Institutional Research Information Service
UCL Logo
Please report any queries concerning the funding data grouped in the sections named "Externally Awarded" or "Internally Disbursed" (shown on the profile page) to your Research Finance Administrator. Your can find your Research Finance Administrator at http://www.ucl.ac.uk/finance/research/post_award/post_award_contacts.php by entering your department
Please report any queries concerning the student data shown on the profile page to:

Email: portico-services@ucl.ac.uk

Help Desk: http://www.ucl.ac.uk/ras/portico/helpdesk
Publication Detail
Empirical evaluation of search based requirements interaction management
  • Publication Type:
    Journal article
  • Publication Sub Type:
    Conference Proceeding
  • Authors:
    Zhang Y, Harman M, Lim SL
  • Publication date:
  • Pagination:
    126, 152
  • Journal:
    Information and Software Technology
  • Volume:
  • Issue:
  • Status:
  • Print ISSN:
Context: Requirements optimization has been widely studied in the Search Based Software Engineering (SBSE) literature. However, previous approaches have not handled requirement interactions, such as the dependencies that may exist between requirements, and, or, precedence, cost- and value-based constraints. Objective: To introduce and evaluate a Multi-Objective Search Based Requirements Selection technique, using chromosome repair and to evaluate it on both synthetic and real world data sets, in order to assess its effectiveness and scalability. The paper extends and improves upon our previous conference paper on requirements interaction management. 1 Method: The popular multi-objective evolutionary algorithm NSGA-II was used to produce baseline data for each data set in order to determine how many solutions on the Pareto front fail to meet five different requirement interaction constraints. The results for this baseline data are compared to those obtained using the archive based approach previously studied and the repair based approach introduced in this paper. Results: The repair based approach was found to produce more solutions on the Pareto front and better convergence and diversity of results than the previously studied NSGA-II and archive-based NSGA-II approaches based on Kruskal-Wallis test in most cases. The repair based approach was also found to scale almost as well as the previous approach. Conclusion: There is evidence to indicate that the repair based algorithm introduced in this paper is a suitable technique for extending previous work on requirements optimization to handle the requirement interaction constraints inherent in requirement interactions arising from dependencies, and, or, precedence, cost- and value-based constraints. © 2012 Elsevier B.V. All rights reserved.
Publication data is maintained in RPS. Visit https://rps.ucl.ac.uk
 More search options
UCL Researchers
Dept of Computer Science
Dept of Computer Science
University College London - Gower Street - London - WC1E 6BT Tel:+44 (0)20 7679 2000

© UCL 1999–2011

Search by