Quality assessment of large industrial systems, both for maintenance or migration purposes, mounts a serious challenge. Large systems usually contain millions of lines of code spread over thousands of modules; their development involves many person-years of effort, and their documentation is missing or outdated. To a large extent, knowl- edge about such systems is lost, hindering their maintenance. Hence, expert assessment of the code quality is an essential prerequisite for successful maintenance activities. However, and despite of the availability of supporting tools, the assessment itself poses high demands pertaining to automated data gathering, analysis and interpretation. The focus of this paper is on reporting experiences on quality assessment of large legacy systems. We start by presenting an integrated assessment approach. The approach consists of two main steps: analysis, including the retrieval of structural and metric information from the code, and visualization of the data extracted. The approach has been implemented in Software Quality Assessment and Visualization Toolset (SQuAVisiT). We proceed with experiences of applying SQuAVisiT in a number of industrial case studies which constitutes the core of the paper.
|Title of host publication||Proceedings Third International Workshop on Software Quality and Maintainability (SQM'09, Kaiserslautern, Germany, March 24, 2009; in conjunction with CSMR'09)|
|Publisher||IEEE Computer Society|
|Publication status||Published - 2009|