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Model checking driven static analysis for the real world: designing and tuning large scale bug detection

Fehnker, Ansgar and Huuck, R. (2013) Model checking driven static analysis for the real world: designing and tuning large scale bug detection. Innovations in Systems and Software Engineering, 9 (1). pp. 45-56. ISSN 1614-5046

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Abstract

Model checking and static analysis are traditionally seen as two separate approaches to software analysis and verification. In this work we define a model, checking approach for the static analysis of large C/C++ source code bases to detect potential run-time issues such as program crashes, security vulnerabilities and memory leaks. Working on the intersection of software model checking and automated static bug detection for real-life systems, we address a number of issues: how to scale for real-life systems of 1,000,000 LoC or more, how to quickly write new checks, and most importantly how to distinguish between relevant and irrelevant bugs and fine tune the analysis accordingly. We define our model checking-based static analysis approach implemented in our tool Goanna, illustrate a number of design and implementation decisions to obtain practical outcomes and relevant results, and present our findings by empirical data obtained from regularly analyzing large industrial and open source code bases such as the Firefox Web browser.

Item Type: Journal Article
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science, Technology and Environment (FSTE) > School of Computing, Information and Mathematical Sciences
Depositing User: Ansgar Fehnker
Date Deposited: 01 May 2013 03:03
Last Modified: 15 Jun 2016 03:03
URI: http://repository.usp.ac.fj/id/eprint/5711
UNSPECIFIED

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