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A Study on Guiding Programmers’ Code Navigation with a Graphical Code Recommender

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Software Engineering Research,Management and Applications 2011

Part of the book series: Studies in Computational Intelligence ((SCI,volume 377))

Abstract

While performing an evolution task, programmers spend significant time trying to understand a code base. To facilitate programmers’ comprehension of code, researchers have developed software visualization tools. However, those tools have not predicted the information that programmers seek during their program comprehension activities. To responsively provide informative diagrams in a timely manner, we suggest a graphical code recommender and conduct an iterative Wizard of Oz study in order to examine when and what diagrammatic contents should appear in a graphical view to guide a programmer in exploring source code. We found that programmers positively evaluate a graphical code recommender that changes in response to their code navigation. They favored a graphical view that displays the source locations frequently visited by other programmers during the same task. They commented that the graphical code recommender helped in particular when they were uncertain about where to look while exploring the code base.

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Authors and Affiliations

  1. Department of Computer Science, KAIST, Korea

    Seonah Lee & Sungwon Kang

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  1. Seonah Lee
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  2. Sungwon Kang
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Editors and Affiliations

  1. Computer Science Department, Software Engineering & Information Technology Institute, Central Michigan University, 48859, Mt. Pleasant, MI, USA

    Roger Lee

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Lee, S., Kang, S. (2012). A Study on Guiding Programmers’ Code Navigation with a Graphical Code Recommender. In: Lee, R. (eds) Software Engineering Research,Management and Applications 2011. Studies in Computational Intelligence, vol 377. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23202-2_5

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  • DOI: https://doi.org/10.1007/978-3-642-23202-2_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23201-5

  • Online ISBN: 978-3-642-23202-2

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