Preview |
PDF, English
- main document
Download (861kB) | Lizenz: Creative Commons Attribution 4.0 |
Abstract
During the elicitation and implementation of requirements, the involved stakeholders make decisions and build up important decision knowledge, which they should make explicit and share. Issue tracking and version control systems offer opportunities for a lightweight capture of decision knowledge but currently lack techniques for making this knowledge explicit.
In this paper, we present techniques to make decision knowledge explicit in the text of issue tracking and version control systems. We present features for its manual documentation as well as for its automatic identification using a text classifier. The text classifier identifies implicit decision knowledge in natural language texts, in particular, in the description and comments of tickets in the issue tracking system and commit messages.
Document type: | Conference Item |
---|---|
Publisher: | CEUR-WS.org |
Date Deposited: | 10 May 2021 14:05 |
Date: | 2021 |
Number of Pages: | 9 |
Event Dates: | 12.04.2021 |
Event Location: | Essen (Germany)/Virtual |
Event Title: | Joint Proceedings of REFSQ-2021 Workshops, OpenRE, Posters and Tools Track, and Doctoral Symposium |
Faculties / Institutes: | The Faculty of Mathematics and Computer Science > Department of Computer Science |
DDC-classification: | 000 Generalities, Science 004 Data processing Computer science |
Uncontrolled Keywords: | Rationale Management, Decision Knowledge, Text Classification, Natural Language Processing, ConDec |