TY - GEN
T1 - Variability Debt
T2 - 22nd Brazilian Symposium on Software Quality, SBQS 2023
AU - Wolfart, Daniele
AU - Assunção, Wesley K.Guez
AU - Martinez, Jabier
N1 - Publisher Copyright:
© 2023 ACM.
PY - 2023/11/7
Y1 - 2023/11/7
N2 - 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.
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.
KW - Software reuse
KW - Technical Debt
KW - Variability Debt
KW - Variability management
UR - http://www.scopus.com/inward/record.url?scp=85180148148&partnerID=8YFLogxK
U2 - 10.1145/3629479.3629513
DO - 10.1145/3629479.3629513
M3 - Conference contribution
AN - SCOPUS:85180148148
T3 - ACM International Conference Proceeding Series
SP - 358
EP - 367
BT - SBQS 2023 - Proceedings of the 22nd Brazilian Symposium on Software Quality
PB - Association for Computing Machinery
Y2 - 7 November 2023 through 10 November 2023
ER -