Searched for: subject%3A%22code%255C+smells%22
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Van Oort, Bart (author), Cruz, Luis (author), Loni, Babak (author), van Deursen, A. (author)
Machine Learning (ML) projects incur novel challenges in their development and productionisation over traditional software applications, though established principles and best practices in ensuring the project's software quality still apply. While using static analysis to catch code smells has been shown to improve software quality attributes...
conference paper 2022
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Zhang, H. (author), Cruz, Luis (author), van Deursen, A. (author)
The popularity of machine learning has wildly expanded in recent years. Machine learning techniques have been heatedly studied in academia and applied in the industry to create business value. However, there is a lack of guidelines for code quality in machine learning applications. In particular, code smells have rarely been studied in this...
conference paper 2022
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Shome, A. (author), Cruz, Luis (author), van Deursen, A. (author)
The adoption of Artificial Intelligence (AI) in high-stakes domains such as healthcare, wildlife preservation, autonomous driving and criminal justice system calls for a data-centric approach to AI. Data scientists spend the majority of their time studying and wrangling the data, yet tools to aid them with data analysis are lacking. This...
conference paper 2022
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Kannan, Jai (author), Barnett, Scott (author), Cruz, Luis (author), Simmons, Anj (author), Agarwal, Akash (author)
Meeting the rise of industry demand to incorporate machine learning (ML) components into software systems requires interdisciplinary teams contributing to a shared code base. To maintain consistency, reduce defects and ensure maintainability, developers use code analysis tools to aid them in identifying defects and maintaining standards. With...
conference paper 2022
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van Oort, Bart (author)
Artificial Intelligence (AI) and Machine Learning (ML) are pervasive in the current computer science landscape. Yet, there still exists a lack of Software Engineering (SE) experience and best practices in this field. One such best practice, static code analysis, can be used to find code smells, i.e., (potential) defects in the source code,...
master thesis 2021
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Palomba, Fabio (author), Tamburri, Damian Andrew (author), Arcelli Fontana, Francesca (author), Oliveto, Rocco (author), Zaidman, A.E. (author), Serebrenik, Alexander (author)
Code smells are poor implementation choices applied by developers during software evolution that often lead to critical flaws or failure. Much in the same way, community smells reflect the presence of organizational and socio-Technical issues within a software community that may lead to additional project costs. Recent empirical studies...
journal article 2021
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van Oort, B. (author), Cruz, Luis (author), Aniche, Maurício (author), van Deursen, A. (author)
Artificial Intelligence (AI) and Machine Learning (ML) are pervasive in the current computer science landscape. Yet, there still exists a lack of software engineering experience and best practices in this field. One such best practice, static code analysis, can be used to find code smells, i.e., (potential) defects in the source code,...
conference paper 2021
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Palomba, F. (author), Zanoni, Marco (author), Arcelli Fontana, Francesca (author), De Lucia, Andrea (author), Oliveto, Rocco (author)
Code smells are symptoms of poor design and implementation choices. Previous studies empirically assessed the impact of smells on code quality and clearly indicate their negative impact on maintainability, including a higher bug-proneness of components affected by code smells. In this paper, we capture previous findings on bug-proneness to...
journal article 2019
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Catolino, G. (author), Palomba, F. (author), Arcelli Fontana, Francesca (author), De Lucia, Andrea (author), Zaidman, A.E. (author), Ferrucci, Filomena (author)
Code smells are sub-optimal implementation choices applied by developers that have the effect of negatively impacting, among others, the change-proneness of the affected classes. Based on this consideration, in this paper we conjecture that code smell-related information can be effectively exploited to improve the performance of change...
journal article 2019
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Goularte Carvalho, Suelen (author), Aniche, Maurício (author), Veríssimo, Júlio (author), Durelli, Rafael (author), Gerosa, Marco Aurélio (author)
Software developers, including those of the Android mobile platform, constantly seek to improve their applications’ maintainability and evolvability. Code smells are commonly used for this purpose, as they indicate symptoms of design problems. However, although the literature presents a variety of code smells, such as God Class and Long...
journal article 2019
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Palomba, F. (author), Di Nucci, D. (author), Panichella, A. (author), Zaidman, A.E. (author), De Lucia, Andrea (author)
Context. The demand for green software design is steadily growing higher especially in the context of mobile devices, where the computation is often limited by battery life. Previous studies found how wrong programming solutions have a strong impact on the energy consumption. Objective. Despite the efforts spent so far, only a little knowledge...
journal article 2019
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Lim, Dustin (author)
Code smells are patterns in programming code which indicate potential issues with software quality. Previous research resulted in the development of code smell detectors: automated tools which traverse through large quantities of code and return smell detections to software developers.<br/>The Android platform has become very popular over the...
master thesis 2018
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Palomba, F. (author), Panichella, A. (author), Zaidman, A.E. (author), Oliveto, Rocco (author), De Lucia, Andrea (author)
Code smells are symptoms of poor design or implementation choices that have a negative effect on several aspects of software maintenance and evolution, such as program comprehension or change- and fault-proneness. This is why researchers have spent a lot of effort on devising methods that help developers to automatically detect them in source...
journal article 2018
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Aniche, Maurício (author), Bavota, Gabriele (author), Treude, Christoph (author), Gerosa, Marco Aurélio (author), van Deursen, A. (author)
Previous studies have shown the negative effects that low-quality code can have on maintainability proxies, such as code change- and defect-proneness. One of the symptoms for low-quality code are code smells, defined as sub-optimal implementation choices. While this definition is quite general and seems to suggest a wide spectrum of smells that...
journal article 2018
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Palomba, F. (author), Bavota, Gabriele (author), Di Penta, Massimiliano (author), Fasano, Fausto (author), Oliveto, Rocco (author), De Lucia, Andrea (author)
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...
journal article 2017
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Palomba, F. (author), Di Nucci, D. (author), Panichella, A. (author), Zaidman, A.E. (author), De Lucia, Andrea (author)
Code smells are symptoms of poor design solutions applied by programmers during the development of software systems. While the research community devoted a lot of effort to studying and devising approaches for detecting the traditional code smells defined by Fowler, little knowledge and support isavailable for an emerging category of Mobile app...
conference paper 2017
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Aniche, Maurício (author), Bavota, Gabriele (author), Treude, Christoph (author), van Deursen, A. (author), Gerosa, Marco Aurélio (author)
Code smells are symptoms of poor design and implementation choices that may hinder code comprehension, and possibly increase change-and defect-proneness. A vast catalogue of smells has been defined in the literature, and it includes smells that can be found in any kind of system (e.g., God Classes), regardless of their architecture. On the other...
conference paper 2016
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Hermans, F.F.J. (author), Pinzger, M. (author), Van Deursen, A. (author)
Preprint of article published in: Empirical Software Engineering, February 2014, Springer Science+Business Media New York, doi:10.1007/s10664-013-9296-2 Spreadsheets are used extensively in business processes around the world and just like software, spreadsheets are changed throughout their lifetime causing understandability and maintainability...
report 2013
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Verloop, D. (author)
The mobile applications market is growing rapidly, over 85 billion mobile applications have been downloaded. Smartphone sales are already bigger than computer sales and this might become the first year in which over one billion smart phones will be sold. Regardless of these statistics there is not a lot of research to be found on the subject. In...
master thesis 2013
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Boekesteijn, J. (author)
Static analysis techniques provide a means to detect software errors early in the development process, without actually having to run the software that is being analyzed. These techniques are common for statically typed languages and have found their way into IDEs such as Eclipse and Visual Studio. However, applying the same techniques to...
master thesis 2012
Searched for: subject%3A%22code%255C+smells%22
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