Software evolution visualization: A systematic mapping study

  • Authors:

  • Renato Lima Novais;André Torres;Thiago Souto Mendes;Manoel Mendonça;Nico Zazworka

  • Affiliations:

  • Computer Science Department, Federal University of Bahia, Bahia, Brazil and Information Technology Department, Federal Institute of Bahia, Campus Santo Amaro, Bahia, Brazil;Computer Science Department, Federal University of Bahia, Bahia, Brazil;Computer Science Department, Federal University of Bahia, Bahia, Brazil and Information Technology Department, Federal Institute of Bahia, Campus Santo Amaro, Bahia, Brazil;Computer Science Department, Federal University of Bahia, Bahia, Brazil and Fraunhofer Project Center for Software and Systems Engineering, Bahia, Brazil;Fraunhofer Center for Experimental Software Engineering, MD, USA

  • Venue:
  • Information and Software Technology
  • Year:
  • 2013

Quantified Score

Hi-index 0.00

Visualization

Abstract

Background: Software evolution is an important topic in software engineering. It generally deals with large amounts of data, as one must look at whole project histories as opposed to their current snapshot. Software visualization is the field of software engineering that aims to help people to understand software through the use of visual resources. It can be effectively used to analyze and understand the large amount of data produced during software evolution. Objective: This study investigates Software Evolution Visualization (SEV) approaches, collecting evidence about how SEV research is structured, synthesizing current evidence on the goals of the proposed approaches and identifying key challenges for its use in practice. Methods: A mapping study was conducted to analyze how the SEV area is structured. Selected primary studies were classified and analyzed with respect to nine research questions. Results: SEV has been used for many different purposes, especially for change comprehension, change prediction and contribution analysis. The analysis identified gaps in the studies with respect to their goals, strategies and approaches. It also pointed out to a widespread lack of empirical studies in the area. Conclusion: Researchers have proposed many SEV approaches during the past years, but some have failed to clearly state their goals, tie them back to concrete problems, or formally validate their usefulness. The identified gaps indicate that there still are many opportunities to be explored in the area.