CN101916222A - Software testing method based on combination of control flow graph traversal and slice forward traversal - Google Patents

Software testing method based on combination of control flow graph traversal and slice forward traversal Download PDF

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CN101916222A
CN101916222A CN 201010247742 CN201010247742A CN101916222A CN 101916222 A CN101916222 A CN 101916222A CN 201010247742 CN201010247742 CN 201010247742 CN 201010247742 A CN201010247742 A CN 201010247742A CN 101916222 A CN101916222 A CN 101916222A
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CN101916222B (en
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李刚
高昕睿
高峰
刘厂
张振兴
沈志峰
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Harbin Ship Navigation Technology Co., Ltd.
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Harbin Engineering University
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Abstract

The invention provides a software testing method based on the combination of control flow graph traversal and slice forward traversal. The method improves the traversal strategy of the selective regression testing method based on control flow graph traversal, changes the definitions of variables in codes and introduces the slice forward traversal algorithm; and in the method, all the definition-use pairs vdefine-vuse which are affected directly or indirectly is identified, only the test case of the variable definition-use pairs are selected to traverse, thus avoiding the consumption of test time and effect caused by selecting all the test cases through one node. As the improvement of strategy and the introduction of algorithm only aim at the modification of variable definition and the deletion of code is not considered, the method disclosed by the invention can not influence the safety and increase the selection accuracy of test cases in a certain scope.

