CN105117331A - Error-location-oriented coincidence correctness test case identification method and device - Google Patents
Error-location-oriented coincidence correctness test case identification method and device Download PDFInfo
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- CN105117331A CN105117331A CN201510505684.5A CN201510505684A CN105117331A CN 105117331 A CN105117331 A CN 105117331A CN 201510505684 A CN201510505684 A CN 201510505684A CN 105117331 A CN105117331 A CN 105117331A
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Abstract
The embodiment of the invention discloses an error-location-oriented coincidence correctness test case identification method and device. The method comprises the following steps: collecting the coverage characteristic information of each test case operation preset program in a test case set; taking an execution result obtained by that the preset program operates on each test case as a classification tag of each test case; according to the coverage characteristic information and the test case set which carries the classification tags, training a regression model to obtain a classification model; and according to the classification model, predicting correct test cases, screening the coincidence correctness test case in the correct test cases so as to improve the wrong position positioning efficiency of the test case.
Description
Technical field
The present invention relates to computer software debugging field, more particularly, relate to a kind of coincidence correctness test case recognition methods towards location of mistake and device.
Background technology
Current most of location of mistake method utilizes program coverage information, comes based on the statistical discrepancy of specific statistical model contrast and analysis program statement between correct test case and failure testing use-case the position that in deduction program, mistake may exist.In order to more effectively Wrong localization, researcher proposes multiple statistical model.This kind of statistical model utilize the coverage information of program statement and program correct/unsuccessfully perform the relevance Wrong localization of existence, they are generally carry out Wrong localization based on following two assumed conditions:
If 1, a program statement is performed by more failure testing use-cases, so this statement more may comprise mistake;
If 2, a program statement is performed by more correct test cases, so this statement may be more correct statement.
As can be seen from above-mentioned assumed condition, this kind of statistical model assumes that wrong statement and failure testing use-case also exist High relevancy, and that is when the statement of mistake is performed, program can produce the output of mistake.When this condition meets, this kind of statistical method can find out the position of mistake in program more effectively.But this hypothesis always can not meet in test process, the such as statement of mistake is performed but program does not produce error message.Researchist proposes a kind of PIE model to study three conditions that error message can be observed demand fulfillment:
1, mistake statement is performed;
2, mistake statement makes program produce the program state of mistake;
3, the program state of mistake is propagated and is had influence on the output of program.
Only have when these three conditions meet simultaneously, program could produce the output of mistake.But, as long as when any one is not satisfied in two conditions below, even if mistake statement has been performed, program still can produce correct output.Under this situation, test case covers wrong statement in the process of implementation, is but marked as correct test case.According to above-mentioned two assumed conditions, this class testing-case may reduce the suspicious degree of wrong statement, thus produces adverse influence to location of mistake technology.
Therefore, how improving the efficiency of test case Wrong localization position, is the problem needing now to solve.
Summary of the invention
The object of the present invention is to provide a kind of coincidence correctness test case recognition methods towards location of mistake and device, to improve the efficiency of test case Wrong localization position.
For achieving the above object, following technical scheme is embodiments provided:
Towards a coincidence correctness test case recognition methods for location of mistake, comprising:
Collecting test case concentrates each test case to run the Cover Characteristics information of pre-set programs;
Described each test case is run the tag along sort of execution result as described each test case of described pre-set programs;
According to described Cover Characteristics information and the test use cases carrying tag along sort, regression model is trained, obtains disaggregated model;
According to described disaggregated model, correct test case is predicted, filter out the coincidence correctness test case in described correct test case; Wherein, but described coincidence correctness test case is the test case performing wrong statement create correct output in program process.
Preferably, described in draw coincidence correctness test case after, also comprise:
Heavy label strategy is performed to described coincidence correctness test case.
Preferably, described in draw coincidence correctness test case after, also comprise:
Drop policy is performed to described coincidence correctness test case.
Preferably, described according to described disaggregated model, correct test case is predicted, filters out the coincidence correctness test case in described correct test case, comprising:
According to described disaggregated model, correct test case is predicted, show that described correct test case is the probability sorting of coincidence correctness test case;
According to the probability sorting that described correct test case is coincidence correctness test case, filter out the coincidence correctness test case in described correct test case.
Preferably, described regression model is logistic regression model.
