Please use this identifier to cite or link to this item: https://doi.org/10.1002/smr.375
Title: Mining temporal rules for software maintenance
Authors: Lo, D.
Khoo, S.-C. 
Liu, C.
Keywords: Data mining
Dynamic analysis
Program comprehension
Program verification
Software evolution
Specification mining
Issue Date: 2008
Source: Lo, D., Khoo, S.-C., Liu, C. (2008). Mining temporal rules for software maintenance. Journal of Software Maintenance and Evolution 20 (4) : 227-247. ScholarBank@NUS Repository. https://doi.org/10.1002/smr.375
Abstract: Software evolution incurs difficulties in program comprehension and software verification, and hence it increases the cost of software maintenance. In this study, we propose a novel technique to mine from program execution traces a sound and complete set of statistically significant temporal rules of arbitrary lengths. The extracted temporal rules reveal invariants that the program observes, and will consequently guide developers to understand the program behaviors, and facilitate all downstream applications such as verification and debugging. Different from previous studies that were restricted to mining two-event rules (e.g., (lock) → (unlock)), our algorithm discovers rules of arbitrary lengths. In order to facilitate downstream applications, we represent the mined rules as temporal logic expressions, so that existing model checkers or other formal analysis toolkit can readily consume our mining results. Performance studies on benchmark data sets and a case study on an industrial system have been performed to show the scalability and utility of our approach. We performed case studies on JBoss application server and a buggy concurrent versions system application, and the result clearly demonstrates the usefulness of our technique in recovering underlying program designs and detecting bugs. Copyright © 2008 John Wiley & Sons, Ltd.
Source Title: Journal of Software Maintenance and Evolution
URI: http://scholarbank.nus.edu.sg/handle/10635/41451
ISSN: 1532060X
DOI: 10.1002/smr.375
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