Trace links between requirements and software artifacts provide available traceability information and in-depth insights for different stakeholders. Unfortunately, establishing requirements trace links is a tedious, labor-intensive and fallible task. To alleviate this problem, Information Retrieval (IR) methods, such as Vector Space Model (VSM), Latent Semantic Indexing (LSI), and their variants, have been widely used to establish trace links automatically. But with the widespread use of agile development methodology, artifacts that can be used to generate automatic tracing links are getting shorter and shorter, which decreases the effects of traditional IR-based trace link generation methods. In this paper, Biterm Topic Model–Genetic Algorithm (BTM–GA), which is effective in managing short-text artifacts and configuring initial parameters, is introduced. A hybrid method VSM[Formula: see text]BTM–GA is proposed to generate requirements trace links. Empirical experiments conducted on five real and frequently-used datasets indicate that (1) the hybrid method VSM+BTM[Formula: see text]GA outperforms the others, and its results can achieve the “Good” level, where recall and precision are no less than 70% and 30%, respectively; (2) the performance of the hybrid method is stable and (3) BTM–GA can provide a number of “hard-to-find” trace links that complement the candidate trace links of VSM.
Improving Trace Link Recovery Using Semantic Relation Graphs and Spreading Activation
