DEPARTMENT OF COMPUTER SCIENCE
DOCTORAL DISSERTATION DEFENSE


Candidate: Tarak Goradia
Advisor: Elaine Weyuker

Dynamic Impact Analysis:
Analyzing Error Propagation in Program Executions

11:00 a.m., Wednesday, December 15, 1993
719 Broadway, 12th floor conference room




Abstract

Test adequacy criteria serve as rules to determine whether a test set adequately tests a program. The effectiveness of a test adequacy criterion is determined by its ability to detect faults. For a test case to detect a specific fault, it should execute the fault, cause the fault to generate an erroneous state and propagate the error to the output. Analysis of previously proposed code-based testing strategies suggests that satisfying the error propagation condition is both important and expensive. The technique of dynamic impact analysis is proposed for analyzing a program execution and estimating the error propagation behavior of various potential sources of errors in the execution. Impact graphs are introduced to provide an infrastructure supporting the analysis. A program impact graph modifies the notion of a program dependence graph proposed in the literature in order to capture some of the subtle impact relationships that exist in a program. An execution impact graphs represents the dynamic impact relationships that are demonstrated during a program execution. The notion of impact strength is defined as a quantitative measure of the error sensitivity of an impact. A cost-effective algorithm for analyzing impact relationships in an execution and computing the impact strengths is presented. A research prototype implemented to demonstrate the feasibility of dynamic impact analysis is briefly described. The time complexity of dynamic impact analysis is shown to be linear with respect to the original execution time, and experimental measurements indicate that the constant of proportionality is a small number. The experiments undertaken to validate the computation of impact strengths are presented. An experience study relating impact strengths to error propagation in faulty programs is also presented. The empirical results provide evidence indicating a strong positive correlation between impact strength and error propagation. The results also emphasize the need for better heuristics to improve the accuracy of the error propagation estimates. Potential applications of dynamic impact analysis to mutation testing, syntactic coverage-based testing and dynamic program slicing are discussed.