Paper Info
Title
A Literature Review of Automatic Traceability Links Recovery for Software Change Impact Analysis
Abstract
ABSTRACTIn large-scale software development projects, change impact analysis (CIA) plays an important role in controlling software design evolution. Identifying and accessing the effects of software changes using traceability links between various software artifacts is a common practice during the software development cycle. Recently, research in automated traceability-link recovery has received broad attention in the software maintenance community to reduce the manual maintenance cost of trace links by developers. In this study, we conducted a systematic literature review related to automatic traceability link recovery approaches with a focus on CIA. We identified 33 relevant studies and investigated the following aspects of CIA: traceability approaches, CIA sets, degrees of evaluation, trace direction and methods for recovering traceability link between artifacts of different types. Our review indicated that few traceability studies focused on designing and testing impact analysis sets, presumably due to the scarcity of datasets. Based on the findings, we urge further industrial case studies. Finally, we suggest developing traceability tools to support fully automatic traceability approaches, such as machine learning and deep learning.
Year
DOI
Venue
2020
10.1145/3387904.3389251
International Conference on Software Engineering
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Thazin Win Win Aung111.02
Huan Huo23510.00
Yulei Sui332933.34