A Safe, Efficient Algorithm for Regression Test Selection

Abstract

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.


Related research categories:
(1) Regression Testing
(2) Testing

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