CN101814055A - Sampling method for test cases in clusters - Google Patents
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Abstract
The invention discloses a stamping method for test cases in clusters, which comprises the following steps of: selecting the test cases in the clusters to test based on a technology for filtrating the clusters in an observed software test technology; computing the reliability of excused sentences according to a test result; judging whether the excused sentences are doubtful sentences, wherein the doubtful sentences form a doubtful sentences set; computing the failure probability of remainder test cases in the clusters according to the doubtful sentences set; selecting the test case with the highest failure probability; testing the result and recomputing the reliability of each sentence; updating the doubtful sentences set; and repeating the step of sampling to the untested test cases till that the failure probability of all remainder test cases in the clusters are 0. As the results of the test cases after sampling do not need to be tested, the method simples the test cases, saves the time and the energy for manually testing the test cases, and guarantees that the failure test cases in the test cases to be sampled has significant proportion and the reliability value of the sentences can be used for helping test persons to perform error locating.
Description
Technical field
The invention belongs to the software test field, relate to software test result's checking, at first test case is carried out cluster, from each class bunch, extract test case then and allow the hand inspection test result, need hand inspection result's test use cases to save manpower by yojan according to execution route.The present invention is mainly used in the generation of test input and the execution of test case can be finished automatically, but test result needs to be a kind of sampling method for test cases in clusters under the scene of artificial comparison.
Background technology
Traditional method for testing software comprises three steps: 1) create the test input; 2) implementation of test cases; 3) checkout result.Software test need expend a large amount of time and manpower, but it is an important means of guaranteeing software quality.In order to save testing cost, the researchist has designed some automatic tools and has helped generate test input, implementation of test cases and checkout result.Yet in manipulation type test (as the beta test, the field test), the test result variation can't be described clearly in advance accurately, therefore need manually go checking, thereby expend great amount of manpower.
Can finish automatically at the generation of this test input and the execution of test case, but test result needs the situation of artificial checking, people such as David Leon have proposed the software testing technology (Observation-Based Testing) based on observation, comprise three steps: 1) test input well for all test case creation; 2) carry out all test cases, and note the execution route of each test case; 3) analyze the execution path information of each test case, select test case and allow its test result of hand inspection whether meet demand.Therefore, be to need the test case number of hand inspection to save manpower based on the software testing technology of observing, but choose maximum failure use-cases simultaneously as far as possible to keep the validity of test by minimizing.
Calendar year 2001, humans such as William Dickinson have proved that by experiment the cluster filtering technique is a kind of effectively based on the software testing technology of observation, mainly comprises following three steps:
1. move all test cases, note execution path information.
2. the execution route according to test case comes cluster, and the test case that has similar execution route like this will be by poly-in same class bunch.
3. sampling from each class bunch, select test case has constituted the test use cases after the yojan.The tester only need verify these test cases and get final product.
Wherein the sampling method in the 3rd step can influence the effect of test use cases yojan significantly.Had the scholar to propose following several sampling methods:
1) one of random choose (One-per-cluster Sampling) from each class bunch: under optimal situation, the failure test case that the same program mistake causes is all gathered in same class bunch.Find out all program errors, only need get final product from test case of random choose each class bunch.But in fact the effect of cluster can not be so good, may mix the failure test case that successful test case and different program errors cause in class bunch.In addition, a failure test case that only causes according to this mistake, the programmer is difficult to carry out location of mistake.Therefore, the target of sampling is to find out maximum failure test cases as far as possible.
2) random choose a plurality of (N-per-cluster Sampling) from each class bunch: this method is intended to find out more failure use-case by selecting more test case.But this method is the simple extension of " random choose is from each class bunch " just, and they all are simple random sampling in essence, do not utilize any information to come guide sampling.
