Kruizinga, Ronald and Scheedler, Ruben (2020) Exploring the Relation between Co-changes and Architectural Smells. Master's Thesis / Essay, Computing Science.
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Abstract
In the last decade, the technical debt metaphor has gradually grown in popularity and is now become the preferred way for both practitioners and researchers to discuss the effort, costs and issues arising during software development activities. Detecting technical debt is one of the first steps to limit its growth and eventually pay it back. Co-changes are artefacts that over time change in a similar way and are an indicator of technical debt. Architectural smells are combinations of architectural decisions that reduce system maintainability, and are a form of technical debt. The goal of this thesis is twofold, namely to investigate the possible relationship between co-changes and architectural smells and to compare different ways of mining co-changes. If co-changes are related to architectural smells, detecting co-changes can be used to trace technical debt. To this end, this research introduces a novel way of detecting co-changes called “Fuzzy Overlap”. This approach is compared with state-of-the-art approaches such as Market Basket Analysis and Dynamic Time Warping. Regarding the relation between co-changes and architectural smells, this study attempts to analyze its direction, whether co-changes are more often found in smelly artefacts, and whether the smells are introduced before or after file pairs start to cochange. From this analysis, it has become clear that the output produced by the Fuzzy Overlap algorithm tends to vastly differ from that generated by Market Basket Analysis and Dynamic Time Warping. For 50% of the projects analyzed, a relation between architectural smells and co-changes was found and for 100% of the projects it was found that co-changing precedes the introduction of architectural smells.
| Item Type: | Thesis (Master's Thesis / Essay) |
|---|---|
| Supervisor name: | Avgeriou, P. and Sas, D.D. |
| Degree programme: | Computing Science |
| Thesis type: | Master's Thesis / Essay |
| Language: | English |
| Date Deposited: | 31 Jul 2020 09:54 |
| Last Modified: | 04 Aug 2020 11:28 |
| URI: | https://fse.studenttheses.ub.rug.nl/id/eprint/22763 |
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