Paper Info
Title
Implementing Traceability Repositories as Graph Databases for Software Quality Improvement
Abstract
Traceability identifies dependencies between software artifacts facilitating the impact analysis of modifications to requirements, design and code. There is limited application of traceability in industry due to the complexity of traceability models and lack of tools. In this paper, we present simplified rules to define trace link types. To store and represent trace links, we implement a traceability repository as a native graph database. This is in contrast to other approaches that use structured files for storage or traceability matrices for representation. In addition, we present a methodology to apply our proposed rules to create trace links using three datasets. We demonstrate the advantage of the graph traceability repository over current representation and storage methods in visualizing traceability links, facilitating the derivation of new trace links and in query response times.
Year
DOI
Venue
2018
10.1109/QRS.2018.00040
2018 IEEE International Conference on Software Quality, Reliability and Security (QRS)
Keywords
Field
DocType
traceability, trace type links, traceability metamodels, graph traceability repositories
Graph,Query language,Graph database,Software engineering,XML,Computer science,Software,Software quality improvement,Traceability,Semantics
Conference
ISBN
Citations 
PageRank 
978-1-5386-7758-2
1
0.36
References 
Authors
13
2
Name
Order
Citations
PageRank
Randa Elamin120.72
Rasha Osman2292.98