Hier finden Sie wissenschaftliche Publikationen aus den Fraunhofer-Instituten.

Trade-off analysis for requirements selection

: Ruhe, G.; Eberlein, A.; Pfahl, D.


International Journal of Software Engineering and Knowledge Engineering : SEKE 13 (2003), No.4, pp.345-366 : Ill., Lit.
ISSN: 0218-1940
Journal Article
Fraunhofer IESE ()
requirement selection; decision support; trade-off analysis; resource constraint; analytical hierarchy process; simulation

Evaluation, prioritization and selection of candidate requirements are of tremendous importance and impact for subsequent software development. Effort, time as well as quality constraints have to be taken into account. Typically, different stakeholders have conflicting priorities and the requirements of all these stakeholders have to be balanced in an appropriate way to ensure maximum value of the final set of requirements. Trade-off analysis is needed to proactively explore the impact of certain decisions in terms of all the criteria and constraints.
The proposed method called Quantitative WinWin uses an evolutionary approach to provide support for requirements negotiations. The novelty of the presented idea is fourfold. Firstly, it iteratively uses the Analytical Hierarchy Process (AHP) for a stepwise analysis with the aim to balance the stakeholders' preferences related to different classes of requirements. Secondly, requirements selection is based on predicting and rebalancing its impact on effort, time and quality. Both prediction and rebalancing uses the simulation model prototype GENSIM. Thirdly, alternative solution sets offered for decision-making are developed incrementally based on thresholds for the degree of importance of requirements and heuristics to find a best fit to constraints. Finally, trade-off analysis is used to determine non-dominated extensions of the maximum value that is achievable under resource and quality constraints. As a main result, quantitative WinWin proposes a small number of possible sets of requirements from which the actual decision-maker finally can select the most appropriate solution.