Can you Trust a Single Data Source Exploratory Software Engineering Case Study

Abstract

As the demand for empirical evidence for claims of improvements in software development and evolution has increased, the use of empirical methods such as case studies has grown. In case study methodology various types of triangulation is a commonly recommended technique for increasing validity. This study investigates a multiple data source case study with the objective of identifying whether more findings, trustworthier findings and other findings are made using multiple data source triangulation, than had a single data source been used. The case study investigated analyses key lead-time success factors for a software evolution project in a large organization developing eBusiness systems with high-availability high throughput transaction characteristics. By tracing each finding in that study to the individual evidences motivating the finding, it is suggested that a multiple data source explorative case study can have a higher validity than a single data source study. It is concluded that a careful case study design with multiple sources of evidence can result in not only better justified findings than a single data source study, but also other findings. Thus this study provides empirically derived evidence that a multiple data source case study is more trustworthy than a comparable single data source case study.