Towards a coincidence correctness test case recognition device for location of mistake, comprising:
Collection module, concentrates each test case to run the Cover Characteristics information of pre-set programs for collecting test case;
Tag along sort arranges module, for described each test case being run the tag along sort of execution result as described each test case of described pre-set programs;
Training module, for according to described Cover Characteristics information and the test use cases carrying tag along sort, trains regression model, obtains disaggregated model;
Screening module, for according to described disaggregated model, predicts correct test case, filters out the coincidence correctness test case in described correct test case; Wherein, but described coincidence correctness test case is the test case performing wrong statement create correct output in program process.
Preferably, also comprise:
Heavy label module, for performing heavy label strategy to described coincidence correctness test case;
Preferably, also comprise:
Discard module, for performing drop policy to described coincidence correctness test case.
Preferably, described screening module comprises:
Probability sorting unit, for according to described disaggregated model, predicts correct test case, show that described correct test case is the probability sorting of coincidence correctness test case;
Screening unit, for being the probability sorting of coincidence correctness test case according to described correct test case, filters out the coincidence correctness test case in described correct test case.
Preferably, described regression model is logistic regression model.
Known by above scheme, a kind of coincidence correctness test case recognition methods towards location of mistake that the embodiment of the present invention provides and device, comprising: collect test case and concentrate each test case to run the Cover Characteristics information of pre-set programs; Described each test case is run the tag along sort of execution result as described each test case of described pre-set programs; According to described Cover Characteristics information and the test use cases carrying tag along sort, regression model is trained, obtains disaggregated model; According to described disaggregated model, correct test case is predicted, filter out the coincidence correctness test case in described correct test case, thus improve the efficiency of test case Wrong localization position.
Accompanying drawing explanation
In order to be illustrated more clearly in the embodiment of the present invention or technical scheme of the prior art, be briefly described to the accompanying drawing used required in embodiment or description of the prior art below, apparently, accompanying drawing in the following describes is only some embodiments of the present invention, for those of ordinary skill in the art, under the prerequisite not paying creative work, other accompanying drawing can also be obtained according to these accompanying drawings.
Fig. 1 is a kind of coincidence correctness test case recognition methods process flow diagram towards location of mistake disclosed in the embodiment of the present invention;
Fig. 2 is a kind of coincidence correctness test case recognition device structural representation towards location of mistake disclosed in the embodiment of the present invention.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, be clearly and completely described the technical scheme in the embodiment of the present invention, obviously, described embodiment is only the present invention's part embodiment, instead of whole embodiments.Based on the embodiment in the present invention, those of ordinary skill in the art, not making the every other embodiment obtained under creative work prerequisite, belong to the scope of protection of the invention.
The embodiment of the invention discloses a kind of coincidence correctness test case recognition methods towards location of mistake and device, to improve the efficiency of test case Wrong localization position.
See Fig. 1, a kind of coincidence correctness test case recognition methods towards location of mistake that the embodiment of the present invention provides, comprising:
S101, collection test case concentrate each test case to run the Cover Characteristics information of pre-set programs;
Concrete, collect the coverage information of test use cases in operational process, and extract the Cover Characteristics information of suitable coverage information as test use cases.
Concrete, coincidence correctness test case must cover error code in program process.These test cases are distributed in and can arrive on all Program paths of error code position.The angle performed from path, in order to the error code in arrival program, the branch of these test cases on execution route must meet certain value condition.Therefore, for the paths covering error code, the branch value of test case on execution route be distributed on this paths will show similar value characteristic, so the present embodiment extracts the Cover Characteristics information of branch's coverage information as wall scroll test case.
Concrete, suppose program P contains m branch <p
1, p
2..., p
m>, the present embodiment adopts following steps to collect the Cover Characteristics information of test case.
(1) branch relevant to mistake is extracted
Only can be covered by current correct test case owing to there are some branches in program P, whether very weak with the relevance of error code the execution of these branches is, if these will not affected classification results by the branch that current any failure testing use-case covers as the part of characteristic information, thus we adopt following rule-based filtering those and the incoherent branch of mistake, thus make the branch of reservation more can reflect the correlation properties of mistake.
Wherein, tps (t
j) represent test case t
jbranch's set of covering.As can be seen from formula (1), any one branch in RP is all at least covered by a test case of failure testing set of uses case Tr, and that is the execution of branch may have influence on infection and the propagation of error code.Conveniently follow-up discussion, the branch's set represented by RP is expressed as { rp
1, rp
2..., rp
w, w <=m.
