Investigating factors that affect the human perception on god class detection: an analysis based on a family of four controlled experiments
Context Evaluation of design problems in object oriented systems, which we call code smells, is mostly a human-based task. Several studies have investigated the impact of code smells in practice. Studies focusing on human identification of code smells have shown low agreement among developers. Unfor...
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Veröffentlicht in: | Journal of software engineering research and development 2017-11, Vol.5 (1), p.1-39, Article 8 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Context
Evaluation of design problems in object oriented systems, which we call code smells, is mostly a human-based task. Several studies have investigated the impact of code smells in practice. Studies focusing on human identification of code smells have shown low agreement among developers. Unfortunately, those studies do not attempt to investigate the reasons behind this phenomenon.
Objective
This paper aims to investigate factors affecting human perception of code smells. Specifically, it focuses on factors affecting god class detection, one of the most known code smells.
Method
The investigation encompassed a family of four controlled experiments, covering potential factors affecting human detection of code smells. The method is incremental. In other words, each experiment produces insights to the next one. This allows the investigators to control specific factors affecting the agreement on god class detection. The factors addressed in this study are: i) developer experience, ii) developer knowledge, iii) developer training, iv) tool support for design comprehension, and v) software size.
Result
Our findings show that tool support for design comprehension is the only factor that does not affect the human perception of god class. The other factors impact this perception in some way.
Conclusion
The area still needs more investigation and discussion on what we call the
code smell conceptualization problem
, to ensure similar criteria and thresholds on human-based code smell detection. |
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ISSN: | 2195-1721 2195-1721 |
DOI: | 10.1186/s40411-017-0042-0 |