Title: Combining lexical and structural information for static bug localisation

Authors: Peng Shao; Travis Atkison; Nicholas A. Kraft; Randy K. Smith

Addresses: Department of Computer Science, The University of Alabama, Tuscaloosa, AL 35487-0290, USA ' College of Engineering and Science, Louisiana Tech University, 239 Nethken Hall, Ruston, LA 71272, USA ' Department of Computer Science, The University of Alabama, Tuscaloosa, AL 35487-0290, USA ' Department of Computer Science, The University of Alabama, Tuscaloosa, AL 35487-0290, USA

Abstract: In bug localisation a developer uses information about a bug present in a software system to locate the source code elements that must be modified to correct the bug. Researchers have developed static bug localisation techniques using Information Retrieval techniques such as Latent Semantic Indexing (LSI) to model lexical information from source code. In this paper we present a new technique, LSICG, that combines LSI to model lexical information and call graphs to model structural information. A case study of 21 bugs in Rhino demonstrates that our technique provides improved performance compared to LSI alone.

Keywords: bug localisation; program comprehension; LSI; latent semantic indexing; information retrieval; call graphs; static program analysis; software bugs; lexical information; structural information; modelling.

DOI: 10.1504/IJCAT.2012.048208

International Journal of Computer Applications in Technology, 2012 Vol.44 No.1, pp.61 - 71

Available online: 24 Jul 2012 *

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