Academic
Publications
Studying Software Evolution Information by Visualizing the Change History

Studying Software Evolution Information by Visualizing the Change History,10.1109/ICSM.2004.1357818,Filip Van Rysselberghe,Serge Demeyer

Studying Software Evolution Information by Visualizing the Change History   (Citations: 49)
BibTex | RIS | RefWorks Download
Before re-engineering a large and complex software system, it is wise to study its change history in order to identify the most valuable and problematic parts. Unfortunately, typical change histories contain thousands of entries, therefore the challenge is to discover those changes which are relevant for both the current and future situations of our product and process. We demonstrate how a simple visualization allows us to recognize relevant changes. Applying the technique on the change history of Tomcat, we have been able to identify (a) unstable components, (b) coherent entities, (c) design and architectural evolution, and (d) fluctuations in team productivity.
Cumulative Annual
View Publication
The following links allow you to view full publications. These links are maintained by other sources not affiliated with Microsoft Academic Search.
    • ...As studying the history of software projects involves large amounts of data, visualization can help to deal with the resulting complexity and to understand aspects of either product or process (Ball and Eick 1996; Van Rysselberghe and Demeyer 2004)...
    • ...As such, the Change History View is loosely based on work of Gîrba and Ducasse (2006) and Van Rysselberghe and Demeyer (2004), while the Growth History View has its roots in work of, e.g., Godfrey and Tu (2000)...
    • ...changed files. Other patterns not specifically involving the tests, e.g., vertical or horizontal blue bars, have been studied by others (Van Rysselberghe and Demeyer 2004 ;G all et al.1998)...
    • ...Van Rysselberghe and Demeyer (2004) use a very simple, yet effective visualization of the history of a software system in order to identify the most valuable and problematic parts of a software system...

    Andy Zaidmanet al. Studying the co-evolution of production and test code in open source a...

    • ...Researchers have demonstrated that versioning information can not only help to predict future evolutionary trends [21], [34], but can also provide starting points for reengineering activities [15]...
    • ...We use visualization [7], [28] because it provides effective ways to break down the complexity of information, and because it has shown to be a successful means to study the evolution of software systems [2], [9], [16], [17], [22], [31], [34]...
    • ...Van Rysselberghe and Demeyer used a simple visualization based on information in version control systems to provide an overview of the evolution of a system [34]...

    Marco D'ambroset al. Visualizing Co-Change Information with the Evolution Radar

    • ...Another timeline view of source code files focusing on cluster recognition was proposed by van Rysselberghe and Demeyer [14]...

    Christoph Treudeet al. ConcernLines: A timeline view of co-occurring concerns

    • ...Its goal is to use the history of a software system to analyse and understand its present state and to predict its future development [4, 14, 15, 23, 28]...
    • ...Visualization has long been used in software evolution research to break down the data quantity and complexity [2, 17, 19, 24, 26, 28]...
    • ...Rysselberghe and Demeyer [28] used a simple visualization of CVS data to recognize relevant changes in the software system such as: (1) unstable components, (2) coherent entities, (3) design and architectural evolut ion, and (4) fluctuations in team productivity...

    Marco D'Ambroset al. Visual software evolution reconstruction

    • ...Many approaches based on evolutionary information demonstrated that not only can this information be used to predict a system’s future evolution [17], [24], but it can also provide good starting points for reengineering activities [12]...

    Marco D'ambroset al. On the Relationship Between Change Coupling and Software Defects

Sort by: