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 :
بازگشت