Description

Travel through the method for testing software that combines based on control flow graph traversal and slice forward
Technical field
What the present invention relates to is a kind of method for testing software.Be particularly related to a kind of selectivity regression test method of regression test technical field based on control flow graph traversal and the combination of slice forward ergodic algorithm.
Background technology
The generation that software test is accompanied by software produces, and in the early stage software development process, the implication of test is narrow, test is equal to " debugging ".Up to nineteen fifty-seven, software test just begins to come with the debugging difference, becomes a kind of activity of finding software defect.The research focus of software test both at home and abroad exists at present: software test procedure model, unit testing adequacy standard, regression test, embedded software test, object-oriented software test, software quality and complexity metric, the generation of automatic test data etc.Wherein, regression test is an important research direction in the software test field.
In regression test, often face the unit testing use-case and the very high member function of complexity of enormous amount, how to concentrate the selection test case or to design new test case from already present test case, thereby both guaranteed the regression tested quality, improve regression test efficient again, be the subject matter that regression test faces always.
At present, had several selectivity regression test methods, in this field, the quality of method of testing is mainly weighed by security and degree of accuracy, and security and degree of accuracy are defined as follows:
1. security
Suppose that M is a selectivity regression test method, security is to weigh M to select to revise the scope that discloses test case from test use cases T.We define security is program P ' and test use cases T according to a specific program P, modification, specific as follows:
Definition: suppose that T has comprised n test case and revised to disclose for program P and P ', suppose to select the m in these test cases individual, then M is as follows about the security of P, P ' and T:
M safety = m / n n ≠ 0 100 % n = 0
If M has selected all modifications to disclose test case definitely, we say that the M technology is safe so.If the superset that M has selected a known modification to disclose, then M also is safe.For example, if M has selected the test case of all modification traversals for controlled regression test, M is a safety so.
If M is safe, then M has selected in T each wrong test case that discloses, and if M is unsafe, then it may be ignored some and exposes wrong test case, in addition, we suppose M 1And M 2Be two selectivity regression test methods, if M 1Compare M 2Bigger security is arranged, then M 1Relative M 2The ability that bigger uncover mistakes is arranged.
2. degree of accuracy
Suppose that M is a selectivity regression test method, degree of accuracy is weighed M and is ignored the degree that non-modification discloses test case, and the definition degree of accuracy is according to a specific program P, the program P ' that is modified and test use cases T, and is specific as follows:
Definition: supposing to have comprised among the test use cases T n test case is that non-modification discloses, and supposes that M has ignored the test case of m wherein, and then M is as follows about the degree of accuracy of P, P ' and T:
M precision = m / n n ≠ 0 100 % n = 0
Similar to security, for M, P, P ' and T arbitrarily, go back the neither one algorithm and can determine the degree of accuracy of M, but about degree of accuracy, we still can access some useful conclusions about P, P ' and T.At first, we can come comparison selectivity regression test method M according to degree of accuracy 1And M 2Quality; Secondly, we can prove whether accurate M is, if the test case that M selects a non-modification to disclose, then M is coarse.
Degree of accuracy is of great practical value, because it has weighed the ability that a selectivity regression test method M avoids selecting some test cases, and these test cases can not produce different output results on P and P '.In general, compare selectivity regression test method, can discern which method execution test unnecessary still less according to degree of accuracy.
Document related to the present invention comprises:
[1]R.Gupta,M.J.Harrold,M.L.Soffa.An?Approach?to?Regression?Testing?UsingSlicing;
[2]H.Agrawal,J.Horgan,E.Krauser,S.London.Incremental?Regression?Testing;
[3]Gregg?Rothermel,Mary?Jean?Harrold.A?Safe,Efficient?Regression?Test?SelectionTechnique。
Next analyze three typical selectivity regression test methods, use above-mentioned framework to assess and analyze them, in order more clearly to set forth security and degree of accuracy, here describe with Fig. 1, all test cases in oval all are to revise traversal, remaining test case then is not, in Fig. 1, and T ' Modification-revealingDash area is to revise the test use cases that discloses, and be to revise to disclose because revise the concentrated a part of test case of the test case of traversal, and another part is not to revise to disclose.
Document [1] has proposed the selectivity regression test method based on data stream.
Security:
Only considered to use the modification relevant to (define-use) with variable-definition, so it may ignore some and revise the test case that discloses, for example the deletion of the function call code definition that do not relate to variable is used, and this method can not be selected any test case; Similarly, if a test case is carried out an output statement new or that revise, but does not comprise the use of variable in this statement, this method just can not be selected corresponding test case, even this statement is revised to disclose for P and P ', so data flow technique is incomplete.
Degree of accuracy:
1) only selects to carry out those that increase newly, that be modified or deleted variable-definitions and use right test case, so the test case of non-modification traversal has been ignored on data stream selectivity regression test technological model ground;
2) the data stream measuring technology selects definition that traversal increases newly, that revise or deletion to use right test case, data flow technique just may be ignored some test cases, this test case has reached a variable-definition that is modified, but but do not reach the use of this variable, these test cases are to revise traversal, but are that non-modification discloses.
3) data flow technique may neglect and revise the test case that discloses, for example, and when the deletion of code does not relate to the variable-definition use.
Document [2] has defined the employing program slicing technique and has realized selectivity regression tested method.Comprise and carry out section, Dynamic Slicing, relevant section and approximate four kinds of slice types of relevant section.
