Towards Automated Test Practice Detection and Governance

• Published in: 2009 First International Conference on Advances in System Testing and Validation Lifecycle pp. 19 - 24
• Main Author: Oberhauser, R.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.09.2009
• Subjects: automated test practice detection; Automatic testing; complex event processing; Data analysis; Data engineering; Event detection; Face detection; ISO standards; process-aware information systems; Quality assurance; Software engineering; software engineering environments; Software testing; System testing; test-driven development
• ISBN: 142444862X; 9781424448623
• DOI: 10.1109/VALID.2009.25

The selection, monitoring, and adjustment of quality measures are fundamental to software engineering, and testing is a key quality assurance activity. In Small and Medium Enterprises (SMEs), it is often difficult and time consuming to manually ascertain the degree and type of test practice usage and related process compliance, thus such data collection may be omitted. Moreover, any manual data collection may not be objective, comprehensive, and dependable, since manual collection cannot typically be done transparently with software engineers. Considering test-driven development, the intention and the order of programming are important, and few clues are left ex post that can be objectively verified. This paper presents an approach that enables an automatic test practice detection capability using the SEEEK (Software Engineering Environment Event-driven framework) to support adaptable processes while ensuring process compliance and supporting governance. The results show the feasibility of this approach for automatically detecting test practices and adjusting developer task management accordingly.