Abstract
Many software engineering tasks can potentially be automated using search heuristics. However, much work is needed in designing and evaluating search heuristics before this approach can be routinely applied to a software engineering problem. Experimental methodology should be complemented with theoretical analysis to achieve this goal. Recently, there have been significant theoretical advances in the runtime analysis of evolutionary algorithms (EAs) and other search heuristics in other problem domains. We suggest that these methods could be transferred and adapted to gain insight into the behaviour of search heuristics on software engineering problems while automating software engineering. © 2009 Higher Education Press and Springer-Verlag GmbH.
| Original language | English |
|---|---|
| Pages (from-to) | 64-72 |
| Number of pages | 9 |
| Journal | Frontiers of Computer Science in China |
| Volume | 3 |
| Issue number | 1 |
| Early online date | 26 Feb 2009 |
| DOIs | |
| Publication status | Published - Mar 2009 |
| Externally published | Yes |
Bibliographical note
The authors would like to thank Pietro Oliveto, Ramon Sagarna, Andrea Arcuri and the other members of the SEBASE project† for useful comments. This work was partially supported by EP-SRC (EP/C520696/1) and by the Royal Society under a grant in its UK-China Science Network programme.Keywords
- Evolutionary algorithms
- Runtime analysis
- Software engineering