(2) branch's Cover Characteristics information
When each test case in testing results set of uses case T on program P, for each branch rp in RP
j, we collect following information
with
be illustrated respectively in a test case t
jbranch rp during execution
jexecution result is genuine number of times and execution result is false number of times.Due to may circulation be there is in program execution, so it performs number of times may be greater than 1.Work as rp
jtrue or false perform and be not triggered, then corresponding value is 0.For any one test case t
j, its branch's Cover Characteristics can be expressed as follows:
S102, described each test case is run the tag along sort of execution result as described each test case of described pre-set programs;
When after the branch's Cover Characteristics information collecting all test cases, simultaneously using the execution result of every bar test case as class label, if execution result is correct, then class label is 0, otherwise is 1.
S103, according to described Cover Characteristics information and the test use cases carrying tag along sort, regression model is trained, obtains disaggregated model;
Concrete, described regression model is logistic regression model.
Concrete, the branch of the present embodiment all test cases in test set covers as characteristic information, trains and draw disaggregated model using the execution result of test case as class label to logistic regression model.
S104, according to described disaggregated model, correct test case to be predicted, filter out the coincidence correctness test case in described correct test case;
Wherein, but described coincidence correctness test case is the test case performing wrong statement create correct output in program process.
Concrete, coincidence correctness is that the tested use-case of wrong statement in program performs, but does not produce the output of mistake.Coincidence correctness test case to be a test case be coincidence is correct, and and if only if that it meets following two conditions simultaneously:
1, this test case performs the statement of mistake in program process;
2, this test case creates correct output.
Concrete, described according to described disaggregated model, correct test case is predicted, filters out the coincidence correctness test case in described correct test case, comprising:
According to described disaggregated model, correct test case is predicted, show that described correct test case is the probability sorting of coincidence correctness test case;
According to the probability sorting that described correct test case is coincidence correctness test case, filter out the coincidence correctness test case in described correct test case.
Concrete, when according to described disaggregated model, after correct test case is predicted, the possibility size for coincidence correctness test case in correct test case can be obtained, and sort by size.Finally, appropriate doubtful coincidence correctness test case is selected from big to small based on the possible coincidence correctness test case estimated.
A kind of coincidence correctness test case recognition methods towards location of mistake that the embodiment of the present invention provides, comprising: collect test case and concentrate each test case to run the Cover Characteristics information of pre-set programs; Described each test case is run the tag along sort of execution result as described each test case of described pre-set programs; According to described Cover Characteristics information and the test use cases carrying tag along sort, regression model is trained, obtains disaggregated model; According to described disaggregated model, correct test case is predicted, filter out the coincidence correctness test case in described correct test case, thus improve the efficiency of test case Wrong localization position.
Concrete, identify coincidence correctness test case rapidly in order to efficient, in the present invention, adopt logistic regression model.Logistic regression model belongs to probabilistic type non-linear regression, it be research two classify observations and some affect between a kind of multivariable technique of relation.After logistic regression model completes training, this model, when predicting new example generic, can calculate the probability that the example that makes new advances is a certain classification fast.Because its calculation cost is not high, easy to understand and realization, and there is good classifying quality, thus in classification problem, obtain extensive utilization.
The present embodiment, after the characteristic information obtaining all test cases in T and class label, is trained logistic regression model in this, as input, is obtained a disaggregated model, be designated as LG.Introduce below and identify coincidence correctness test case based on LG model.
First the present embodiment proposes a kind of coincidence correctness test case number estimating may exist in test set T, instructs follow-up selection quantity with this number.
The present invention utilizes the Cover Characteristics of test case and execution result to infer possible coincidence correctness test case number.First, for the suspicious angle value that each the executable statement e in program, computing statement e comprise error code, S (e) is designated as.Here we use Oichai measure formulas, because it shows more stable performance on Wrong localization.S (e) is defined as follows:
Symbol <a
np, a
nf, a
ep, a
ef> represents the test case quantity of satisfied corresponding subscript condition, wherein first subscript of each symbol represents that this statement is performed (e) by the test case of correspondence or is not performed (n), and second subscript represents that corresponding test case execution result is (f) of correct (p) or mistake.When the context of symbol can not indicate be for any bar statement time, we can add that " (e) " represents the correlation of statement e below at symbol.Such as, a
epe () expression performs statement e and result is correct test case number.
