We are inviting IDEALS users, both people looking for materials in IDEALS and those who want to deposit their work, to give us feedback on improving this service through an interview. Participants will receive a $20 VISA gift card. Please sign up via https://forms.illinois.edu/sec/4069811

Files in this item

FilesDescriptionFormat

application/pdf

application/pdfPredicting Conc ... using Sliced Causality.pdf (157kB)
(no description provided)PDF

Description

Title:Predicting Concurrency Errors at Runtime using Sliced Causality
Author(s):Chen, Feng; Rosu, Grigore
Subject(s):computer science
Abstract:A runtime analysis technique is presented, which can predict concurrency errors in multithreaded systems by observing potentially non-erroneous executions. It builds upon a novel causal partial order, sliced causality, that weakens the classic but strict "happens-before" by using both static information about the program, such as control- and data-flow dependence, and dynamic synchronization information, such as lock-sets. A vector clock algorithm is introduced to automatically extract a sliced causality from any execution. A memory-efficient procedure then checks all causally consistent potential runs against properties given as monitors. If any of these runs violates a property, it is returned as a "predicted" counter-example. This runtime analysis technique is sound (no false alarms) but not complete (says nothing about code that was not covered). A prototype called jPredictor has been implemented and evaluated on several Java applications with promising results.
Issue Date:2006-04
Genre:Technical Report
Type:Text
URI:http://hdl.handle.net/2142/11455
Other Identifier(s):UIUCDCS-R-2006-2965
Rights Information:You are granted permission for the non-commercial reproduction, distribution, display, and performance of this technical report in any format, BUT this permission is only for a period of 45 (forty-five) days from the most recent time that you verified that this technical report is still available from the University of Illinois at Urbana-Champaign Computer Science Department under terms that include this permission. All other rights are reserved by the author(s).
Date Available in IDEALS:2009-04-22


This item appears in the following Collection(s)

Item Statistics