Quantifying the Effect of Code Smells on Maintenance Effort

Sjøberg, Dag I. K.; Yamashita, Aiko; Anda, Bente; Mockus, Audris; Dybå, Tore

doi:10.1109/tse.2012.89

Cited by 277 publications

(175 citation statements)

References 35 publications

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“…As discussed in Section IV we do not focus on smell co-occurrences because they happen in a very small percentage (< 9%) of affected classes. The controlled experiment conducted by Sjøberg et al [43] confirmed that smells do not always constitute a problem, and that often class size impacts maintainability more than the presence of smells. Other studies investigate the impact of smells and their perception by surveying project developers.…”

Section: Related Workmentioning

confidence: 91%

“…In the past and, most notably, in recent years, several studies investigated the relevance that code smells have for developers [36], [50], the extent to which code smells tend to remain in a software system for long periods of time [3], [15], [32], [40], as well as the side effects of code smells, such as increase in change-and fault-proneness [25], [26] or decrease of software understandability [1] and maintainability [43], [49], [48].…”

Section: Introductionmentioning

confidence: 99%

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When and Why Your Code Starts to Smell Bad

Tufano

Palomba

Bavota

et al. 2015

2015 IEEE/ACM 37th IEEE International Conference on Software Engineering

200

143

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Abstract-In past and recent years, the issues related to managing technical debt received significant attention by researchers from both industry and academia. There are several factors that contribute to technical debt. One of these is represented by code bad smells, i.e., symptoms of poor design and implementation choices. While the repercussions of smells on code quality have been empirically assessed, there is still only anecdotal evidence on when and why bad smells are introduced. To fill this gap, we conducted a large empirical study over the change history of 200 open source projects from different software ecosystems and investigated when bad smells are introduced by developers, and the circumstances and reasons behind their introduction. Our study required the development of a strategy to identify smellintroducing commits, the mining of over 0.5M commits, and the manual analysis of 9,164 of them (i.e., those identified as smellintroducing). Our findings mostly contradict common wisdom stating that smells are being introduced during evolutionary tasks. In the light of our results, we also call for the need to develop a new generation of recommendation systems aimed at properly planning smell refactoring activities.

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Section: Related Workmentioning

confidence: 91%

Section: Introductionmentioning

confidence: 99%

When and Why Your Code Starts to Smell Bad

Tufano

Palomba

Bavota

et al. 2015

2015 IEEE/ACM 37th IEEE International Conference on Software Engineering

200

143

View full text Add to dashboard Cite

show abstract

“…They identified which maintainability factors are reflected by code smells and which ones are not, basing their results on (i) expertbased maintainability assessments, and (ii) observations and interviews with professional developers. Sjoberg et al (2013) investigated the impact of twelve code smells on the maintainability of software systems. In particular, the authors conducted a study with six industrial developers involved in three maintenance tasks on four Java systems.…”

Section: Code Smells and User Studiesmentioning

confidence: 99%

“…Such tools exploit different types of approaches, including metrics-based detection (Lanza and Marinescu 2010;Moha et al 2010;Marinescu 2004;Munro 2005), graph-based techniques (Tsantalis and Chatzigeorgiou 2009), mining of code changes (Palomba et al 2015a), textual analysis of source code (Palomba et al 2016b), or search-based optimization techniques (Kessentini et al 2010;Sahin et al 2014). On the other side, researchers investigated how relevant code smells are for developers (Yamashita and Moonen 2013;Palomba et al 2014), when and why they are introduced (Tufano et al 2015), how they evolve over time (Arcoverde et al 2011;Chatzigeorgiou and Manakos 2010;Lozano et al 2007;Ratiu et al 2004;Tufano et al 2017), and whether 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 Moonen 2012, 2013;Deligiannis et al 2004;Li and Shatnawi 2007;Sjoberg et al 2013).…”

Section: Introductionmentioning

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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“…Khomh et al found that classes affected by design problems in the form of 'anti-patterns' are more change and fault prone (Khomh et al 2012). On the other hand, Sjøberg et al investigated the relationship between code smells and maintenance effort using professional developers and found that none of the investigated smells were significantly associated with increased effort (Sjøberg et al 2013). Fontana et al used a literature review to identify a range of examples of anti-patterns that might Bnot be as detrimental as previously conjectured .…”

Section: Related Work 21 Software Design Qualitymentioning

confidence: 99%

Recognising object-oriented software design quality: a practitioner-based questionnaire survey

Stevenson

Wood

2017

Software Qual J

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Design quality is vital if software is to be maintainable. What practices do developers actually use to achieve design quality in their day-to-day work and which of these do they find most useful? To discover the extent to which practitioners concern themselves with object-oriented design quality and the approaches used when determining quality in practice, a questionnaire survey of 102 software practitioners, approximately half from the UK and the remainder from elsewhere around the world was used. Individual and peer experience are major contributors to design quality. Classic design guidelines, well-known lower level practices, tools and metrics all can also contribute positively to design quality. There is a potential relationship between testing practices and design quality. Inexperience, time pressures, novel problems, novel technology, and imprecise or changing requirements may have a negative impact on quality. Respondents with most experience are more confident in their design decisions, place more value on reviews by team leads and are more likely to rate design quality as very important. For practitioners, these results identify the techniques and tools that other practitioners find effective. For researchers, the results highlight a need for more work investigating the role of experience in the design process and the contribution experience makes to quality. There is also the potential for more in-depth studies of how practitioners are actually using design guidance, including Clean Code. Lastly, the potential relationship between testing practices and design quality merits further investigation.

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Quantifying the Effect of Code Smells on Maintenance Effort

Cited by 277 publications

References 35 publications

When and Why Your Code Starts to Smell Bad

When and Why Your Code Starts to Smell Bad

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

Recognising object-oriented software design quality: a practitioner-based questionnaire survey

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