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Publication Detail
The Value of Exact Analysis in Requirements Selection
  • Publication Type:
    Journal article
  • Publication Sub Type:
  • Authors:
    Li L, Harman M, Wu F, Zhang Y
  • Publication date:
  • Journal:
    IEEE Transactions on Software Engineering
  • Volume:
  • Issue:
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  • Print ISSN:
© 2016 IEEE.Uncertainty is characterised by incomplete understanding. It is inevitable in the early phase of requirements engineering, and can lead to unsound requirement decisions. Inappropriate requirement choices may result in products that fail to satisfy stakeholders' needs, and might cause loss of revenue. To overcome uncertainty, requirements engineering decision support needs uncertainty management. In this research, we develop a decision support framework METRO for the Next Release Problem (NRP) to manage algorithmic uncertainty and requirements uncertainty. An exact NRP solver (NSGDP) lies at the heart of METRO. NSGDP's exactness eliminates interference caused by approximate existing NRP solvers. We apply NSGDP to three NRP instances, derived from a real world NRP instance, RALIC, and compare with NSGA-II, a widely-used approximate (inexact) technique. We find the randomness of NSGA-II results in decision makers missing up to 99.95% of the optimal solutions and obtaining up to 36:48% inexact requirement selection decisions. The chance of getting an inexact decision using existing approximate approaches is negatively correlated with the implementation cost of a requirement (Spearman ρ up to -0.72). Compared to the inexact existing approach, NSGDP saves 15.21% lost revenue, on average, for the RALIC dataset.
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