VA4SM: A Visual Analytics Tool for Software Maintenance
Sandeep Reddivari, Kaihua Liu, R. Sudha Dharani Reddy
Abstract
Sandeep Reddivari, Kaihua Liu, R. Sudha Dharani Reddy
Abstract
Source code can contain a large amount of data to be interpreted by the human reader. This can be a daunting task since the cognitive ability of an individual may not be as efficient as computers. Visual analytics (VA) can be applied in software maintenance to facilitate code comprehension and other maintenance tasks. In this research, we propose a prototype tool called VA4SM, for visualizing important source code information such as static dependencies, structure and code metrics. We discuss the key features of VA4SM and improvements for future work.
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Source code can contain a large amount of data to be interpreted by the human reader. This can be a daunting task since the cognitive ability of an individual may not be as efficient as computers. Visual analytics (VA) can be applied in software maintenance to facilitate code comprehension and other maintenance tasks. In this research, we propose a prototype tool called VA4SM, for visualizing important source code information such as static dependencies, structure and code metrics. We discuss the key features of VA4SM and improvements for future work.
Key concepts: Computer science, Program comprehension, Software analytics, Source code, Visual analytics, Software maintenance, Software visualization, Task (project management)