Master data has been revealed as one of the most potent instruments to guarantee adequate levels of data quality. The main contribution of this paper is a data quality model to guide repeatable and homogeneous evaluations of the level of data quality of master data repositories. This data quality model follows several international open standards: ISO/IEC 25012, ISO/IEC 25024, and ISO 8000-1000, enabling compliance certification. A case study of applying the data quality model to an organizational master data repository has been carried out to demonstrate the applicability of the data quality model.
Pub. online:2 Jun 2021Type:Research ArticleOpen Access
Volume 32, Issue 3 (2021), pp. 619–660
Code repositories contain valuable information, which can be extracted, processed and synthesized into valuable information. It enabled developers to improve maintenance, increase code quality and understand software evolution, among other insights. Certain research has been made during the last years in this field. This paper presents a systematic mapping study to find, evaluate and investigate the mechanisms, methods and techniques used for the analysis of information from code repositories that allow the understanding of the evolution of software. Through this mapping study, we have identified the main information used as input for the analysis of code repositories (commit data and source code), as well as the most common methods and techniques of analysis (empirical/experimental and automatic). We believe the conducted research is useful for developers working on software development projects and seeking to improve maintenance and understand the evolution of software through the use and analysis of code repositories.