Please use this identifier to cite or link to this item: https://ruomo.lib.uom.gr/handle/7000/1103
Title: Translating quality-driven code change selection to an instance of multiple-criteria decision making
Authors: Lamprakos, Christos P.
Marantos, Charalampos
Siavvas, Miltiadis
Papadopoulos, Lazaros
Tsintzira, Angeliki-Agathi
Ampatzoglou, Apostolos
Chatzigeorgiou, Alexander
Kehagias, Dionysios
Soudris, Dimitrios
Type: Article
Subjects: FRASCATI::Natural sciences::Computer and information sciences
Keywords: Decision support
Software quality
Multiple-criteria decision making
Issue Date: May-2022
Source: Information and Software Technology
Volume: 145
First Page: 106851
Abstract: Context: The definition and assessment of software quality have not converged to a single specification. Each team may formulate its own notion of quality and tools and methodologies for measuring it. Software quality can be improved via code changes, most often as part of a software maintenance loop. Objective: This manuscript contributes towards providing decision support for code change selection given a) a set of preferences on a software product’s qualities and b) a pool of heterogeneous code changes to select from. Method: We formulate the problem as an instance of Multiple-Criteria Decision Making, for which we provide both an abstract flavor and a prototype implementation. Our prototype targets energy efficiency, technical debt and dependability. Results: This prototype achieved inconsistent results, in the sense of not always recommending changes reflecting the decision maker’s preferences. Encouraged from some positive cases and cognizant of our prototype’s shortcomings, we propose directions for future research. Conclusion: This paper should thus be viewed as an imperfect first step towards quality-driven, code change-centered decision support and, simultaneously, as a curious yet pragmatic enough gaze on the road ahead.
URI: https://doi.org/10.1016/j.infsof.2022.106851
https://ruomo.lib.uom.gr/handle/7000/1103
ISSN: 0950-5849
Other Identifiers: 10.1016/j.infsof.2022.106851
Appears in Collections:Department of Applied Informatics

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