Control Flow Error Detection
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Error Detection And Correction
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control flow error detection and correlation with system performance deviationArticle in Journal of Computer and System Sciences 80(5) · August 2014 with 28 ReadsDOI: 10.1016/j.jcss.2014.02.004 1st Atef Shalan2nd Mohammad ZulkernineAbstractDepending on the role https://www.researchgate.net/publication/260167939_Software_control_flow_error_detection_and_correlation_with_system_performance_deviation of software in everyday life, the cost of failure can sometimes be unaffordable. Detecting runtime errors helps avoid the cost of failures and enables systems to perform corrective actions prior to failure occurrences. Control flow errors are major impairments of system dependability during component interactions. Existing control flow monitors are susceptible to false negatives due to possible inaccuracies of the error detection underlying control flow representations. Moreover, avoiding performance overhead and program modifications are major challenges in these monitoring techniques. In this paper, we utilize a Connection Dependence Graph (CDG) representation of software control flow to construct a connection-based signature approach for detecting errors among component interactions. We analyze the monitored system performance and examine the relationship of the captured error state parameters error detection and with the system performance deviation. Using a large open-source software (PostgreSQL 8.4.4 database system) with randomly injected errors, the experimental evaluation results show a decrease in false negatives using our approach relative to the existing techniques. It also demonstrates a significant ability of identifying the responsible components and error state patterns for system performance deviation.Do you want to read the rest of this article?Request full-text CitationsCitations0ReferencesReferences32A Connection-Based Signature Approach for Control Flow Error Detection[Show abstract] [Hide abstract] ABSTRACT: Control Flow Errors (CFEs) are major impairments of software system correctness. These CFEs can be caused by operational faults with respect to the execution environment of a software system. Several techniques are proposed to monitor the control flow using signature-based approaches. These techniques partition a software program into branch-free blocks and assign a unique signature for each block. They detect CFEs by comparing the runtime signatures of these blocks with pre-computed signatures based on the program Control Flow Graph (CFG). Unfortunately, branch-free block partitioning does not completely include all the program connections. Consequently, these techniques may fail to detect some invalid