Opti-Soft+: A Recommender and Sensitivity Analysis for Optimal Software Feature Selection and Release Planning

Fernando Boccanera, Alexander Brodsky

2022

Abstract

Many approaches have been developed to increase the return on a software investment, but each one has drawbacks. Proposed in this paper is the Opti-Soft+ framework that addresses this problem by producing a software release schedule that maximizes the business value of investments in information systems that automate business processes. The optimal release schedule is the result of solving a mixed integer linear programming problem. Opti-Soft+ is an extension of the Opti-Soft framework proposed earlier with (1) a refined cost model, (2) a technique for sensitivity analysis of the normalized cost per unit of production, and (3) an atomic business process model that is driven by output throughputs in addition to input throughputs.

Paper Citation

in Harvard Style

Boccanera F. and Brodsky A. (2022). Opti-Soft+: A Recommender and Sensitivity Analysis for Optimal Software Feature Selection and Release Planning. In Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-758-569-2, pages 500-513. DOI: 10.5220/0011062400003179

in Bibtex Style

@conference{iceis22,
author={Fernando Boccanera and Alexander Brodsky},
title={Opti-Soft+: A Recommender and Sensitivity Analysis for Optimal Software Feature Selection and Release Planning},
booktitle={Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2022},
pages={500-513},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011062400003179},
isbn={978-989-758-569-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 24th International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - Opti-Soft+: A Recommender and Sensitivity Analysis for Optimal Software Feature Selection and Release Planning
SN - 978-989-758-569-2
AU - Boccanera F.
AU - Brodsky A.
PY - 2022
SP - 500
EP - 513
DO - 10.5220/0011062400003179