Security:
1) when having comprised the assertion statement of revising among the program P, the Dynamic Slicing technology may be ignored some and revise the test case that discloses, so this technology is unsafe; When the modification of code does not have the control flow graph of reprogramming P or increases new variable-definition, other microtomy is safe.
2) increase assertion statement or assignment statement will have a negative impact to the security of microtomy in program P, for example in P, increase a new assignment statement s, because the section that program slicing technique obtains only is included in the statement that appears at before the modification of program among the program P, the section of any test case can not comprise statement s.But in test procedure P ' time, any test case that can carry out the s statement all is to revise to disclose in T, but microtomy is not selected these test cases, so microtomy is unsafe.
Degree of accuracy:
It is non-structured revising when code, and does not have the increase of fresh code, and microtomy only selects to revise the test case of traversal.By restrictively selecting to influence the test case of program output, the Dynamic Slicing technology is to revise traversal rather than revise the test case that discloses with relevant microtomy having got rid of some in varying degrees.But comprise structurized change in program P ', this technology just may be selected the test case of non-modification traversal.
Document [3] has proposed one based on control flow graph traversal Technology Selection regression test method.
Security:
The control flow graph traversal choice of technology test case of all modification traversal, for controlled regression test, this technology is safe.
Degree of accuracy:
Control flow graph traversal technology be not 100% accurate.The control flow graph has a repeatedly accessed node (multiply-visited-node) characteristic, and when not containing this characteristic among program P and the P ', this technology has accurately selected to revise the test case of traversal simultaneously; When containing this characteristic among program P and the P ', this technology may have been selected the test case of some non-modification traversals.
Summary of the invention
The object of the present invention is to provide a kind of method for testing software that combines based on control flow graph traversal and slice forward traversal that guarantees security that regression test case is selected and degree of accuracy simultaneously.
The objective of the invention is to realize as follows:
A. create original program and amended programmed control flow graph G and G ' respectively,, set up the corresponding relation of itself and execution route each test case among the test use cases T before the regression test;
B. G and G ' are carried out the depth-first search traversal synchronously, compare the statement node that each traversal can arrive; For the change of variable-definition in the code, use the forward direction ergodic algorithm only to discern all variable-definitions that directly or indirectly are affected and use v Define~v Use, in T, select to traverse variable-definition and use right test case; For other node N and the inconsistent situation of statement morphology of N ' in the comparison procedure, in T, select all can reach the test case of this node;
C. list all suitable test cases of revising the back program of from T, selecting.
In the technique scheme, described step B further comprises:
B1. according to the variable that travels through the definition change that obtains among the step B, its variable-definition of initialization is used pair set, and writes down the node location at this statement place;
B2. continue traversal forward:
1), puts it into definition and use in the pair set if find in a statement, to use the value of the variable that traverses among the step B;
2) depend on the value of the variable that traverses among the step B if find the Variable Control of in a statement, using, put it into definition and use in the pair set;
3) if find in a statement, the variable that step B traversal obtains has a new definition, stops at the traversal on this path;
B3. the node location that returns step B1 record continues execution in step B.
The present invention is on the basis based on the selectivity regression test method of controlling flow graph traversal, in conjunction with the slice forward ergodic algorithm, a kind of improved selectivity regression test method has been proposed, make it in the advantage while that keeps based on the overall safety of the selectivity regression test method of controlling flow graph traversal, further change and improve the degree of accuracy that regression test case is selected.
The notable feature that method of the present invention is different from existing method is: for the change of the variable-definition that exists in the code, only need all variable-definitions that directly or indirectly are affected of identification to use v Define~v UseGet final product, and need not select all to pass through the test case of this variate-value definition.The variable-definition that directly is affected is used being meant the direct change mainly due to the variable-definition value, for example definition statement x=2 is directly changed into x=3, it is right that new definition use is not introduced in the code change, but it is right to test all definition uses that rely on variable x values again; The variable-definition use that is affected indirectly uses right variable-definition value to depend on reformed variate-value to being meant certain variable-definition, or certain variable-definition use depends on reformed variable to control.Select these variable-definitions of traversal to use right test case, promptly selected the test case of all modification traversals, thereby also guaranteed its security.
The beneficial effect of method of the present invention is mainly reflected in: among the present invention, traversal strategy based on the selectivity regression test method of controlling flow graph traversal is improved, change for variable-definition in the code, quote the slice forward ergodic algorithm, discern all variable-definitions that directly or indirectly are affected and use v Define~v Use, and only select to traverse these variable-definitions and use right test case, avoided selecting all test durations of causing by the test case of certain node and the consumption of effectiveness.Because improvement just at the modification of variable-definition, is not considered the deletion of code etc.,, and improved the degree of accuracy that test case is selected within the specific limits so method disclosed by the invention can not produce adverse influence to security.
Description of drawings
Fig. 1 is the test use cases graph of a relation;
