Guiding software quality assurance activities through data analytics : Case M-Files

Nowadays, utilizing data in decision-making has become an important topic in organizations. Data is constantly gathered from organizations' internal and external sources, but the full potential of data has not been utilized to maximum extent. The software development context involves a lot of decisions regarding resourcing and prioritization, that are difficult to solve based on intuition. The purpose of this thesis is to find ways for software development quality assurance team to guide testing efforts based on data, instead of intuition. This case study research was conducted for a company that develops an intelligent information management system for customers globally. More specifically, the research was conducted for the quality assurance team within the product development organization of the case company. The challenge in quality assurance is the constantly growing software product that has increasing demand in testing resources. The results of this thesis reveal that the QA team in the case company has so far performed well in ensuring quality of the product, but some improvement areas were identified. The research identified relevant information needs and data sources, that could support the optimization of testing activities. This thesis provides a framework including suggestions how to guide and develop quality assurance activities