3) adaptive sampling (Adaptive Sampling): test case of random choose from each class bunch at first, then the execution result of all these test cases is verified.If a test case has been failed, then the residue of all in its place class bunch test cases all can selectedly come out to verify; Otherwise, the success of this test case, then all residue test cases all are filtered in its place class bunch.People such as William Dickinson prove that by experiment this self-adaptation selection method is more effective than above two kinds of simple random samplings.Under the equirotal situation of yojan collection, this method can be picked out more failure test case.Yet the effect of this adaptive sampling technology depends on the test case that the first time, random choose went out to a great extent.If the test case that random choose goes out from a class bunch checking result is failure, so whole class bunch all can be selected, even successful test case has accounted for major part in such bunch; Equally, if the test case that random choose goes out from a class bunch checking result be successfully, so whole class bunch all can be abandoned, even the test case of failing in such bunch has accounted for major part.
Summary of the invention
Technical matters to be solved by this invention is: existing software testing technology based on observation is comprehensive inadequately on test result is checked, need to improve existing " adaptive sampling " technology, the execution spectrum information that makes full use of test case selected in each class bunch helps select test case, and when decision stops sampling from such bunch.
Technical scheme of the present invention is: a kind of sampling method for test cases in clusters, after the test case of software test is carried out, obtain a plurality of classes bunch according to the execution route cluster of test case, selecting test case in class bunch verifies, according to the checking result of selected test case, calculate the confidence level of its performed statement, if the test case checking is passed through, the statement confidence level increases, otherwise then reduces; If a statement is with a low credibility in given threshold value, then this statement is suspicious statement, and suspicious statement constitutes suspicious statement set; Calculate the possibility of remaining each test case failure in such bunch according to suspicious statement set, it is high more that certain test case was carried out its failure possibility of how suspicious more statement, select that the highest test case of failure possibility, recomputate the confidence level of each statement then according to the checking result of this test case, upgrade suspicious statement set, and calculate the possibility of not verified residue test case failure, select the highest test case of next failure possibility and verify its result; Whole sampling process so repeats down, the failure possibility of all residue test cases all is 0 in such bunch, the performed statement that promptly remains test case is not all in suspicious statement set, the remaining test case of taking a sample is all no longer verified its result, and about degeneracy of realization test case is guaranteed the ratio of failure test case in the sampled test case.
Concrete steps of the present invention are as follows:
1) obtains m class bunch C after establishing cluster
1, C
2... C
m, j representation class bunch numbering, initialization j=1;
2) confidence level of all statements of initialization is 0; From class bunch C
iIn select the maximum test case t of perform statement;
3) verification test cases: the execution result of tester's verification test cases t, obtain feedback information: this test case is failure, still success;
4) calculate the perform statement confidence level: according to the checking result of test case t, the confidence level of computing statement, the formula of computing statement confidence level is confidence (s)=passed (s)-failed (s), be that the confidence level of statement s equals to carry out s and the number of the test case passed through, deduct the test case number of carrying out s and failure, if t authentication failed just, then the confidence level of all statements of carrying out of t subtracts 1; Otherwise, t success, then the confidence level of all statements of carrying out of t adds 1;
5) statement identification: according to the confidence level of statement, statement is identified as two kinds of suspicious statement and credible statements, set a threshold value ConfidenceThreshold, be abbreviated as CT, all confidence levels are identified as suspicious statement less than the statement of CT, and concrete formula is suspicious (S)={ s ∈ S|confidence (s)＜CT}; All confidence levels are identified as credible statement more than or equal to the statement of CT, and concrete formula is correct (S)={ s ∈ S|confidence (s)＞=CT}; Do not occur simultaneously between suspicious statement collection and the credible statement collection
6) test case failure possibility tolerance: the statement set representations that test case t carried out is t (S)={ s ∈ S|t executes s}, the possibility of test case t failure is the number of its suspicious statement of carrying out, computing formula be failpossibility (t)=| t (S) ∩ suspicious (S) |;
7) choose the test case of failure possibility maximum in the class bunch residue test case:, choose the test case t ' of the possibility maximum of wherein failing according to the failure possibility of the residue test case of calculating; If a plurality of test cases have maximum failure possibility, then adopt the method for random choose, select a test case t ';
8) if the failure possibility value of t ' is 0, then stop from class bunch C
jIn sampling, j=j+1, if j＜=m would return step 2), begin sampling from next class bunch; If j＞m, after promptly all classes bunch were all taken a sample and to be finished, whole sampling process finished; If the failure possibility value of t ' is then returned step 3) greater than 0, continue sampling from current class bunch.
