4th International Workshop on Requirements Engineering and Testing, Lisbon, Portugal

Abbrevation

RET

Link

http://ret.cs.lth.se/17/

City

Lisbon

Country

Portugal

Deadline Paper

2017-06-09

Start Date

2017-09-05

End Date

2017-09-05

Abstract

THEME AND GOALS The objective of the RET workshop is to explore the interaction of Requirements Engineering (RE) and Testing, in research and industry, and the challenges that result from this interaction. RET provides a forum for exchanging ideas and best practices for aligning RE and testing, and helps foster industry–academia collaboration on this topic. The workshop encourages participant interaction through panel discussions of presented papers, through tool demos and by an interactive session during which the participants together define a roadmap for research in the area of RET. Submissions should either discuss challenges involved in RET alignment, or propose approaches on how to best align RET. This can include processes, practices, artifacts, methods, techniques, tools and softer aspects like the communication between roles in the development lifecycle. We particularly encourage submissions from industrial practitioners or those working with industrial partners. TOPICS OF INTEREST RET′17 solicits papers that discuss both RE and Testing aspects, and the interaction between them. The list of suggested topics is based on the mapping exercise conducted during RET′14: – Processes and practices for supporting RET alignment – Requirements–based testing processes and techniques, e.g. optimizing testing according to req. prioritization – Testability of requirements, impact of requirements quality to test quality – Model–based testing, test–driven and behavior–driven development – Traceability between requirements and tests, also including requirements evolution and regression testing – Metrics for assessing and monitoring RET alignment – Context–specific RET alignment, e.g. for OSS development, continuous deployment, safety–critical systems – RET at different phases of the development lifecycle – Scalability of RET alignment, RET for big data – RET alignment for non–functional and quality requirements – Organizational aspects of RET alignment, including training and education – Automation techniques to support RET (e.g. based on machine learning, information retrieval) – Collaboration and communication between requirements engineers and testers – "Good enough" RET alignment, balancing effort and return of investment – Empirical research on RET alignment – Tools supporting RET alignment, e.g. management, visualization, monitoring