TL;DR: This paper describes GenProg, an automated method for repairing defects in off-the-shelf, legacy programs without formal specifications, program annotations, or special coding practices, and analyzes the generated repairs qualitatively and quantitatively to demonstrate the process efficiently produces evolved programs that repair the defect.
Abstract: This paper describes GenProg, an automated method for repairing defects in off-the-shelf, legacy programs without formal specifications, program annotations, or special coding practices. GenProg uses an extended form of genetic programming to evolve a program variant that retains required functionality but is not susceptible to a given defect, using existing test suites to encode both the defect and required functionality. Structural differencing algorithms and delta debugging reduce the difference between this variant and the original program to a minimal repair. We describe the algorithm and report experimental results of its success on 16 programs totaling 1.25 M lines of C code and 120K lines of module code, spanning eight classes of defects, in 357 seconds, on average. We analyze the generated repairs qualitatively and quantitatively to demonstrate that the process efficiently produces evolved programs that repair the defect, are not fragile input memorizations, and do not lead to serious degradation in functionality.
TL;DR: The delta debugging algorithm generalizes and simplifies the failing test case to a minimal test case that still produces the failure, and isolates the difference between a passing and a failingTest case.
Abstract: Given some test case, a program fails. Which circumstances of the test case are responsible for the particular failure? The delta debugging algorithm generalizes and simplifies the failing test case to a minimal test case that still produces the failure. It also isolates the difference between a passing and a failing test case. In a case study, the Mozilla Web browser crashed after 95 user actions. Our prototype implementation automatically simplified the input to three relevant user actions. Likewise, it simplified 896 lines of HTML to the single line that caused the failure. The case study required 139 automated test runs or 35 minutes on a 500 MHz PC.
TL;DR: A new technique that uses color to visually map the participation of each program statement in the outcome of the execution of the program with a test suite, consisting of both passed and failed test cases is presented.
Abstract: One of the most expensive and time-consuming components of the debugging process is locating the errors or faults. To locate faults, developers must identify statements involved in failures and select suspicious statements that might contain faults. This paper presents a new technique that uses visualization to assist with these tasks. The technique uses color to visually map the participation of each program statement in the outcome of the execution of the program with a test suite, consisting of both passed and failed test cases. Based on this visual mapping, a user can inspect the statements in the program, identify statements involved in failures, and locate potentially faulty statements. The paper also describes a prototype tool that implements our technique along with a set of empirical studies that use the tool for evaluation of the technique. The empirical studies show that, for the subject we studied, the technique can be effective in helping a user locate faults in a program.
TL;DR: The experiment reported here shows that programmers also routinely break programs into one kind of coherent piece which is not coniguous.
Abstract: Computer programmers break apart large programs into smaller coherent pieces. Each of these pieces: functions, subroutines, modules, or abstract datatypes, is usually a contiguous piece of program text. The experiment reported here shows that programmers also routinely break programs into one kind of coherent piece which is not coniguous. When debugging unfamiliar programs programmers use program pieces called slices which are sets of statements related by their flow of data. The statements in a slice are not necessarily textually contiguous, but may be scattered through a program.
TL;DR: A fully automated method for locating and repairing bugs in software that works on off-the-shelf legacy applications and does not require formal specifications, program annotations or special coding practices is introduced.
Abstract: Automatic program repair has been a longstanding goal in software engineering, yet debugging remains a largely manual process. We introduce a fully automated method for locating and repairing bugs in software. The approach works on off-the-shelf legacy applications and does not require formal specifications, program annotations or special coding practices. Once a program fault is discovered, an extended form of genetic programming is used to evolve program variants until one is found that both retains required functionality and also avoids the defect in question. Standard test cases are used to exercise the fault and to encode program requirements. After a successful repair has been discovered, it is minimized using structural differencing algorithms and delta debugging. We describe the proposed method and report experimental results demonstrating that it can successfully repair ten different C programs totaling 63,000 lines in under 200 seconds, on average.