The present invention is based on the cluster filtering technique in the software testing technology of observation, be a kind of test case cluster sampling technology.The present invention needs the test case number of artificial checking to save manpower by yojan, guarantees to pick out failure test case as much as possible simultaneously.During sampling verifying software test result, the present invention's remaining test case of taking a sample is all no longer verified its result, realized the yojan of test case, saved artificial validation test result's time and efforts, guarantee again simultaneously that the failure test case accounts for significant proportion in the sampled test case, the confidence value of statement can be carried out location of mistake with helping the tester.
Description of drawings
Fig. 1 is a schematic flow sheet of the present invention.
Fig. 2 (a) is 3-per-cluster sampling, adaptive sampling and ESBS of the present invention experiment effect figure on experimental arrangement PrintTokens.
Fig. 2 (b) is 3-per-cluster sampling, adaptive sampling and ESBS of the present invention experiment effect figure on experimental arrangement PrintTokens2.
Fig. 2 (c) is 3-per-cluster sampling, adaptive sampling and ESBS of the present invention experiment effect figure on experimental arrangement Schedule.
Fig. 2 (d) is 3-per-cluster sampling, adaptive sampling and ESBS of the present invention experiment effect figure on experimental arrangement Schedule2.
Fig. 2 (e) is 3-per-cluster sampling, adaptive sampling and ESBS of the present invention experiment effect figure on experimental arrangement Replace.
Fig. 2 (f) is 3-per-cluster sampling, adaptive sampling and ESBS of the present invention experiment effect figure on experimental arrangement Space.
Embodiment
The present invention is based on the cluster filtering technique in the software testing technology of observation, in class bunch, select test case and verify, according to the checking result of selected test case, calculate the confidence level of its performed statement, if the test case checking is passed through, statement is credible, otherwise then is suspicious; Calculate the possibility of remaining each test case failure in such bunch according to the statement confidence level, it is high more that certain test case was carried out its failure possibility of how suspicious more statement, select that the highest test case of failure possibility, recomputate the confidence level of each statement then according to the checking result of this test case, and calculate the possibility of not verified residue test case failure, select next test case; Whole sampling process so repeats down, the failure possibility of all residue test cases all is 0 in such bunch, the performed statement that promptly remains test case is credible, then distinguish by the checking result and be successfully that test case still is the failure test case through the test case of sampling checking, the remaining test case of taking a sample is successfully test case, realizes the automatic sampling of such bunch test case.
By or the statement of the test case of failure carry out information and be called as " execution frequency spectrum " in the location of mistake field, because the present invention is based on the execution spectrum information that is verified test case and selects the residue test case, so can be called based on the sampling method Execution Spectra Based Sampling that carries out frequency spectrum, be subsequently abbreviated as ESBS.
