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DOI

Existing maintainability models are used to identify technical debt of software systems. Targeting entire codebases, such models lack the ability to determine shortcomings of smaller, fine-grained changes. This paper proposes a new maintainability model – the Delta Maintainability Model (DMM) – to measure fine-grained code changes, such as commits, by adapting and extending the SIG Maintainability Model. DMM categorizes changed lines of code into low and high risk, and then uses the proportion of low risk change to calculate a delta score. The goal of the DMM is twofold: first, producing meaningful and actionable scores; second, compare and rank the maintainability of fine-grained modifications.
We report on an initial study of the model, with the goal of understanding if the adapted measurements from the SIG Maintainability Model suit the fine-grained scope of the DMM. In a manual inspection process for 100 commits, 67 cases matched the expert judgment. Furthermore, we report an exploratory empirical study on a data set of DMM scores on 3,017 issue-fixing commits of four open source and four closed source systems. Results show that the scores of DMM can be used to compare and rank commits, providing developers with a means to do root cause analysis on activities that impacted maintainability and, thus, address technical debt at a finer granularity.
Original languageEnglish
Title of host publicationTechDebt 2019 - International Conference on Technical Debt
Number of pages10
DOIs
Publication statusPublished - 2019
EventTechDebt 2019 - International Conference on Technical Debt - MontréaL, Canada
Duration: 26 May 201927 May 2019

Conference

ConferenceTechDebt 2019 - International Conference on Technical Debt
Abbreviated titleTechDebt 2019
CountryCanada
CityMontréaL
Period26/05/1927/05/19

ID: 53624442