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...

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.

After changes are made to a previously tested program, a goal of regression testing is to perform retesting based on the modifications while maintaining the same testing coverage as completely retesting the program. We present a novel approach to data flow based regression testing that uses slicing algorithms to explicitly detect definition-use associations that are affected by a program change. An important benefit of our slicing technique is that, unlike previous techniques, neither data flow history nor recomputation of data flow for the entire program is required to detect affected definition-use associations. The program changes drive the recomputation of the required partial data flow through slicing. Another advantage is that our technique achieves the same testing coverage with respect to the affected definition-use associations as a complete retest of the program without maintaining a test suite. Thus, the overhead of maintaining and updating a test suite is eliminated. 1. Int...

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.

The purpose of regression testing is to ensure that bug fixes and new functionality introduced in a new version of a software do not adversely affect the correct functionality inherited from the previous version. This paper explores efficient methods of selecting small subsets of regression test sets that may be used to establish the same.

The dependencies that exist among definitions and uses of variables in a program are required by many language-processing tools. This paper considers the computation of definition-use and use-definition chains that extend across procedure boundaries at call and return sites. Intraprocedural definition and use information is abstracted for each procedure and is used to construct an interprocedural flow graph. This intraprocedural data-flow information is then propagated throughout the program via the interprocedural flow graph to obtain sets of reaching deilnitions and/or reachable uses for each interprocedural control point, including procedure entry, exit, call, and return. Interprocedural definition-use and/or use-definition chains are computed from this reaching information. The technique handles the interprocedural effects of the data flow caused by both reference parameters and global variables, while preserving the calling context of called procedures. Additionally, recursion, aliasing, and separate compilation are handled. The technique has been implemented using a Sun-4 Workstation and incorporated into an interprocedural data-flow tester. Results from experiments indicate the practicality of the technique, both

The purpose of regression testing is to ensure that changes made to software, such as adding new features or modifying existing features, have not adversely affected features of the software that should not change. Regression testing is usually performed by running some, or all, of the test cases created to test modifications in previous versions of the software. Many techniques have been reported on how to select regression tests so that the number of test cases does not grow too large as the software evolves. Our proposed hybrid technique combines modification, minimization and prioritization-based selection using a list of source code changes and the execution traces from test cases run on previous versions. This technique seeks to identify a representative subset of all test cases that may result in different output behavior on the new software version. We report our experience with a tool called ATAC which implements this technique. Keywords: Regression Testing, Modification-Based Test Selection, Test Set Minimization, Test Set Prioritization 1

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...