Many of the approaches for recovering links be- tween e-mails and software artifacts are based on text search or text retrieval. They reformulate the link recovery as a document retrieval problem. We refine and improve such solutions by leveraging the parts of which an e-mail is composed of: header, current message, and previous messages. The relevance of these parts is weighted by a probabilistic approach based on text retrieval. We implemented our novel solution exploiting the BM25F model. The approach has been implemented in an Eclipse plug-in named LASCO (Linking e-mAils and Source Code). We present that plug-in in this tool demonstration paper.
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