Abstract
[Context and motivation] Conversations around requirements, such as interviews and workshops, are a key activity of requirements elicitation, and play a significant role in the creation of requirements specifications. [Question/problem] While these conversations contain a wealth of knowledge, requirements engineers use them mainly through note-taking during the conversation and by recalling the information from their memory. There is potential for supporting practitioners by retrieving important information from the recordings of these conversations. [Principal ideas/results] Although transcriptions can be automatically generated with good accuracy, they often contain excessive text to be efficiently used for processing requirements elicitation sessions. Thus, we observed a need to transform these datasets into a useful format for requirements engineers to analyze. [Contribution] We present RECONSUM, a prototype that utilizes Natural Language Processing (NLP) to summarize requirements conversations. RECONSUM takes as input a transcribed conversation, and it filters the speaker turns by keeping only those that include a question and that are expected to contain, or to be answered with, requirements-relevant information. In addition to presenting RECONSUM, we experiment with different algorithms to assess the most effective combination.
Original language | English |
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Title of host publication | Proceedings of the 29th International Working Conference on Requirements Engineering: Foundation for Software Quality (REFSQ 2023) |
Subtitle of host publication | Foundation for Software Quality - 29th International Working Conference, REFSQ 2023, Proceedings |
Editors | Alessio Ferrari, Birgit Penzenstadler |
Pages | 122-139 |
Number of pages | 18 |
DOIs | |
Publication status | Published - 2023 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 13975 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Bibliographical note
Funding Information:We thank all the participants who acted as taggers. The use of the recorded and transcribed dataset is made possible thanks to the ethical Science-Geosciences Ethics Review Board of Utrecht University (case S-20339).
Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Keywords
- Requirements Elicitation
- Natural Language Processing
- Conversational RE
- Requirements-Relevant Information