In application domains that are regulated, software vendors must maintain traceability links between the regulatory items and the code base implementing them. In this paper, we present a traceability approach based on the intuition that the regulatory documents and the user-interface of the corresponding software applications are very close. First, they use the same terminology. Second, most important regulatory pieces of information appear in the graphical user-interface because the end-users in those application domains care about the regulation (by construction). We evaluate our approach in the domain of green building. The evaluation involves a domain expert, lead architect of a commercial product within this area. The evaluation shows that the recovered traceability links are accurate.
De @cite_12 developed ADAMS, a traceability link recovery tool based on latent semantic indexing to retrieve traceability links. Leuser and Ott use a tool called TraceTool @cite_2 implementing two IR algorithms (tf idf and LSI) to evaluate various optimizations on large specifications written in German. generalized this approach with Traceclipse, an Eclipse plug-in providing a generic platform for integrating traceability link recovery into an IDE @cite_7 . Those authors do not explore the terminological richness of user-interface labels.
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Traceability link recovery is an active research area in software engineering with a number of open research questions and challenges, due to the substantial costs and challenges associated with software maintenance. We propose Traceclipse, an Eclipse plug-in that integrates some similar characteristics of traceability link recovery techniques in one easy-to-use suite. The tool enables software developers to specify, view, and manipulate traceability links within Eclipse and it provides an API through which recovery techniques may be added, specified, and run within an integrated development environment. The paper also presents initial case studies aimed at evaluating the proposed plug-in. The main drawback of existing software artifact management systems is the lack of automatic or semi-automatic traceability link generation and maintenance. We have improved an artifact management system with a traceability recovery tool based on Latent Semantic Indexing (LSI), an information retrieval technique. We have assessed LSI to identify strengths and limitations of using information retrieval techniques for traceability recovery and devised the need for an incremental approach. The method and the tool have been evaluated during the development of seventeen software projects involving about 150 students. We observed that although tools based on information retrieval provide a useful support for the identification of traceability links during software development, they are still far to support a complete semi-automatic recovery of all links. The results of our experience have also shown that such tools can help to identify quality problems in the textual description of traced artifacts. An information retrieval technique, latent semantic indexing, is used to automatically identify traceability links from system documentation to program source code. The results of two experiments to identify links in existing software systems (i.e., the LEDA library, and Albergate) are presented. These results are compared with other similar type experimental results of traceability link identification using different types of information retrieval techniques. The method presented proves to give good results by comparison and additionally it is a low cost, highly flexible method to apply with regards to preprocessing and or parsing of the source code and documentation. Traceability provides support for diverse software engineering activities including safety analysis, compliance verification, test-case selection, and impact prediction. However, in practice, there is a tendency for trace links to degrade over time as the system continually evolves. This is especially true for links between source-code and upstream artifacts such as requirements --- because developers frequently refactor and change code without updating the links. In this paper we present TLE (Trace Link Evolver), a solution for automating the evolution of bidirectional trace links between source code classes or methods and requirements. TLE depends on a set of heuristics coupled with refactoring detection tools and informational retrieval algorithms to detect predefined change scenarios that occur across contiguous versions of a software system. We first evaluate TLE at the class level in a controlled experiment to evolve trace links for revisions of two Java applications. Second, we comparatively evaluate several variants of TLE across six releases of our in-house Dronology project. We study the results of integrating human analyst feed back in the evolution cycle of this emerging project. Additionally, in this system, we compare the efficacy of class-level versus method-level evolution of trace links. Finally, we evaluate TLE in a larger scale across 27 releases of the Cassandra Database System and show that the evolved trace links are significantly more accurate than those generated using only information retrieval techniques.