MLSmellHound: A Context-Aware Code Analysis Tool

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...

Data Smells in Public Datasets

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...

'Project smells' - Experiences in Analysing the Software Quality of ML Projects with mllint

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...

Code Smells for Machine Learning Applications

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...

The Prevalence of Code Smells in Machine Learning Projects

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,...

Beyond Technical Aspects: How Do Community Smells Influence the Intensity of Code Smells?

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...

Toward a Smell-aware Bug Prediction Model

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...

On the Impact of Code Smells on the Energy Consumption of Mobile Applications

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...

Improving Change Prediction Models with Code Smell-Related Information

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...

An Empirical Catalog of Code Smells for the Presentation Layer of Android Apps

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...

The Scent of a Smell: An Extensive Comparison between Textual and Structural Smells

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...

Code smells for Model-View-Controller architectures

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...

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

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...

Lightweight Detection of Android-specific Code Smells: The aDoctor Project

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...

A Validated Set of Smells in Model-View-Controller Architectures

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...

Detecting and refactoring code smells in spreadsheet formula

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...

Detecting Code Smells in Spreadsheet Formulas

Spreadsheets are used extensively in business processes around the world and just like software, spreadsheets are changed throughout their lifetime causing maintainability issues. This paper adapts known code smells to spreadsheet formulas. To that end we present a list of metrics by which we can detect smelly formulas and a visualization...

Detecting and Visualizing Inter-Worksheet Smells in Spreadsheets

Spreadsheets are often used in business, for simple tasks, as well as for mission critical tasks such as finance or forecasting. Similar to software, some spreadsheets are of better quality than others, for instance with respect to usability, maintainability or reliability. In contrast with software however, spreadsheets are rarely checked,...