As Fig. 1, step of the present invention is as follows:
1) obtains m class bunch C after establishing cluster
1, C
2... C
m, j representation class bunch numbering, initialization j=1;
2) confidence level of all statements of initialization is 0; From class bunch C
jIn select the maximum test case t of perform statement
3) verification test cases: the execution result of tester's verification test cases t, obtain feedback information: this test case is failure, still success;
4) calculate the perform statement confidence level: according to the checking result of test case t, the confidence level of computing statement, the formula of computing statement confidence level is confidence (s)=passed (s)-failed (s), be that the confidence level of statement s equals to carry out s and the number of the test case passed through, deduct the test case number of carrying out s and failure, if t authentication failed just, then the confidence level of all statements of carrying out of t subtracts 1; Otherwise, t success, then the confidence level of all statements of carrying out of t adds 1;
5) statement identification: according to the confidence level of statement, statement is identified as two kinds of suspicious statement and credible statements, set a threshold value ConfidenceThreshold, be abbreviated as CT, all confidence levels are identified as suspicious statement less than the statement of CT, and concrete formula is suspicious (S)={ s ∈ S|confidence (s)＜CT}; All confidence levels are identified as credible statement more than or equal to the statement of CT, and concrete formula is correct (S)={ s ∈ S|confidence (s)＞=CT}; Do not occur simultaneously between suspicious statement collection and the credible statement collection
6) test case failure possibility tolerance: the statement set representations that test case t carried out is t (S)={ s ∈ S|t executes s}, the possibility of test case t failure is the number of its suspicious statement of carrying out, computing formula be failpossibility (t)=| t (S) ∩ suspicious (S) |;
7) choose the test case of failure possibility maximum in the class bunch residue test case:, choose the test case t ' of the possibility maximum of wherein failing according to the failure possibility of the residue test case of calculating; If a plurality of test cases have maximum failure possibility, then adopt the method for random choose, select a test case t ';
8) if the failure possibility value of t ' is 0, then stop from class bunch C
jIn sampling, j=j+1, if j＜=m would return step 2), begin sampling from next class bunch; If j＞m, after promptly all classes bunch were all taken a sample and to be finished, whole sampling process finished.If the failure possibility value of t ' is then returned step 3) greater than 0, continue sampling from current class bunch.
All not sampled test cases of coming out need not be verified its result, have so just realized labor-saving purpose.Simultaneously, the confidence value of statement can be used for helper person and carries out location of mistake.
Below in conjunction with concrete instance, concrete enforcement of the present invention is described.Supposing has 6 test cases in the class bunch, statement that they were carried out and checking result in the future are as shown in table 1, wherein why be " checking result in the future ", be because the checking result of test case only picks out and verified just and know, but for the number percent of the failure test case of picking out is described, in table 1, listed all test cases checking result in the future in the example.We will therefrom select test case with the sampling method among the present invention and allow the tester verify now.Target is: pick out the least possible test case, but comprise failure test case as much as possible.It is concrete that to select process as shown in table 2.
1) just begin, the confidence level of all statements is initialized as 0.Because threshold value CT=1, the confidence level of all statements is all less than CT, and promptly all statements all are suspicious.Therefore, t2 is picked out by first, because it has carried out maximum suspicious statements, the possibility value of its failure is 5.
Shown in that row that order in the table 2 is 1, t2 checking back is for passing through, so the statement s1 that carried out of t2, s2, and s4, s5, the confidence level of s6 all adds 1, and at this moment, the confidence level of having only s3 is less than CT, and s3 is unique suspicious statement.In remaining 5 test cases, have only t3 and t5 to carry out s3, so they have identical failure possibility value 1.
2) shown in that row that order in the table 2 is 2, test case of random choose supposes that t3 is selected from t3 and t5, because t3 is verified as failure, and the statement s2 that t3 carried out, the confidence level of s3 subtracts 1, and the suspicious statement of this moment is s2 and s3.At remaining 4 test case t1, t4, t5, among the t6, t4 has carried out s2, and t5 has carried out s3, so they have identical failure possibility 1.
3) shown in that row that order in the table 2 is 3, test case of random choose supposes that t4 is selected from t4 and t5, because t4 is verified as failure, the statement s2 that t4 carried out, the confidence level of s5 subtracts 1, the suspicious statement of this moment is s2, s3, s5 is at remaining test case t1, t5, among the t6, have only t5 to carry out suspicious statement s3, t1 and t6 do not carry out any suspicious statement.Therefore have only t5 to have failure possibility 1.
4) shown in that row that order in the table 2 is 4, t5 is selected, because t5 is verified as by, the statement s1 that t5 carried out, s3, the confidence level of s4 adds 1, and the suspicious statement of this moment is s2, s3, s5, remaining test case t1, t6 do not carry out any suspicious statement, and the possibility of promptly failing value all is 0.Such bunch sampling finishes.
