Two Efficient Software Techniques to Detect and Correct Control-Flow Errors

Abstract

This paper proposes two efficient software techniques, Control-flow and Data Errors Correction using Data-flow Graph Consideration (CDCC) and Miniaturized Check-Pointing (MCP), to detect and correct control-flow errors. These techniques have been implemented based on addition of redundant codes in a given program. The creativity applied in the methods for online detection and correction of the control-flow errors is using data-flow graph alongside of using control-flow graph. These techniques can detect most of the control-flow errors in the program firstly, and next can correct them, automatically. Therefore, both errors in the control-flow and program data which is caused by control-flow errors can be corrected, efficiently. In order to evaluate the proposed techniques, a post compiler is used, so that the techniques can be applied to every 80X86 binaries, transparently. Three benchmarks quick sort, matrix multiplication and linked list are used, and a total of 5000 transient faults are injected on several executable points in each program. The experimental results demonstrate that at least 93% and 89% of the control-flow errors can be detected and corrected without any data error generation by the CDCC and MCP, respectively. Moreover, the strength of these techniques is significant reduction in the performance and memory overheads in compare to traditional methods, for as much as remarkable correction abilities.