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Developers talking about code quality
Blekinge Institute of Technology, Sweden.ORCID iD: 0000-0003-0639-4234
Wageningen University and Research, Netherlands.
Virginia Tech, USA.
Utrecht University, Netherlands.
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2023 (English)In: Empirical Software Engineering, ISSN 1382-3256, E-ISSN 1573-7616, Vol. 28, no 6, article id 128Article in journal (Refereed) Published
Abstract [en]

There are many aspects of code quality, some of which are difficult to capture or to measure. Despite the importance of software quality, there is a lack of commonly accepted measures or indicators for code quality that can be linked to quality attributes. We investigate software developers’ perceptions of source code quality and the practices they recommend to achieve these qualities. We analyze data from semi-structured interviews with 34 professional software developers, programming teachers and students from Europe and the U.S. For the interviews, participants were asked to bring code examples to exemplify what they consider good and bad code, respectively. Readability and structure were used most commonly as defining properties for quality code. Together with documentation, they were also suggested as the most common target properties for quality improvement. When discussing actual code, developers focused on structure, comprehensibility and readability as quality properties. When analyzing relationships between properties, the most commonly talked about target property was comprehensibility. Documentation, structure and readability were named most frequently as source properties to achieve good comprehensibility. Some of the most important source code properties contributing to code quality as perceived by developers lack clear definitions and are difficult to capture. More research is therefore necessary to measure the structure, comprehensibility and readability of code in ways that matter for developers and to relate these measures of code structure, comprehensibility and readability to common software quality attributes.

Place, publisher, year, edition, pages
Springer, 2023. Vol. 28, no 6, article id 128
National Category
Software Engineering
Research subject
Computer Science, Software Technology
Identifiers
URN: urn:nbn:se:lnu:diva-124897DOI: 10.1007/s10664-023-10381-0ISI: 001073677200001Scopus ID: 2-s2.0-85171886124OAI: oai:DiVA.org:lnu-124897DiVA, id: diva2:1800342
Funder
Blekinge Institute of TechnologyAvailable from: 2023-09-26 Created: 2023-09-26 Last updated: 2024-10-23Bibliographically approved

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Toll, Daniel

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