Fig. 2 is the concrete implementing procedure figure of selectivity regression test method disclosed by the invention;
Fig. 3 is the regression test case collection figure that selectivity regression test method disclosed by the invention is selected.
Embodiment
For example the present invention is done description in more detail below in conjunction with accompanying drawing:
In conjunction with Fig. 2, mainly comprise following step:
Step 1: create original program and amended programmed control flow graph G and G ' respectively,, set up the corresponding relation of itself and execution route to each test case among the test use cases T before the regression test.
Step 2: G and G ' depth-first search are synchronously traveled through, compare the statement node that each traversal can arrive.Node for changing variable-definition skips to step 3; For the inconsistent situation of statement morphology of node N and N ' in the comparison procedure, in T, select all can reach the test case of this node.
Step 3: at first variable and the process variable to the use among the forward direction ergodic algorithm ForwardWalk (Pairs) describes:
Algorithm ForwardWalk (Pairs)
Input Pairs:(s i, v i) set of affected variable-definition, wherein s iBe variable v iThe statement of definition, v iBe variable.
Output ValueUseTriples:{ (s, u, v) }
Statement In[i], Out[i], kill, NewIn: the set of variable
Worklist, Cd[i], OldCd, Affected Preds: the set of statement
S: statement collection
V: original variable collection
U: reformed variables set
K, n: statement
I, x: node
DefsOfV[i]: (s, v) Ding Yi set
Pred (i), Succ (i): the forerunner of node i, descendant node in the programmed control flow graph
Def (i): the variable of statement i definition
Specific as follows:
For the node that changes variable-definition, pair set ValueUseTriples:{ is used in the initializing variable definition, and (s, u v) }, make
Figure BSA00000220544600061
Obtain among the set Pairs of affected variable-definition each (s, v) in depth-first search Work List Worklist=n of immediate successor node of s Depth-first+ Worklist.With all node n in Pairs not in the control flow graph iIn[n i] and Out[n i] be initialized as
Figure BSA00000220544600062
The In[s of node s in Pairs] be initialized as
Figure BSA00000220544600063
Out[s] be initialized as (s, v) }.For each statement node n ∈ G, In and Out set have comprised the variable that definition value is modified or influences, adopt a bi-values (d, p) expression, d is the position of variable, and p is the variable that is changed or influences, and the use of these variablees will be found in follow-up ergodic process, set In[n] be illustrated in that the use of variable is found Out[n before the node n] be illustrated in that the use of variable will be found after the node n.
Step 4: each node among the circular treatment Worklist, if
Figure BSA00000220544600071
Then algorithm stops, otherwise takes out first statement node n from Worklist, definition
Figure BSA00000220544600072
If NewIn ≠ In[n], In[n then]=NewIn,
1) if The statement of all k ∈ (OldCd-Cd (n)) ∩ Affected Preds then, set up formula (1), (2), (3), as follows:
In[n]=In[n]-{(k,v i)} (1)
AffectedPreds=AffectedPreds-{k} (2)
ValueUseTriples=ValueUseTriples-{(k,u,v)} (3)
For all (d, v) ∈ DefsOfV[k] definition right, formula (4) is set up, and is as follows:
ValueUseTriples=ValueUseTriples∪{(d,u,v)}?(4)
2) if statement n calculate and to have used (d, v) ∈ In[n] variable v, formula (5) is set up, and is as follows:
ValueUseTriples=ValueUseTriples∪{(d,n,v)}?(5)
If on this path, found the redetermination of variable v, then stop (d, the v) search on this path, and definition kill={ (x, Def (n)): (x, Def (n)) ∈ In[n] }, formula (6) is set up, and is as follows:
Out[n]=(In[n]-kill)∪{n,Def(n)} (6)
3) if statement n assert and used (d, v) ∈ In[n] variable v, formula (7) is set up, and is as follows:
ValueUseTriples=ValueUseTriples∪{(d,n,v)}?(7)
Calculate again and reach this assertion statement but not at In[n] in definition set, formula (8), (9), (10), (11) are set up, and be as follows:
DefsOfV[n]=BackwardWalk(n,{v})-In[n] (8)
In[n]=In[n]∪{(n,v i):(d,v i)∈DefOfV[n]} (9)
Out[n]=In[n] (10)
Affected?Preds=Affected?Preds∪{n} (11)
4) if statement n has defined a variable p, and
Figure BSA00000220544600081
Out[n then]=Out[n] ∪ { (n, Def (n)) };
5) otherwise Out[n]=In[n];
6) if
Figure BSA00000220544600082
The depth-first search of all descendant node x ∈ Succ (n) of n is added Work List Worklist=x Depth-first+ Worklist;
7) if
Figure BSA00000220544600083
Then algorithm stops, and returns ValueUseTriples, otherwise gets back to 1).
Step 5: in T, select the right test case of all variable-definitions uses in the traversal ValueUseTriples set;
Step 6: be back to the node location that variable-definition changes in the step 2, continue depth-first search traversal based on the control flow graph;
Step 7: traversal finishes, and lists all suitable test cases of revising the back program of selecting from T.
Below come by experiment comparative studies method disclosed by the invention with the degree of accuracy and the security of document [3] method, proved that method disclosed by the invention is guaranteeing that test case selects to have improved degree of accuracy under the situation of security, comparative result sees table 1 for details.
Table 1 document [3] method and method test case disclosed by the invention are selected the table of comparisons
Figure BSA00000220544600084
Figure BSA00000220544600091
Interpretation is summed up:
1) complexity when tested function is big more---and cyclomatic complexity and node number, as functions such as calcup, draw_ft, draw_feature and draw_sounding, their complexity is all very high.When only when function entrance changes variate-value, the raising that method disclosed by the invention can be by a relatively large margin is based on the degree of accuracy of control flow graph traversal technology.
2) when the complexity of tested function hour, the nested statement of function inside is less, perhaps be modified to such an extent that definition value exists when asserting use, as functions such as getdeg, kp_sub, putspace and get_text_cmds, method disclosed by the invention and the degree of accuracy basically identical of controlling the flow graph traversal technology.
3) the global variable value in tested function is modified, and in function, do not exist when quoting, as getcmds and get_chinese_cmds function, method disclosed by the invention can not selected any test case, and can select all test cases based on control flow graph traversal algorithm.
In sum, method disclosed by the invention can improve the degree of accuracy based on the algorithm of control flow graph traversal within the specific limits, as shown in Figure 3, because method disclosed by the invention is the modification at variable-definition, do not consider the deletion of code etc., so can not produce adverse influence to security.

