An Exploratory Study of the Impact of Code Smells on Software Change-proneness
By Foutse Khomh, Massimiliano Di Penta, Yann-Gaël Guéhéneuc. Working Conference on Reverse Engineering, 2009
339 citations recorded by the source corpus.
Subfields: Information Systems, Software
View Paper: https://www.semanticscholar.org/paper/907080bd29b16c5f94bd38e205ed2e1c5770bbb2
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Information Systems
- Massimiliano Di Penta
- Gabriele Bavota
- Rocco Oliveto
- Andrea De Lucia
- Fabio Palomba
- Fausto Fasano
- Foutse Khomh
- G. Antoniol
In Software
- Massimiliano Di Penta
- Rocco Oliveto
- Andrea De Lucia
- Gabriele Bavota
- Fabio Palomba
- Fausto Fasano
- Foutse Khomh
- G. Antoniol
Citations in the corpus
- When and Why Your Code Starts to Smell Bad (and Whether the Smells Go Away) (2017, neutral): “…to which code smells tend to remain in a software system for long periods of time [4], [18], [49], [65], as well as the side effects of code smells, such as an increase in change-and fault-proneness [38], [39] or decrease of software understandability [1] and maintainability [73], [90], [89].”
- On the diffuseness and the impact on maintainability of code smells: a large scale empirical investigation (2017, methodology): “…they impact on software quality properties, such as program comprehensibility (Abbes et al. 2011), fault-and change-proneness (Khomh et al. 2012; Khomh et al. 2009a; D’Ambros et al. 2010), and code maintainability (Yamashita and Moonen 2012, 2013; Deligiannis et al. 2004; Li and Shatnawi 2007;…”
- An Empirical Study of the Impact of Two Antipatterns, Blob and Spaghetti Code, on Program Comprehension (2011, background): “Riel [10] defined 61 heuristics characterising good object-oriented programming to assess a system quality manually and improve its design and implementation.”