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Many program comprehension tools use graphs to visualize and analyze source code. The main issue is that existing approaches create graphs overloaded with too much information. Graphs contain hundreds of nodes and even more edges that cross each other. Understanding these graphs and using them for a given program comprehension task is tedious, and in the worst case developers stop using the tools. In this paper we present DA4Java, a graphbased approach for visualizing and analyzing static dependencies between Java source code entities. The main contribution of DA4Java is a set of features to incrementally compose graphs and remove irrelevant nodes and edges from graphs. This leads to graphs that contain significantly fewer nodes and edges and need less effort to understand. A Tool for Visual Understanding of Source Code DependenciesMartin Pinzger, Katja Gräfenhain, Patrick Knab, and Harald C. Gall Department of Informatics, University of Zurich, Switzerland {pinzger,graefenhain,knab,gall}@ifi.uzh.ch AbstractMany program comprehension tools use graphs to visualize and analyze source code. The main issue is that existing approaches create graphs overloaded with too much information. Graphs contain hundreds of nodes and even more edges that cross each other. Understanding these graphs and using them for a given program comprehension task is tedious, and in the worst case developers stop using the tools. In this paper we present DA4Java, a graphbased approach for visualizing and analyzing static dependencies between Java source code entities. The main contribution of DA4Java is a set of features to incrementally compose graphs and remove irrelevant nodes and edges from graphs. This leads to graphs that contain significantly fewer nodes and edges and need less effort to understand.

Software development teams gather valuable data about features and bugs in issue tracking systems. This information can be used to measure and improve the efficiency and effectiveness of the development process. In this paper we present an approach that harnesses the extraordinary capability of the human brain to detect visual patterns. We specify generic visual process patterns that can be found in issue tracking data. With these patterns we can analyze information about effort estimation, and the length, and sequence of problem resolution activities. In an industrial case study we apply our interactive tool to identify instances of these patterns and discuss our observations. Our approach was validated through extensive discussions with multiple project managers and developers, as well as feedback from the project review board. Abstract. Software development teams gather valuable data about features and bugs in issue tracking systems. This information can be used to measure and improve the efficiency and effectiveness of the development process. In this paper we present an approach that harnesses the extraordinary capability of the human brain to detect visual patterns. We specify generic visual process patterns that can be found in issue tracking data. With these patterns we can analyze information about effort estimation, and the length, and sequence of problem resolution activities. In an industrial case study we apply our interactive tool to identify instances of these patterns and discuss our observations. Our approach was validated through extensive discussions with multiple project managers and developers, as well as feedback from the project review board. Visual Patterns in Issue Tracking Data

Issue tracking repositories contain a wealth of information for reasoning about various aspects of software development processes. In this paper, we focus on bug triaging and provide visual means to explore the effort estimation quality and the bug life-cycle of reported problems. Our approach follows the Micro/Macro reading technique and uses a combination of graphical views to investigate details of individual problem reports while maintaining the context provided by the surrounding data population. This enables the detection and detailed analysis of hidden pat-terns and facilitates the analysis of problem report outliers.In an industrial study, we use our approach in various problem report analysis scenarios and answer questions related to effort estimation and resource planning.

Issue tracking repositories contain a wealth of information for reasoning about various aspects of software development processes. In this paper, we focus on bug triaging and provide visual means to explore the effort estimation quality and the bug life-cycle of reported problems.Our approach uses a combination of graphical views to investigate details of individual problem reports while maintaining the context provided by the surrounding data population. This enables the detection and detailed analysis of hidden patterns and facilitates the analysis of problem report outliers.