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Vetting automatically generated trace links: What information is useful to human analysts?

Conference paper
Authors Salome Maro
Jan-Philipp Steghöfer
Jane Hayes
Jane Cleland-Huang
Miroslaw Staron
Published in Proceedings - 2018 IEEE 26th International Requirements Engineering Conference, RE 2018
Publication year 2018
Published at Department of Computer Science and Engineering (GU)
Software Center
Institutionen för data- och informationsteknik, Software Engineering (GU)
Language en
Keywords Automated traceability, Requirements traceability, Traceability
Subject categories Software Engineering, Computer Science

Abstract

© 2018 IEEE. Automated traceability has been investigated for over a decade with promising results. However, a human analyst is needed to vet the generated trace links to ensure their quality. The process of vetting trace links is not trivial and while previous studies have analyzed the performance of the human analyst, they have not focused on the analyst's information needs. The aim of this study is to investigate what context information the human analyst needs. We used design science research, in which we conducted interviews with ten practitioners in the traceability area to understand the information needed by human analysts. We then compared the information collected from the interviews with existing literature. We created a prototype tool that presents this information to the human analyst. To further understand the role of context information, we conducted a controlled experiment with 33 participants. Our interviews reveal that human analysts need information from three different sources: 1) from the artifacts connected by the link, 2) from the traceability information model, and 3) from the tracing algorithm. The experiment results show that the content of the connected artifacts is more useful to the analyst than the contextual information of the artifacts.

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