Suppose in single wrong version program, there is a wrong statement e
f.According to the definition of coincidence correctness test case, known a
ep(e
f) represent the number of actual coincidence correctness test case in the middle of test use cases.Due to wrong statement e
flocation-Unknown in a program, so be difficult to determine a
ep(e
f) value.But, easily can be met the statement e of following condition
*:
argmax
e'∈p{S(e')|a
ef(e')＝|T
f|}(3)
Statement e
*by T in all statements
fin all failure testing use-cases cover and the maximum statement of suspicious angle value S (e).Due to wrong statement e
fcorresponding a
efequal | T
f|, thus at least there is a statement and meet above-mentioned formula.But such statement e
*may exist multiple, due to e
*corresponding a
efalways equal | T
f|, and according to formula, because T
ffor known quantity, so the value of S (e) is only with a
efand a
eprelevant.Thus for the e meeting arbitrarily formula (3)
*, a of its correspondence
epalso always equal.Get an arbitrary e
*all can not have an impact to derivation result below.
According to formula (3), due to a
ep(e
f)=| T
f|, wherein statement e
fmay be one of candidate statement meeting formula (3), thus easily obtain S (e
*)>=S (e
f).Meanwhile, due to a
ep(e
*)=| T
f| so easily draw equation a
ef(e
*)=a
ef(e
f) also set up.Therefore, a can be derived
ep(e
*)≤a
ep(e
f).Proof procedure is as follows:
Due to a
ep(e
f) represent the number of actual coincidence correctness test case in the middle of test use cases, thus according to the e that formula (3) obtains
*corresponding a
ep(e
*) value be always less than or equal in esse coincidence correctness test case number in test use cases T.A
ep(e
*) value be designated as CCN.
Then, doubtful coincidence correctness test case is calculated based on disaggregated model LG and CCN.Conveniently describe, note count equals Ticc, the doubtful coincidence correctness test case quantity namely identified.Easily know time initial that count is 0.The present invention adopts following step to identify coincidence correctness test case:
(1) for T
pany one test case t, calculate LG (T=1) value, namely this test case is the probability of coincidence correctness test case.And formation ranking list RankPro that LG (T=1) is sorted from big to small.
(2) if count<CCN and RankPro are not empty, then test case maximum for probable value in RankPro is added Ticc, remove from RankPro simultaneously, and put count=count+1, continue step (2); Otherwise, perform step (3).
(3) Ticc is returned as the doubtful coincidence correctness test case identified.
Preferably, in another embodiment of the invention, described in draw coincidence correctness test case after, also comprise:
Heavy label strategy is performed to described coincidence correctness test case.
Preferably, in another embodiment of the invention, described in draw coincidence correctness test case after, also comprise:
Drop policy is performed to described coincidence correctness test case.
Concrete, in the present embodiment, after identifying doubtful coincidence correctness test case, propose two kinds of strategies and carry out respectively processing to verify the impact on location of mistake technology.
Concrete, first from correct test use cases T
pin have chosen and be no more than CCN test case and add in Ticc as doubtful coincidence correctness test case.For these test cases, the present invention adopts two kinds of different processing policies to verify its impact on location of mistake technical efficiency.
(1) drop policy: the coincidence correctness test case of identification removed in the middle of test use cases T, remaining test case is using the input as location of mistake technology.This strategy decreases available detecting information to a certain extent.When adopting this strategy, the T=Tf+Tp-Ticc after renewal.
(2) heavy label strategy: the coincidence correctness test case of identification is all labeled as failure testing use-case, and using the input of the test use cases after renewal as location of mistake technology.This strategy adds the quantity of failure testing use-case in the middle of test use cases, but may provide more misleading information thus.When adopting this strategy, the T=Tf+Tp+Ticc after renewal.
Utilize said method to upgrade and obtain test use cases T, when for location of mistake method, coincidence correctness test case can be alleviated on the impact of location of mistake result, and then improve the efficiency of location of mistake.
See Fig. 2, a kind of coincidence correctness test case recognition device towards location of mistake that the embodiment of the present invention provides, comprising:
Collection module 100, concentrates each test case to run the Cover Characteristics information of pre-set programs for collecting test case;
Tag along sort arranges module 200, for described each test case being run the tag along sort of execution result as described each test case of described pre-set programs;
Training module 300, for according to described Cover Characteristics information and the test use cases carrying tag along sort, trains regression model, obtains disaggregated model;
Screening module 400, for according to described disaggregated model, predicts correct test case, filters out the coincidence correctness test case in described correct test case; Wherein, but described coincidence correctness test case is the test case performing wrong statement create correct output in program process.
