles, prices, locations of consignment and filterable attributes to carry out filtering together, and carrying out operations of repetition, adhesion, simplified / traditional Chinese characters, wrongly written characters, partial deletion and useless-symbol doping on the keyword; utilizing the keywords B for searching, and denoting searching result sets as FR2; and carrying out result comparison and calculation on FR1 and FR2 under use of the different construction methods to obtain an index result of evaluating commodity searching function quality. The method can effectively carry out searching correctness evaluation on a shopping website searching engine through processing on the commodity attributes, commodity rankings and the commonly used commodity keyword.

The invention discloses a method for selecting an unsupervised machine learning system based on metamorphic testing. According to the method, 11 universal metamorphic relations suitable for most application scenes are defined on the basis of general expectation of a user on a clustering system by taking dynamic characteristics of measurement data as a purpose, so that the oracle problem in the field of unsupervised machine learning is effectively relieved, and the purpose of verifying the unsupervised machine learning system is achieved; secondly, a system characteristic-oriented sufficiency criterion based on the metamorphic relationship is defined, the metamorphic relationship is endowed with different weights by a user according to importance and severity of a failure clustering mode, and a final weighted score is calculated; according to the invention, a set of complete unsupervised machine learning system verification and evaluation system is finally formed; a user is allowed to select a part of universal metamorphic relations according to own requirements or define a new specific metamorphic relation according to domain related knowledge, and finally the user is helped to deeply understand algorithm characteristics and select an unsupervised machine learning system suitable for a specific scene.

The invention discloses a metamorphic test method for an automatic driving system, which is characterized in that test cases are expanded on the basis of existing automatic driving system test cases according to metamorphic rules, newly generated test cases and original data are input into an automatic driving system together, and the performance of the automatic driving system is observed, so that the problem of insufficient test is solved. Three parts ofa metamorphic test case generation module, an automatic verification module and a test report generation module are included. The input is the original test picture and the test case which is expandedbased on the metamorphic rule, the original test picture and the test case are sequentially sent to the automatic driving system, the difference of output results is compared, and possible defects of the system are judged. The method has the beneficial effects that the problems of insufficient test cases of the automatic driving system and difficulty in test predication collection are solved, meanwhile, the test loss can be reduced, and the product research and development period is shortened.

The invention discloses a test case self-adaptive generation method for a metamorphic test. The test case self-adaptive generation method comprises the following steps: (1) initializing; (2) checking whether all partitions of all parameters are covered or not; (3) selecting uncovered partitions, and randomly generating a metamorphic test case set; (4) calculating the distance between the initial input and the subsequent input; (5) taking a group of metamorphic test inputs with the maximum distance as candidate inputs; (6) calculating an abnormal score of the candidate input relative to the result set; and (7) removing the candidate input with the abnormal score smaller than the threshold value, if the candidate input set is empty, returning to the step (3), and otherwise, returning to the step (2). The invention supports the metamorphic test, and automatically generates the test case until all the input partitions at least comprise one test input; differential measurement of initial test input and subsequent test input is supported, difference measurement of test input and a result set is supported, a measurement result is not affected by parameter dimensions, the possibility of discovering defects is improved, and a small data set is supported.

The invention discloses a sentence granularity metamorphic testing method oriented to a neural machine translation system, and belongs to the field of metamorphic testing, aiming at the translation robustness evaluation problem existing in the neural machine translation system. The method comprises the following steps: firstly, carrying out data preprocessing operation on two groups of texts which need to be subjected to similarity calculation to generate two groups of word lists; then, using a TF-IDF-based word bag model to construct text vectors for the two groups of word lists, and calculating an included angle cosine value of the two groups of text vectors; meanwhile, calculating a Jaccard similarity coefficient and an editing distance of the two groups of word lists; and finally, calculating the similarity between the sentences and the metamorphic relationship satisfaction rate according to the defined similarity calculation formula and the metamorphic relationship. According to the method, the problem that a single cosine similarity method is difficult to reflect semantic changes caused by different word sequences of the sentences is solved, the capability of distinguishing the semantic changes caused by the word sequence changes of the sentences is enhanced, and the sentence similarity calculation accuracy and the translation quality evaluation accuracy are improved.

The invention discloses a block chain smart contract test method based on a metamorphic test, and belongs to the field of software engineering. Comprising the following steps: step 1, analyzing a called function and a code of a parameter thereof based on a smart contract; 2, analyzing necessary attributes among the intelligent contract parameters according to the called function and the corresponding parameters; step 3, determining a metamorphic relationship (MRs) according to a relationship between input and output in the necessary attributes, wherein the metamorphic relationship comprises an input metamorphic relationship and an output metamorphic relationship; and step 4, generating an original test case by using a random test method, generating a subsequent test case according to input relationship, respectively running the two groups of test cases in the smart contract, and verifying the correctness of the result by judging whether the output result meets the corresponding output relationship. According to the method, the oracle problem in the smart contract test is relieved while the security defect of the smart contract is tested, and the effectiveness and advantages of the method are verified by performing a test experiment on the existing smart contract vulnerability.

The invention discloses a metamorphic test method for a concurrent program in order to solve the test expectation problem existing in a concurrent program test, and the metamorphic test method comprises the following steps: aiming at the characteristic of executing interlacing by the concurrent program, guiding the identification of a metamorphic relation mode by using an interlacing scene capable of triggering data competition; taking the execution track of the original test case as an original execution sequence, generating a derivative test case according to the metamorphic relation mode, and controlling the execution of the derivative test case; verifying the test result by comparing whether the output results of the derivative test case and the original test case violate the current metamorphic relation mode or not; meanwhile, a metamorphic relation mode of concurrent programs is provided, and generation of derivative test cases and judgment of test results are guided. According to the method, the execution process of the program is optimized by reducing the interlaced space of the concurrent program, and the data competition fault in the concurrent program can be effectively detected.

According to the invention, the metamorphic test technology is adopted to test the correctness of the intelligent traffic model, a metamorphic relationship applied to the intelligent traffic model isdesigned, the correctness of program functions is judged from multiple aspects, and an original case and a derivative case generated based on the metamorphic relationship are used for testing the intelligent traffic model, and checking whether the outputs of the original and derivative cases meet the corresponding metamorphic relationship or not to obtain a test result. According to the method, the correctness of the intelligent traffic model can be reasonably measured and evaluated by adopting a new software testing method.

The invention discloses a linear classifier-oriented software testing method based on metamorphic testing, which comprises the following steps of: 1, randomly generating a plurality of groups of training data sets and testing data sets as source data sets, and testing a to-be-tested program by utilizing the source data sets to obtain a training result; 2, generating a new data set according to a mode in a metamorphic relation according to the hyperplane model obtained by the source data set, and training on the new data set to obtain a group of new hyperplane models; and 3, calculating whether the hyperplane model obtained by training the hyperplane model and the new data set meets a metamorphic relation, and if the metamorphic relation is not met on any training data set, judging that the program has bug. According to the stability of the linear classifier, two new metamorphic relations are provided, the test result is more accurate, the training result on the source data set is applied when the source data set generates the new data set, and the test effect is improved.