University of Illinois Urbana-Champaign

Scalable Automated Methods for Dynamic Program Analysis

Sen, Koushik

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Scalable Automated Methods for Dynamic Program Analysis.pdf

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https://hdl.handle.net/2142/11198

Description

Title
Scalable Automated Methods for Dynamic Program Analysis
Author(s)
Sen, Koushik
Issue Date
2006-06
Keyword(s)
computer science
Date of Ingest
2009-04-21T14:43:51Z
Abstract
Testing using manually generated test cases is the primary technique used in industry to improve reliability of software---in fact, such ad hoc testing accounts for over half of the typical cost of software development. We propose new methods for systematically and automatically testing sequential and concurrent programs. The methods are based on three new techniques: concolic testing, race-detection and flipping, and predictive monitoring. Concolic testing combines concrete and symbolic testing to avoid redundant test cases as well as false warnings. Concolic testing can catch generic errors such as assertion violations, uncaught exceptions, and segmentation faults. Large real-world programs are almost always concurrent. Because of the inherent non-determinism of such programs, testing is notoriously hard. We extend concolic testing with a method called race-detection and flipping, which provides ways of reducing, often exponentially, the exploration space for concolic testing. This combined method provides the first technique to effectively test concurrent programs with complex data inputs. Concolic testing may also be combined with formal specifications by using runtime monitors. Runtime monitors are small software units which are synthesized automatically from the formal specification for the software and weaved into the code to dynamically check if the specification is violated. For multi-threaded concurrent programs, we developed a novel technique which allows efficient predictive monitoring to enable the detection of a violation by observing some related, but possibly bug-free execution of a concurrent program. Predictive monitoring dramatically improves the efficiency of testing. Based on the above methods we have developed tools for testing both C and Java programs. We have used the tools to find bugs in several real-world software systems including SGLIB, a popular C data structure library used in a commercial tool, implementations of the Needham-Schroeder protocol and the TMN protocol, the scheduler of Honeywell's DEOS real-time operating system, and the Sun Microsystems' JDK 1.4 collection framework.
Type of Resource
text
Genre of Resource
Technical Report
Permalink
http://hdl.handle.net/2142/11198
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