Empirical Evaluation of a Nesting Testability Transformation for Evolutionary Testing

Phil McMinn, David Binkley, Mark Harman

Research output: Contribution to journalArticlepeer-review

47 Citations (Scopus)

Abstract

Evolutionary testing is an approach to automating test data generation that uses an evolutionary algorithm to search a test object's input domain for test data. Nested predicates can cause problems for evolutionary testing, because information needed for guiding the search only becomes available as each nested conditional is satisfied. This means that the search process can overfit to early information, making it harder, and sometimes near impossible, to satisfy constraints that only become apparent later in the search. The article presents a testability transformation that allows the evaluation of all nested conditionals at once. Two empirical studies are presented. The first study shows that the form of nesting handled is prevalent in practice. The second study shows how the approach improves evolutionary test data generation.
Original languageEnglish
Article number11
JournalACM TRANSACTIONS ON SOFTWARE ENGINEERING AND METHODOLOGY
Volume18
Issue number3
Publication statusPublished - 1 May 2009

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