Authors:
Daniel Atzberger
;
Tim Cech
;
Adrian Jobst
;
Willy Scheibel
;
Daniel Limberger
;
Matthias Trapp
and
Jürgen Döllner
Affiliation:
Hasso Plattner Institute, Digital Engineering Faculty, University of Potsdam, Germany
Keyword(s):
Topic Modeling, Software Visualization, Source Code Mining.
Abstract:
In order to detect software risks at an early stage, various software visualization techniques have been developed for monitoring the structure, behaviour, or the underlying development process of software. One of greatest risks for any IT organization consists in an inappropriate distribution of knowledge among its developers, as a projects’ success mainly depends on assigning tasks to developers with the required skills and expertise. In this work, we address this problem by proposing a novel Visual Analytics framework for mining and visualizing the expertise of developers based on their source code activities. Under the assumption that a developer’s knowledge about code is represented directly through comments and the choice of identifier names, we generate a 2D layout using Latent Dirichlet Allocation together with Multidimensional Scaling on the commit history, thus displaying the semantic relatedness between developers. In order to capture a developer’s expertise in a concept,
we utilize Labeled LDA trained on a corpus of Open Source projects. By mapping aspects related to skills onto the visual variables of 3D glyphs, we generate a 2.5D Visualization, we call KnowhowMap. We exemplify this approach with an interactive prototype that enables users to analyze the distribution of skills and expertise in an explorative way.
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