xiao-invdetopt-mengthesis

xiao-invdetopt-mengthesis - Performance Enhancements for a...

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Unformatted text preview: Performance Enhancements for a Dynamic Invariant Detector by Chen Xiao Submitted to the Department of Electrical Engineering and Computer Science in partial fulfillment of the requirements for the degree of Master of Engineering in Computer Science and Engineering at the MASSACHUSETTS INSTITUTE OF TECHNOLOGY February 2007 c Massachusetts Institute of Technology 2007. All rights reserved. Author . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Department of Electrical Engineering and Computer Science February 2, 2007 Certified by. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Michael D. Ernst Associate Professor Thesis Supervisor Certified by. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Jeff H. Perkins Research Staff Thesis Supervisor Accepted by . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Arthur C. Smith Chairman, Department Committee on Graduate Students 2 Performance Enhancements for a Dynamic Invariant Detector by Chen Xiao Submitted to the Department of Electrical Engineering and Computer Science on February 2, 2007, in partial fulfillment of the requirements for the degree of Master of Engineering in Computer Science and Engineering Abstract Dynamic invariant detection is the identification of the likely properties about a program based on observed variable values during program execution. While other dynamic invariant detectors use a brute force algorithm, Daikon adds powerful opti- mizations to provide more scalable invariant detection without sacrificing the richness of the reported invariants. Daikon improves scalability by eliminating redundant invariants. For example, the suppression optimization allows Daikon to delay the creation of invariants that are logically implied by other true invariants. Although conceptually simple, the implementation of this optimization in Daikon has a large fixed cost and scales polynomially with the number of program variables. I investigated performance problems in two implementations of the suppression optimization in Daikon and evaluated several methods for improving the algorithm for the suppression optimization: optimizing existing algorithms, using a hybrid, context-sensitive approach to maximize the effectiveness of the two algorithms, and batching applications of the algorithm to lower costs. Experimental results showed a 10% runtime improvement in Daikon runtime. In addition, I implemented an oracle to verify the implementation of these improvements and the other optimizations in Daikon....
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This note was uploaded on 02/24/2012 for the course CSE 503 taught by Professor Davidnotikin during the Spring '11 term at University of Washington.

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xiao-invdetopt-mengthesis - Performance Enhancements for a...

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