Architectural Decay as Predictor of Issue- and Change-Proneness
| Autor: | Nenad Medvidovic, Suhrid Karthik, Duc Minh Le, Marcelo Schmitt Laser |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
FOS: Computer and information sciences
Correctness business.industry Computer science Maintenance engineering Data modeling Software Engineering (cs.SE) Computer Science - Software Engineering Empirical research Feature (machine learning) Software system Software architecture Software engineering business Implementation |
| Zdroj: | ICSA |
| DOI: | 10.1109/icsa51549.2021.00017 |
| Popis: | Architectural decay imposes real costs in terms of developer effort, system correctness, and performance. Over time, those problems are likely to be revealed as explicit implementation issues (defects, feature changes, etc.). Recent empirical studies have demonstrated that there is a significant correlation between architectural "smells" -- manifestations of architectural decay -- and implementation issues. In this paper, we take a step further in exploring this phenomenon. We analyze the available development data from 10 open-source software systems and show that information regarding current architectural decay in these systems can be used to build models that accurately predict future issue-proneness and change-proneness of the systems' implementations. As a less intuitive result, we also show that, in cases where historical data for a system is unavailable, such data from other, unrelated systems can provide reasonably accurate issue- and change-proneness prediction capabilities. |
| Databáze: | OpenAIRE |
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