Hybridizing Evolutionary Testing with the Chaining Approach

by Phil McMinn, and Mike Holcombe

Genetic and Evolutionary Computation Conference (GECCO 2004)


A more recent and expanded journal version of this paper is available — see "Evolutionary Testing Using an Extended Chaining Approach".


Fitness functions derived for certain white-box test goals can cause problems for Evolutionary Testing (ET), due to a lack of sufficient guidance to the required test data. Often this is because the search does not take into account data dependencies within the program, and the fact that some special intermediate statement (or statements) needs to have been executed in order for the target structure to be feasible. This paper proposes a solution which combines ET with the Chaining Approach. The Chaining Approach is a simple method which probes the data dependencies inherent to the test goal. By incorporating this facility ... [more]


Reference

Phil McMinn, and Mike Holcombe. Hybridizing Evolutionary Testing with the Chaining Approach. Genetic and Evolutionary Computation Conference (GECCO 2004), Lecture Notes in Computer Science, vol. 3103, pp. 1363–1374, 2004


Bibtex Entry
@inproceedings{McMinn2004,
  author    = "McMinn, Phil and Holcombe, Mike",
  title     = "Hybridizing Evolutionary Testing with the Chaining Approach",
  booktitle = "Genetic and Evolutionary Computation Conference (GECCO 2004)",
  series    = "Lecture Notes in Computer Science",
  volume    = "3103",
  pages     = "1363--1374",
  year      = "2004",
  publisher = "Springer"
}