Sum up: have 6 test cases such as tables 1 in such bunch, we have selected wherein four test case: t2, t3, t4, t5 sees Table 2, allows the tester verify its result, (t1 t6) does not verify its result to two other test case, has saved tester's validation test result's time like this.(t3, t4), the test case of these 2 failures is all selected in table 2 has come out to have the test case of 2 failures in the table 1.That is to say that test case only verifying under the situation of 4/6 test case, found the test case of 100% failure, both saved the time, do not influence the test effect again.
Statement that carried out six test cases of table 1 and they and checking result in the future
| Test case | The statement of carrying out | Checking result in the future |
| ??t1 | ??s1，s4，s6 | By |
| ??t2 | ??s1，s2，s4，s5，s6 | By |
| ??t3 | ??s2，s3 | Failure |
| ??t4 | ??s2，s5 | Failure |
| ??t5 | ??s1，s3，s4 | By |
| ??t6 | ??s1，s6 | By |
Table 2 is based on the process of specifically selecting of table 1 test case
As Fig. 2 (a)-(d), we operate in existing two kinds of cluster sampling technology 3-per-cluster sampling (getting 3 samples in each bunch at random) and adaptive sampling (adaptive sampling) and ESBS of the present invention (based on the cluster sampling technology of carrying out frequency spectrum) on Siemens's experimental arrangement of 6 classics.Among each figure, the selected test case number that comes out to verify of horizontal ordinate representative accounts for the number percent (%tests selected) of original test case number, and the failure test case number that the ordinate representative is selected accounts for the number percent (%failures found) of original failure test case number.Under the identical situation of the selected test case number that comes out, the failure test case number that finds is many more, illustrates that this sampling technique effect is good more.Promptly under the identical situation of abscissa value, the vertical tabular value of sitting is big more, and this sampling technique is good more.As can be seen from the figure, ESBS method of the present invention is at Printtokens, Printtokens, Schedule2, Replace, the effect of Space on 5 experimental arrangements is all significantly better than 3-per-cluster sampling and adaptive sampling, and only the effect on Schedule is not as good as adaptivesampling.Find after searching reason that the effect of ESBS of the present invention depends on the effect of location of mistake to a great extent, and the mistake in the Schedule program is not easy the location, thereby has influenced the effect that test case is selected.
Claims (2)
1. sampling method for test cases in clusters, after the test case of software test is carried out, obtain a plurality of classes bunch according to the execution route cluster of test case, it is characterized in that selecting test case in class bunch verifies, according to the checking result of selected test case, calculate the confidence level of its performed statement, if the test case checking is passed through, the statement confidence level increases, otherwise then reduces; If a statement is with a low credibility in given threshold value, then this statement is suspicious statement, and suspicious statement constitutes suspicious statement set; Calculate the possibility of remaining each test case failure in such bunch according to suspicious statement set, it is high more that certain test case was carried out its failure possibility of how suspicious more statement, select that the highest test case of failure possibility, recomputate the confidence level of each statement then according to the checking result of this test case, upgrade suspicious statement set, and calculate the possibility of not verified residue test case failure, select the highest test case of next failure possibility and verify its result; Whole sampling process so repeats down, the failure possibility of all residue test cases all is 0 in such bunch, the performed statement that promptly remains test case is not all in suspicious statement set, the remaining test case of taking a sample is all no longer verified its result, and about degeneracy of realization test case is guaranteed the ratio of failure test case in the sampled test case.
