A Bayesian Approach for the Detection of Code and Design Smells

Khomh, Foutse; Vaucher, Stéphane; Guéhéneuc, Yann‐Gaël; Sahraoui, Houari

doi:10.1109/qsic.2009.47

Cited by 175 publications

(115 citation statements)

References 14 publications

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“…This is pretty much consistent with results of the previous study made by Ratiu et al for God classes [11]. This result highlights the usefulness of smell detectors providing a measure of severity for each identified smell, as in the approach by Khomh et al [20]. In this way, developers can focus their attention on smells that are more likely to represent a threat from their point of view.…”

Section: Discussionsupporting

confidence: 89%

See 1 more Smart Citation

Do They Really Smell Bad? A Study on Developers' Perception of Bad Code Smells

Palomba

Bavota

Penta

et al. 2014

2014 IEEE International Conference on Software Maintenance and Evolution

206

121

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Abstract-In the last decade several catalogues have been defined to characterize code bad smells, i.e., symptoms of poor design and implementation choices. On top of such catalogues, researchers have defined methods and tools to automatically detect and/or remove bad smells. Nevertheless, there is an ongoing debate regarding the extent to which developers perceive bad smells as serious design problems. Indeed, there seems to be a gap between theory and practice, i.e., what is believed to be a problem (theory) and what is actually a problem (practice).This paper presents a study aimed at providing empirical evidence on how developers perceive bad smells. In this study, we showed to developers code entities-belonging to three systemsaffected and not by bad smells, and we asked them to indicate whether the code contains a potential design problem, and if any, the nature and severity of the problem. The study involved both original developers from the three projects and outsiders, namely industrial developers and Master students. The results provide insights on characteristics of bad smells not yet explored sufficiently. Also, our findings could guide future research on approaches for the detection and removal of bad smells.

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Section: Discussionsupporting

confidence: 89%

“…Khomh et al [20] use quality metrics to train a Bayesian belief networks aiming at detecting bad smells. The main novelty of that approach is that it provides a likelihood that a code component is affected by a smell, instead of just providing a Boolean value like the previous techniques.…”

Section: A Code Bad Smell Detectionmentioning

confidence: 99%

Do They Really Smell Bad? A Study on Developers' Perception of Bad Code Smells

Palomba

Bavota

Penta

et al. 2014

2014 IEEE International Conference on Software Maintenance and Evolution

206

121

View full text Add to dashboard Cite

show abstract

“…While the research community devoted a lot of effort on understanding [41], [42], [43], [44], [45], [46], [47], [48], [49], [50], [51], [52] and detecting [53], [54], [55], [56], [57], [58], [59], [60], [61] design flaws occurring in production code, smells affecting test code have only been partially explored.…”

Section: A About Test Smellsmentioning

confidence: 99%

Notice of Retraction: Does Refactoring of Test Smells Induce Fixing Flaky Tests?

Palomba

Zaidman

2017

2017 IEEE International Conference on Software Maintenance and Evolution (ICSME)

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Abstract-Regression testing is a core activity that allows developers to ensure that source code changes do not introduce bugs. An important prerequisite then is that test cases are deterministic. However, this is not always the case as some tests suffer from socalled flakiness. Flaky tests have serious consequences, as they can hide real bugs and increase software inspection costs. Existing research has focused on understanding the root causes of test flakiness and devising techniques to automatically fix flaky tests; a key area of investigation being concurrency. In this paper, we investigate the relationship between flaky tests and three previously defined test smells, namely Resource Optimism, Indirect Testing and Test Run War. We have set up a study involving 19,532 JUnit test methods belonging to 18 software systems. A key result of our investigation is that 54% of tests that are flaky contain a test code smell that can cause the flakiness. Moreover, we found that refactoring the test smells not only removed the design flaws, but also fixed all 54% of flaky tests causally co-occurring with test smells.

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“…We chose not to use existing detection tools (Marinescu 2004;Khomh et al 2009b;Sahin et al 2014;Tsantalis and Chatzigeorgiou 2009;Moha et al 2010;Oliveto et al 2010;Palomba et al 2015a) because (i) none of them has ever been applied to detect all the studied code smells and (ii) their detection rules are generally more restrictive to ensure a good compromise between recall and precision and thus may miss some smell instances. To verify this claim, we evaluated the behavior of three existing tools, i.e., DECOR (Moha et al 2010), JDeodorant (Tsantalis and Chatzigeorgiou 2009), and HIST (Palomba et al 2015a) on one of the systems used in the empirical study, i.e., Apache Cassandra 1.1.…”

Section: Research Questions and Planningmentioning

confidence: 99%

On the diffuseness and the impact on maintainability of code smells: a large scale empirical investigation

et al. 2017

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Code smells are symptoms of poor design and implementation choices that may hinder code comprehensibility and maintainability. Despite the effort devoted by the research community in studying code smells, the extent to which code smells in software systems affect software maintainability remains still unclear. In this paper we present a large scale empirical investigation on the diffuseness of code smells and their impact on code change-and fault-proneness. The study was conducted across a total of 395 releases of 30

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A Bayesian Approach for the Detection of Code and Design Smells

Cited by 175 publications

References 14 publications

Do They Really Smell Bad? A Study on Developers' Perception of Bad Code Smells

Do They Really Smell Bad? A Study on Developers' Perception of Bad Code Smells

Notice of Retraction: Does Refactoring of Test Smells Induce Fixing Flaky Tests?

On the diffuseness and the impact on maintainability of code smells: a large scale empirical investigation

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