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• W4380354937 abstract "The research on visual analytics for software maintenance has noticeabily advanced in the past few years. For many software projects, software maintenance needs an effective and efficient path from data to decision. Visual analytics (VA) creates such a path that enables the user to extract insights by interacting with the relevant information. This paper focuses on VA in software maintenance and has the following goals: investigate the VA adoption and suggest important implications for practice, and identify current research trends, open problems, and areas for improvement. To achieve these goals we conducted a systematic literature review with three research questions and assessed 51 studies published in the past two decades. The results indicate that there is a lack of collaboration between academic researchers and industry practitioners. This impedes the credibility of the proposed tools and methods due to lack of confidence in industry adoption. Furthermore, in this study we identified the need to expand VA support to other programming languages and software maintenance tasks." @default.
• W4380354937 created "2023-06-13" @default.
• W4380354937 creator A5019682573 @default.
• W4380354937 creator A5077167825 @default.
• W4380354937 date "2023-04-12" @default.
• W4380354937 modified "2023-09-25" @default.
• W4380354937 title "Visual Analytics in Software Maintenance: A Systematic Literature Review" @default.
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• W4380354937 doi "https://doi.org/10.1145/3564746.3587022" @default.
• W4380354937 hasPublicationYear "2023" @default.
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