2. a kind of sampling method for test cases in clusters according to claim 1 is characterized in that concrete steps are as follows:
1) obtains m class bunch C after establishing cluster
1, C
2... C
m, j representation class bunch numbering, initialization j=1;
2) confidence level of all statements of initialization is 0; From class bunch C
jIn select the maximum test case t of perform statement;
3) verification test cases: the execution result of tester's verification test cases t, obtain feedback information: this test case is failure, still success;
4) calculate the perform statement confidence level: according to the checking result of test case t, the confidence level of computing statement, the formula of computing statement confidence level is confidence (s)=passed (s)-failed (s), be that the confidence level of statement s equals to carry out s and the number of the test case passed through, deduct the test case number of carrying out s and failure, if t authentication failed just, then the confidence level of all statements of carrying out of t subtracts 1; Otherwise, t success, then the confidence level of all statements of carrying out of t adds 1;
5) statement identification: according to the confidence level of statement, statement is identified as two kinds of suspicious statement and credible statements, set a threshold value ConfidenceThreshold, be abbreviated as CT, all confidence levels are identified as suspicious statement less than the statement of CT, and concrete formula is suspicious (S)={ s ∈ S|confidence (s)＜CT}; All confidence levels are identified as credible statement more than or equal to the statement of CT, and concrete formula is correct (S)={ s ∈ S|confidence (s)＞=CT}; Do not occur simultaneously between suspicious statement collection and the credible statement collection
6) test case failure possibility tolerance: the statement set representations that test case t carried out is t (S)={ s ∈ S|t executes s}, the possibility of test case t failure is the number of its suspicious statement of carrying out, computing formula be failpossibility (t)=| t (S) ∩ suspicious (S) |;
7) choose the test case of failure possibility maximum in the class bunch residue test case:, choose the test case t ' of the possibility maximum of wherein failing according to the failure possibility of the residue test case of calculating; If a plurality of test cases have maximum failure possibility, then adopt the method for random choose, select a test case t ';
8) if the failure possibility value of t ' is 0, then stop from class bunch Cj, to take a sample, j=j+1, if j＜=m would return step 2), begin sampling from next class bunch; If j＞m, after promptly all classes bunch were all taken a sample and to be finished, whole sampling process finished; If the failure possibility value of t ' is then returned step 3) greater than 0, continue sampling from current class bunch.
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| CN102193864B (en) * | 2011-05-13 | 2014-02-26 | 南京大学 | Test case set optimization method of coverage-based error positioning technology |
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| CN102253889B (en) * | 2011-08-07 | 2014-02-26 | 南京大学 | Method for dividing priorities of test cases in regression test based on distribution |
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| CN102521131A (en) * | 2011-12-13 | 2012-06-27 | 南京大学 | Defect positioning test case reduction method based on dynamic basic block |
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| CN102831055B (en) * | 2012-07-05 | 2015-04-29 | 陈振宇 | Test case selection method based on weighting attribute |
| CN103744789A (en) * | 2014-01-23 | 2014-04-23 | 中国科学院软件研究所 | Method of locating software errors by 3D surface representation |
| CN103744789B (en) * | 2014-01-23 | 2017-01-11 | 中国科学院软件研究所 | Method of locating software errors by 3D surface representation |
| CN104050083A (en) * | 2014-06-17 | 2014-09-17 | 南京大学 | Condition/Decision-coverage-oriented test data automatic generation method |
| CN104050083B (en) * | 2014-06-17 | 2017-05-03 | 南京大学 | Condition/Decision-coverage-oriented test data automatic generation method |
| CN104090837B (en) * | 2014-06-19 | 2018-02-09 | 苏州市职业大学 | The method for generating test case |
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| CN106776208B (en) * | 2016-12-02 | 2018-08-31 | 中国航天系统科学与工程研究院 | Fault Locating Method when a kind of running software |
| CN112905443A (en) * | 2019-12-04 | 2021-06-04 | 阿里巴巴集团控股有限公司 | Test case generation method, device and storage medium |
| CN114880242A (en) * | 2022-06-08 | 2022-08-09 | 北京百度网讯科技有限公司 | Test case extraction method, device, equipment and medium |
| CN114880242B (en) * | 2022-06-08 | 2023-01-13 | 北京百度网讯科技有限公司 | Test case extraction method, device, equipment and medium |
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