Abstract-Regression testing is a necessary but expensive maintenance activity aimed at showing that code has not been adversely affected by changes. Regression test selection techniques reuse tests from an existing test suite to test a modified program. Many regression test selection techniques have been proposed; however, it is difficult to compare and evaluate these techniques because they have different goals. This paper outlines the issues relevant to regression test selection techniques, and uses these issues as the basis for a framework within which to evaluate the techniques. We illustrate the application of our framework by using it to evaluate existing regression test selection techniques. The evaluation reveals the strengths and weaknesses of existing techniques, and highlights some problems that future work in this area should address. Index Terms-Software maintenance, regression testing, selective retest, regression test selection. 1

Regression testing is an expensive but necessary maintenance activity performed on modified software to provide confidence that changes are correct and do not adversely affect other portions of the software. A regression test selection technique chooses, from an existing test set, tests that are deemed necessary to validate modified software. We present a new technique for regression test selection. Our algorithms construct control flow graphs for a procedure or program and its modified version, and use these graphs to select tests that execute changed code from the original test suite. We prove that under certain conditions, the set of tests our technique selects includes every test from the original test suite that can expose faults in the modified procedure or program. Under these conditions our algorithms are safe. Moreover, although our algorithms may select some tests that cannot expose faults, they are at least as precise as other safe regression test selection algorith...

This paper presents a technique to select a representative set of test cases from a test suite that provides the same coverage as the entu-e test suite This selectlon m performed by ldentlfymg, and then ehmmating, the redundant and obsolete test cases in the test suite. The representatl ~ e set replaces the orgznal test mute and thus, potential y produces a smaller test suite The representative set can also be used to identify those test cases that should be rerun to test the program after it has been changed. Our techmque us independent of the testing methodology and only requu-es an association between a testing requirement and the test cases tb at satisfy the requirement We i] lustrate the technique using the data flow testing methodology. The reduction that is possible with our technique is illustrated by experimental results,

Regression testing is an expensive testing procedure utilized to validate modified software. Regression test selection techniques attempt to reduce the cost of regression testing by selecting a subset of a program’s existing test suite. Safe regression test selection techniques select subsets that, under certain well-defined conditions, exclude no tests (from the original test suite) that if executed would reveal faults in the modified software. Many regression test selection techniques, including several safe techniques, have been proposed, but few have been subjected to empirical validation. This paper reports empirical studies on a particular safe regression test selection technique, in which the technique is compared to the alternative regression testing strategy of running all tests. The results indicate that safe regression test selection can be cost-effective, but that its costs and benefits vary widely based on a number of factors. In particular, test suite design can significantly affect the effectiveness of test selection, and coverage-based test suites may provide test selection results superior to those provided by test suites that are not coverage-based.

Regression testing is the process of validating modified software to detect whether new errors have been introduced into previously tested code and to provide confidence that modifications are correct. Since regression testing is an expensive process, researchers have proposed regression test selection techniques as a way to reduce some of this expense. These techniques attempt to reduce costs by selecting and running only a subset of the test cases in a program's existing test suite. Although there have been some analytical and empirical evaluations of individual techniques, to our knowledge only one comparative study, focusing on one aspect of two of these techniques, has been reported in the literature. We conducted an experiment to examine the relative costs and benefits of several regression test selection techniques. The experiment examined ve techniques for reusing test cases, focusing on their relative abilities to reduce regression testing effort and uncover faults in modified programs. Our results highlight several differences between the techniques, and expose essential tradeoffs that should be considered when choosing a technique for practical application.

Software maintainers are faced with the task of regression testing: retesting a modified program on an often large number of test cases. The cost of regression testing can be reduced if the size of the program that must be retested is reduced and if old test cases and old test results can be reused. Tw o complimentary algorithms for reducing the cost of regression testing are presented. The first produces a program called differences that captures the semantic change between certified, apreviously tested program, and modified, achanged version of certified. Itis more efficient to test differences, because it omits unchanged computations. The program differences is computed using a combination of program slices. The second algorithm identifies test cases for which certified and modified will produce the same output and existing test cases that will test components new inmodified. Not rerunning test cases that produce the same output avoids unproductive testing; testing new components with existing test cases avoids the costly construction of new test cases. The second algorithm is based on the notion of common execution patterns, which is the interprocedural extension of the notion introduced by Bates and Horwitz. Program components with common execution patterns have the same execution pattern during some call to their procedure. They are computed using a new type of interprocedural slice called a calling context slice. Whereas an interprocedural slice includes the program components necessary to

Regression testing is applied to modified software to provide confidence that the changed parts behave as intended and that the unchanged parts have not been adversely affected by the modifications. To reduce the cost of regression testing, test cases are selected from the test suite that was used to test the original version of the software---this process is called regression test selection. A safe regressiontest -selection algorithm selects every test case in the test suite that may reveal a fault in the modified software. Safe regression-test-selection techniques can help to reduce the time required to perform regression testing because they select only a portion of the test suite for use in the testing but guarantee that the faults revealed by this subset will be the same as those revealed by running the entire test suite. This paper presents the first safe regression-test-selection technique that, based on the use of a suitable representation, handles the features of the Java language. Unlike other safe regression test selection techniques, the presented technique also handles incomplete programs. The technique can thus be safely applied in the (very common) case of Java software that uses external libraries or components

This paper presents an algorithm that reduces the cost of regression testing by reducing the number of test cases that must be re-run and by reducing the size of the program that they must be run on. The algorithm uses dependence graphs and program slicing to partition the components of the new program into two sets: preserved points---components that have unchanged run-time behavior; and affected points---components that have changed run-time behavior. Only test cases that test the behavior of affected points must be re-run; the behavior of the preserved points is guaranteed to be the same in the old and new versions of the program. Furthermore, the algorithm produces a program differences, which captures the behavior of (only) the affected points. Thus, rather than re-testing the (large) new program on a large number of test cases, it is possible to certify the new program by running the (smaller) program differences on a (smaller) number of test cases. CR Categories and Subject De...

Regression testing is performed on modified software to provide confidence that changed and affected portions of the code behave correctly. We present an approach to regression testing that handles two important tasks: selecting tests from the existing test suite that should be rerun, and identifying portions of the code that must be covered by tests. Both tasks are performed by traversing graphs for the program and its modified version. We first apply our technique to single procedures and then show how our technique is applied at the interprocedural level. Our approach has several advantages over previous work. First, our test selection technique is safe, selecting every test that may produce different output in the modified program. However, our selection technique chooses smaller test sets than other safe approaches. Second, our approach is the first safe approach to identify coverage requirements, and the first safe approach to do so interprocedurally. Third, our approach handles ...

Regression testing is a necessary but costly maintenance activity aimed at demonstrating that code has not been adversely affected by changes. A selective approach to regression testing selects tests for a modified program from an existing test suite. We present a new technique for selective regression testing. Our algorithm constructs control dependence graphs for program versions, and uses these graphs to determine which tests from the existing test suite may exhibit changed behavior on the new version. Unlike most previous techniques for selective retest, our algorithm selects every test from the original test suite that might expose errors in the modified program, and does this without prior knowledge of program modifications. Our algorithm handles all language constructs and program modifications, and is easily automated. 1 Introduction It has been estimated that software maintenance activities account for as much as two-thirds of the overall cost of software production[18]. One...