The use of search-based optimization techniques to schedule and staff software projects: an approach and an empirical study

Authors:
Massimiliano Di Penta;Mark Harman;Giuliano Antoniol
Affiliations:
Department of Engineering, University of Sannio—Palazzo ex Poste, Via Traiano, 82100 Benevento, Italy;Department of Computer Science, King's College London—Strand, London WC2R 2LS, U.K.;Department of Génie Informatique, École Polytechnique de Montréal, Montréal, QC, Canada
Venue:
Software—Practice & Experience
Year:
2011

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Abstract

Allocating resources to a software project and assigning tasks to teams constitute crucial activities that affect project cost and completion time. Finding a solution for such a problem is NP-hard; this requires managers to be supported by proper tools for performing such an allocation. This paper shows how search-based optimization techniques can be combined with a queuing simulation model to address these problems. The obtained staff and task allocations aim to minimize the completion time and reduce schedule fragmentation. The proposed approach allows project managers to run multiple simulations, compare results and consider trade-offs between increasing the staffing level and anticipating the project completion date and between reducing the fragmentation and accepting project delays. The paper presents results from the application of the proposed search-based project planning approach to data obtained from two large-scale commercial software maintenance projects. Copyright © 2011 John Wiley & Sons, Ltd.