On integrating orthogonal information retrieval methods to improve traceability recovery

  • Authors:

  • Malcom Gethers;Rocco Oliveto;Denys Poshyvanyk;Andrea De Lucia

  • Affiliations:

  • Computer Science Department, The College of William and Mary, Williamsburg, VA, USA;STAT Department, University of Molise, Pesche (IS), Italy;Computer Science Department, The College of William and Mary, Williamsburg, VA, USA;School of Science, University of Salerno, Fisciano, Italy

  • Venue:
  • ICSM '11 Proceedings of the 2011 27th IEEE International Conference on Software Maintenance
  • Year:
  • 2011

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Abstract

Different Information Retrieval (IR) methods have been proposed to recover traceability links among software artifacts. Until now there is no single method that sensibly outperforms the others, however, it has been empirically shown that some methods recover different, yet complementary traceability links. In this paper, we exploit this empirical finding and propose an integrated approach to combine orthogonal IR techniques, which have been statistically shown to produce dissimilar results. Our approach combines the following IR-based methods: Vector Space Model (VSM), probabilistic Jensen and Shannon (JS) model, and Relational Topic Modeling (RTM), which has not been used in the context of traceability link recovery before. The empirical case study conducted on six software systems indicates that the integrated method outperforms stand-alone IR methods as well as any other combination of non-orthogonal methods with a statistically significant margin.