DocumentCode
1634336
Title
Application of reinforcement learning to requirements engineering: requirements tracing
Author
Sultanov, Hakim ; Hayes, Jane Huffman
Author_Institution
Univ. of Kentucky, Lexington, KY, USA
fYear
2013
Firstpage
52
Lastpage
61
Abstract
We posit that machine learning can be applied to effectively address requirements engineering problems. Specifically, we present a requirements traceability method based on the machine learning technique Reinforcement Learning (RL). The RL method demonstrates a rather targeted generation of candidate links between textual requirements artifacts (high level requirements traced to low level requirements, for example). The technique has been validated using two real-world datasets from two problem domains. Our technique demonstrated statistically significant better results than the Information Retrieval technique.
Keywords
formal verification; learning (artificial intelligence); program diagnostics; RL method; machine learning technique; reinforcement learning; requirements engineering; requirements traceability method; textual requirements artifacts; Educational institutions; Joining processes; Learning (artificial intelligence); Navigation; Software; Vocabulary; Research Project 2 of Grand Challenges of Traceability; Ubiquitous Grand Challenge; information retrieval; machine learning; reinforcement learning; requirements traceability; software engineering;
fLanguage
English
Publisher
ieee
Conference_Titel
Requirements Engineering Conference (RE), 2013 21st IEEE International
Conference_Location
Rio de Janeiro
Type
conf
DOI
10.1109/RE.2013.6636705
Filename
6636705
Link To Document