A kind of coincidence correctness test case recognition device towards location of mistake that the embodiment of the present invention provides, comprising: collect test case and concentrate each test case to run the Cover Characteristics information of pre-set programs; Described each test case is run the tag along sort of execution result as described each test case of described pre-set programs; According to described Cover Characteristics information and the test use cases carrying tag along sort, regression model is trained, obtains disaggregated model; According to described disaggregated model, correct test case is predicted, filter out the coincidence correctness test case in described correct test case, thus improve the efficiency of test case Wrong localization position.
Preferably, in another embodiment of the invention, also comprise:
Heavy label module, for performing heavy label strategy to described coincidence correctness test case.
Preferably, in another embodiment of the invention, also comprise:
Discard module, for performing drop policy to described coincidence correctness test case.
Preferably, in another embodiment of the invention, described screening module 400 comprises:
Probability sorting unit, for according to described disaggregated model, predicts correct test case, show that described correct test case is the probability sorting of coincidence correctness test case;
Screening unit, for being the probability sorting of coincidence correctness test case according to described correct test case, filters out the coincidence correctness test case in described correct test case.
Preferably, in another embodiment of the invention, described regression model is logistic regression model.
In this instructions, each embodiment adopts the mode of going forward one by one to describe, and what each embodiment stressed is the difference with other embodiments, between each embodiment identical similar portion mutually see.
To the above-mentioned explanation of the disclosed embodiments, professional and technical personnel in the field are realized or uses the present invention.To be apparent for those skilled in the art to the multiple amendment of these embodiments, General Principle as defined herein can without departing from the spirit or scope of the present invention, realize in other embodiments.Therefore, the present invention can not be restricted to these embodiments shown in this article, but will meet the widest scope consistent with principle disclosed herein and features of novelty.
Claims (10)
1., towards a coincidence correctness test case recognition methods for location of mistake, it is characterized in that, comprising:
Collecting test case concentrates each test case to run the Cover Characteristics information of pre-set programs;
Described each test case is run the tag along sort of execution result as described each test case of described pre-set programs;
According to described Cover Characteristics information and the test use cases carrying tag along sort, regression model is trained, obtains disaggregated model;
According to described disaggregated model, correct test case is predicted, filter out the coincidence correctness test case in described correct test case; Wherein, but described coincidence correctness test case is the test case performing wrong statement create correct output in program process.
2. coincidence correctness test case according to claim 1 recognition methods, is characterized in that, described in draw coincidence correctness test case after, also comprise:
Heavy label strategy is performed to described coincidence correctness test case.
3. coincidence correctness test case according to claim 1 recognition methods, is characterized in that, described in draw coincidence correctness test case after, also comprise:
Drop policy is performed to described coincidence correctness test case.
4. coincidence correctness test case according to claim 1 recognition methods, is characterized in that, described according to described disaggregated model, predicts correct test case, filters out the coincidence correctness test case in described correct test case, comprising:
According to described disaggregated model, correct test case is predicted, show that described correct test case is the probability sorting of coincidence correctness test case;
According to the probability sorting that described correct test case is coincidence correctness test case, filter out the coincidence correctness test case in described correct test case.
5., according to the coincidence correctness test case recognition methods in claim 1-4 described in any one, it is characterized in that, described regression model is logistic regression model.
6., towards a coincidence correctness test case recognition device for location of mistake, it is characterized in that, comprising:
Collection module, concentrates each test case to run the Cover Characteristics information of pre-set programs for collecting test case;
Tag along sort arranges module, for described each test case being run the tag along sort of execution result as described each test case of described pre-set programs;
Training module, for according to described Cover Characteristics information and the test use cases carrying tag along sort, trains regression model, obtains disaggregated model;
Screening module, for according to described disaggregated model, predicts correct test case, filters out the coincidence correctness test case in described correct test case; Wherein, but described coincidence correctness test case is the test case performing wrong statement create correct output in program process.
7. coincidence correctness test case recognition device according to claim 6, is characterized in that, also comprise:
Heavy label module, for performing heavy label strategy to described coincidence correctness test case.
8. coincidence correctness test case recognition device according to claim 6, is characterized in that, also comprise:
Discard module, for performing drop policy to described coincidence correctness test case.
9. coincidence correctness test case recognition device according to claim 6, it is characterized in that, described screening module comprises:
Probability sorting unit, for according to described disaggregated model, predicts correct test case, show that described correct test case is the probability sorting of coincidence correctness test case;
Screening unit, for being the probability sorting of coincidence correctness test case according to described correct test case, filters out the coincidence correctness test case in described correct test case.
10., according to the coincidence correctness test case recognition device in claim 6-9 described in any one, it is characterized in that, described regression model is logistic regression model.
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