You are required to read and agree to the below before accessing a full-text version of an article in the IDE article repository.

The full-text document you are about to access is subject to national and international copyright laws. In most cases (but not necessarily all) the consequence is that personal use is allowed given that the copyright owner is duly acknowledged and respected. All other use (typically) require an explicit permission (often in writing) by the copyright owner.

For the reports in this repository we specifically note that

  • the use of articles under IEEE copyright is governed by the IEEE copyright policy (available at http://www.ieee.org/web/publications/rights/copyrightpolicy.html)
  • the use of articles under ACM copyright is governed by the ACM copyright policy (available at http://www.acm.org/pubs/copyright_policy/)
  • technical reports and other articles issued by M‰lardalen University is free for personal use. For other use, the explicit consent of the authors is required
  • in other cases, please contact the copyright owner for detailed information

By accepting I agree to acknowledge and respect the rights of the copyright owner of the document I am about to access.

If you are in doubt, feel free to contact webmaster@ide.mdh.se

Search-based resource scheduling for bug fixing tasks

Fulltext:


Publication Type:

Conference/Workshop Paper

Venue:

The 2nd International Symposium on Search Based Software Engineering

DOI:

10.1109/SSBSE.2010.24


Abstract

Abstract—The software testing phase usually results in a large number of bugs to be fixed. The fixing of these bugs require executing certain activities (potentially concurrent) that demand resources having different competencies and workloads. Appropriate resource allocation to these bug-fixing activities can help a project manager to schedule capable resources to these activities, taking into account their availability and skill requirements for fixing different bugs. This paper presents a multi-objective search-based resource scheduling method for bug-fixing tasks. The inputs to our proposed method include i) a bug model, ii) a human resource model, iii) a capability matching method between bug-fixing activities and human resources and iv) objectives of bug-fixing. A genetic algorithm (GA) is used as a search algorithm and the output is a bug-fixing schedule, satisfying different constraints and value objectives. We have evaluated our proposed scheduling method on an industrial data set and have discussed three different scenarios. The results indicate that GA is able to effectively schedule resources by balancing different objectives. We have also compared the effectiveness of using GA with a simple hill-climbing algorithm. The comparison shows that GA is able to achieve statistically better fitness values than hill-climbing.

Bibtex

@inproceedings{Xiao3061,
author = {Junchao Xiao and Wasif Afzal},
title = {Search-based resource scheduling for bug fixing tasks},
month = {September},
year = {2010},
booktitle = {The 2nd International Symposium on Search Based Software Engineering},
url = {http://www.es.mdu.se/publications/3061-}
}