Exact Scalable Sensitivity Analysis for the Next Release Problem

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The nature of the requirements analysis problem, based as it is on uncertain and often inaccurate estimates of costs and effort, makes sensitivity analysis important. Sensitivity analysis allows the decision maker to identify those requirements and budgets that are particularly sensitive to misestimation. However, finding scalable sensitivity analysis techniques is not easy because the underlying optimization problem is NP-hard. This article introduces an approach to sensitivity analysis based on exact optimization. We implemented this approach as a tool, O-ATSAC, which allowed us to experimentally evaluate the scalability and applicability of Requirements Sensitivity Analysis (RSA). Our results show that O-ATSAC scales sufficiently well for practical applications in Requirements Sensitivity Analysis. We also show how the sensitivity analysis can yield insights into difficult and otherwise obscure interactions between budgets, requirements costs, and estimate inaccuracies using a real-world case study.
Publisher
ASSOC COMPUTING MACHINERY
Issue Date
2014-03
Language
English
Article Type
Article
Keywords

REQUIREMENTS; SELECTION; OPTIMIZATION; KNAPSACK; PRODUCT

Citation

ACM TRANSACTIONS ON SOFTWARE ENGINEERING AND METHODOLOGY, v.23, no.2

ISSN
1049-331X
DOI
10.1145/2537853
URI
http://hdl.handle.net/10203/200835
Appears in Collection
CS-Journal Papers(저널논문)
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