Claims (2)

1. method for testing software that combines based on control flow graph traversal and slice forward traversal is characterized in that:
A. create original program and amended programmed control flow graph G and G ' respectively,, set up the corresponding relation of itself and execution route each test case among the test use cases T before the regression test;
B. G and G ' are carried out the depth-first search traversal synchronously, seek inconsistent node N of statement morphology and N ', for a change whether decision node N and N ' node of variable-definition; If then use the forward direction ergodic algorithm to discern all variable-definitions that directly or indirectly are affected and use to v Define~v Use, and right test case is used in the choice variable definition in T; If not, then directly in T, select all can reach the test case of this node;
C. list all suitable test cases of revising the back program of from T, selecting.
2. according to claim 1 based on controlling the method for testing software that flow graph traversal and slice forward traversal combines, it is characterized in that described step B further comprises:
B1. inconsistent node N of the statement morphology that searches out among the determining step B and N ', and judge whether the node of variable-definition for a change, if then carry out B2; If not, then continue G and G ' are carried out the depth-first search traversal synchronously, finish until traversal;
B2. according to the variable that travels through the definition change that obtains among the step B, its variable-definition of initialization is used pair set, and writes down the node location at this statement place;
B3. it is right, specific as follows to discern all variable-definitions that directly or indirectly are affected uses:
1), puts it into variable-definition and use in the pair set if find in a statement, to have used the value of the variable that traverses among the step B;
2) depend on the value of the variable that traverses among the step B if find the variable that in a statement, uses, put it into variable-definition and use in the pair set;
3) if find in a statement, the variable that step B traversal obtains has a new definition, puts it into variable-definition and uses in the pair set, and stop at traversal on this path;
B4. select to traverse among the T variable-definition and use right test case, continue G and G ' are carried out the depth-first search traversal synchronously, finish until traversal.
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Cited By (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103425581A (en) * 2013-08-12 2013-12-04 浪潮电子信息产业股份有限公司 Software testing method based on learning control model
CN103678097A (en) * 2012-09-05 2014-03-26 百度在线网络技术(北京)有限公司 Method and device for selecting regression test case
CN104391793A (en) * 2014-11-27 2015-03-04 中国联合网络通信集团有限公司 Generation method and device of test steps and scripts
CN104615535A (en) * 2015-01-29 2015-05-13 北方工业大学 Method and device for generating test case based on extended data flow model
CN104834603A (en) * 2015-05-26 2015-08-12 牟永敏 Regression-testing-oriented control flow change influence domain analyzing method and system
CN105247493A (en) * 2013-05-06 2016-01-13 微软技术许可有限责任公司 Identifying impacted tests from statically collected data
WO2017201853A1 (en) * 2016-05-26 2017-11-30 西安交通大学 Method for locating program regression fault using slicing model
CN109634862A (en) * 2018-12-12 2019-04-16 腾讯科技(深圳)有限公司 Application analysis method, device and storage medium
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CN115809203A (en) * 2023-02-07 2023-03-17 杭州罗莱迪思科技股份有限公司 Software test case dynamic nesting method, device and application thereof

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101329652A (en) * 2008-07-30 2008-12-24 中兴通讯股份有限公司 Regression test automatic system and method
CN101719095A (en) * 2009-12-30 2010-06-02 北京世纪高通科技有限公司 Method and device for managing regression testing

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101329652A (en) * 2008-07-30 2008-12-24 中兴通讯股份有限公司 Regression test automatic system and method
CN101719095A (en) * 2009-12-30 2010-06-02 北京世纪高通科技有限公司 Method and device for managing regression testing

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
《系统工程与电子技术》 20091231 鲍亮 BPEL静态流程切片技术研究 241-245 1-2 第31卷, 第1期 2 *
《计算机技术与发展》 20071231 陈永郑 基于程序切片技术的回归测试方法研究 113-116 1-2 第17卷, 第12期 2 *

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CN115809203B (en) * 2023-02-07 2023-04-25 杭州罗莱迪思科技股份有限公司 Dynamic nesting method and device for software test cases and application of dynamic nesting method and device

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