Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-642-24559-6_32
Title: Extracting significant specifications from mining through mutation testing
Authors: Nguyen, A.C.
Khoo, S.-C. 
Keywords: formal specifications
mutation testing
Specification mining
Issue Date: 2011
Citation: Nguyen, A.C.,Khoo, S.-C. (2011). Extracting significant specifications from mining through mutation testing. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 6991 LNCS : 472-488. ScholarBank@NUS Repository. https://doi.org/10.1007/978-3-642-24559-6_32
Abstract: Specification mining techniques are used to automatically infer interaction specifications among objects in the format of call sequences, but many of these specifications can be meaningless or insignificant. As a consequence, when used in program testing or formal verification, the presence of these leads to false positive defects, which in turn demand much effort for manual investigation. We propose a novel process for determining and extracting significant specifications from a set of mined specifications using mutation testing. The resulting specifications can then be used with program verification to detect defects with high accuracy. To our knowledge, this is the first fully automatic approach for extracting significant specifications from mining using program testing. We evaluate our approach through mining significant specifications for the Java API and use them to find real defects in many systems. © 2011 Springer-Verlag.
Source Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
URI: http://scholarbank.nus.edu.sg/handle/10635/40048
ISBN: 9783642245589
ISSN: 03029743
DOI: 10.1007/978-3-642-24559-6_32
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.