Omar M. Villanueva
Leonardo Trujillo
ABSTRACT
Genetic Improvement (GI) focuses on the development of evolutionary methods to automate software engineering tasks, such as performance improvement or software bugs removal. Concerning the latter, one of the earliest and most well-known methods in this area is the Genetic Program Repair (GenProg), a variant of Genetic Programming (GP). However, most GI systems encounter problems that are derived from the fact that they operate directly at source code level. These problems include highly neutral fitness landscapes and loss of diversity during the search, which are always undesirable in search and optimization tasks. This paper explores the use of Novelty Search (NS) with GenProg, since it can allow a search process to overcome these type of issues. While NS has been combined with GP before, and recently used with other GI systems, in the area of automatic bug repair NS has not been used until this work. Results show that GenProg with NS outperforms the original algorithm in some cases, based on an extensive experimental evaluation.
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Index Terms
- Novelty search for automatic bug repair
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