Fabiano Pecorelli, Fabio Palomba, Foutse Khomh et Andrea De Lucia
Communication écrite (2020)
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Code smells are symptoms of poor implementation choices applied during software evolution. While previous research has devoted effort in the definition of automated solutions to detect them, still little is known on how to support developers when prioritizing them. Some works attempted to deliver solutions that can rank smell instances based on their severity, computed on the basis of software metrics. However, this may not be enough since it has been shown that the recommendations provided by current approaches do not take the developer's perception of design issues into account. In this paper, we perform a first step toward the concept of developer-driven code smell prioritization and propose an approach based on machine learning able to rank code smells according to the perceived criticality that developers assign to them. We evaluate our technique in an empirical study to investigate its accuracy and the features that are more relevant for classifying the developer's perception. Finally, we compare our approach with a state-of-the-art technique. Key findings show that the our solution has an F-Measure up to 85% and outperforms the baseline approach.
Mots clés
code smells; machine learning for software engineering; empirical software engineering
Sujet(s): |
2700 Technologie de l'information > 2705 Logiciels et développement 2700 Technologie de l'information > 2706 Génie logiciel |
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Département: | Département de génie informatique et génie logiciel |
Organismes subventionnaires: | Swiss National Science Foundation |
Numéro de subvention: | SNF Project No. PZ00P2_186090(TED) |
URL de PolyPublie: | https://publications.polymtl.ca/9343/ |
Nom de la conférence: | 17th International Conference on Mining Software Repositories (MSR 2020) |
Lieu de la conférence: | Seoul, Republic of Korea |
Date(s) de la conférence: | 2020-06-29 - 2020-06-30 |
Maison d'édition: | ACM |
DOI: | 10.1145/3379597.3387457 |
URL officielle: | https://doi.org/10.1145/3379597.3387457 |
Date du dépôt: | 06 sept. 2023 12:22 |
Dernière modification: | 25 sept. 2024 15:45 |
Citer en APA 7: | Pecorelli, F., Palomba, F., Khomh, F., & De Lucia, A. (juin 2020). Developer-driven code smell prioritization [Communication écrite]. 17th International Conference on Mining Software Repositories (MSR 2020), Seoul, Republic of Korea. https://doi.org/10.1145/3379597.3387457 |
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