DocumentCode
2860734
Title
An Improving Approach for Recovering Requirements-to-Design Traceability Links
Author
Di, Fangshu ; Zhang, Maolin
Author_Institution
Comput. Sci. Dept., Beihang Univ., Beijing, China
fYear
2009
fDate
11-13 Dec. 2009
Firstpage
1
Lastpage
6
Abstract
Requirement tracing is an important activity for its helpfulness to effective system quality assurance, impact analyzing of changes and software maintenance. In this paper, we propose an automatic approach called LGRTL to recover traceability links between high-level requirements and low-level design elements. This approach treats the recovery process as Bayesian classification process. Meanwhile, we add a synonym process to the preprocessing phase, and improve the Bayesian model for performing better. To evaluate the validity of the method, we perform a case study and the experimental results show that our method can enhance the effect to a certain extent.
Keywords
Bayes methods; formal specification; pattern classification; software maintenance; software quality; Bayesian classification; Bayesian model; high-level requirement; learning and generating requirements traceability links; low-level design element; recovery process; requirement tracing; requirements-to-design traceability links; software maintenance; system quality assurance; Bayesian methods; Computer science; Data mining; Information retrieval; Niobium compounds; Performance evaluation; Programming profession; Quality assurance; Software maintenance; Thesauri;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-4507-3
Electronic_ISBN
978-1-4244-4507-3
Type
conf
DOI
10.1109/CISE.2009.5366024
Filename
5366024
Link To Document