RT Conference Proceedings
T1 Variability Debt: 												A Multi-method Study
A1 Wolfart, Daniele
A1 Assunção, Wesley K.Guez
A1 Martinez, Jabier
AB Technical debt is a metaphor to guide the identification, measurement, and general management of decisions that were mostly appropriate in the short term but created obstacles mainly for the evolution and maintenance of systems. Variability management, which is the ability to create variants of systems to satisfy different needs, is a potential source of technical debt. Variability debt, a term coined in this work, is caused by sub-optimal solutions in the implementation of variability management in software systems. We performed a systematic literature review to characterize variability debt, and conducted a field study in which we report quantitative and qualitative analysis based on documents (e.g., requirements, specifications, source code, and test cases) and a survey with stakeholders. The context is a large company with three different systems, where opportunistic reuse was applied to create variants for each system. We describe and characterize the variability debt phenomenon in this field study, and we assess the validity of the metaphor to create awareness in diverse company stakeholders and to guide technical debt management research related to variability aspects. The analysis of the field study's artifacts show evidences of factors that complicate the evolution of the variants, such as code duplication and non-synchronized artifacts. Time pressure is identified as the main cause for not considering other options than opportunistic reuse. Technical practitioners mostly agree on the creation of usability problems and complex maintenance of multiple independent variants. However, this is not fully perceived by managerial practitioners.
PB Association for Computing Machinery
SN 9798400707865
YR 2023
FD 2023-11-07
LK https://hdl.handle.net/11556/2145
UL https://hdl.handle.net/11556/2145
LA eng
NO Wolfart , D , Assunção , W K G & Martinez , J 2023 , Variability Debt : A Multi-method Study . in SBQS 2023 - Proceedings of the 22nd Brazilian Symposium on Software Quality . ACM International Conference Proceeding Series , Association for Computing Machinery , pp. 358-367 , 22nd Brazilian Symposium on Software Quality, SBQS 2023 , Brasilia , Brazil , 7/11/23 . https://doi.org/10.1145/3629479.3629513
NO conference
NO Publisher Copyright: © 2023 ACM.
DS TECNALIA Publications
RD 28 jul 2024