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183
Automatically Finding Patches Using Genetic Programming ∗
"... 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 specif ..."
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Cited by 146 (24 self)
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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. 1
An Indexed Bibliography of Genetic Algorithms in Power Engineering
, 1995
"... s: Jan. 1992 -- Dec. 1994 ffl CTI: Current Technology Index Jan./Feb. 1993 -- Jan./Feb. 1994 ffl DAI: Dissertation Abstracts International: Vol. 53 No. 1 -- Vol. 55 No. 4 (1994) ffl EEA: Electrical & Electronics Abstracts: Jan. 1991 -- Dec. 1994 ffl P: Index to Scientific & Technical Proceed ..."
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Cited by 90 (10 self)
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s: Jan. 1992 -- Dec. 1994 ffl CTI: Current Technology Index Jan./Feb. 1993 -- Jan./Feb. 1994 ffl DAI: Dissertation Abstracts International: Vol. 53 No. 1 -- Vol. 55 No. 4 (1994) ffl EEA: Electrical & Electronics Abstracts: Jan. 1991 -- Dec. 1994 ffl P: Index to Scientific & Technical Proceedings: Jan. 1986 -- Feb. 1995 (except Nov. 1994) ffl EI A: The Engineering Index Annual: 1987 -- 1992 ffl EI M: The Engineering Index Monthly: Jan. 1993 -- Dec. 1994 The following GA researchers have already kindly supplied their complete autobibliographies and/or proofread references to their papers: Dan Adler, Patrick Argos, Jarmo T. Alander, James E. Baker, Wolfgang Banzhaf, Ralf Bruns, I. L. Bukatova, Thomas Back, Yuval Davidor, Dipankar Dasgupta, Marco Dorigo, Bogdan Filipic, Terence C. Fogarty, David B. Fogel, Toshio Fukuda, Hugo de Garis, Robert C. Glen, David E. Goldberg, Martina Gorges-Schleuter, Jeffrey Horn, Aristides T. Hatjimihail, Mark J. Jakiela, Richard S. Judson, Akihiko Konaga...
Testability Transformation
- IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
, 2004
"... A testability transformation is a source-to-source transformation that aims to improve the ability of a given test generation method to generate test data for the original program. This paper ..."
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Cited by 89 (38 self)
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A testability transformation is a source-to-source transformation that aims to improve the ability of a given test generation method to generate test data for the original program. This paper
GenProg: A Generic Method for Automatic Software Repair
"... 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 f ..."
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Cited by 73 (3 self)
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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. Index Terms—Automatic programming, corrections, testing and debugging. Ç 1
Evolutionary testing in the presence of loop-assigned flags: A testability transformation approach
- In Proceedings of the International Symposium on Software Testing and Analysis (ISSTA 2004
, 2004
"... Evolutionary testing is an effective technique for automatically generating good quality test data. However, for structural testing, the technique degenerates to random testing in the presence of flag variables, which also present problems for other automated test data generation techniques. Previou ..."
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Cited by 67 (23 self)
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Evolutionary testing is an effective technique for automatically generating good quality test data. However, for structural testing, the technique degenerates to random testing in the presence of flag variables, which also present problems for other automated test data generation techniques. Previous work on the flag problem does not address flags assigned in loops. This paper introduces a testability transformation that transforms programs with loop-assigned flags so that existing genetic approaches can be successfully applied. It then presents empirical data demonstrating the effectiveness of the transformation. Untransformed, the genetic algorithm flounders and is unable to find a solution. Two transformations are considered. The first allows the search to find a solution. The second reduces the time taken by an order of magnitude and, more importantly, reduces the slope of the cost increase; thus, greatly increasing the complexity of the problem to which the genetic algorithm can be applied. The paper also presents a second empirical study showing that loop-assigned flags are prevalent in real world code. They account for just under 11 % of all flags.
A Systematic Review of the Application and Empirical Investigation of Search-based Test-Case Generation
, 2008
"... Metaheuristic search techniques have been extensively used to automate the process of generating test cases and thus providing solutions for a more cost-effective testing process. This approach to test automation, often coined as “Search-based Software Testing” (SBST), has been used for a wide varie ..."
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Cited by 58 (6 self)
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Metaheuristic search techniques have been extensively used to automate the process of generating test cases and thus providing solutions for a more cost-effective testing process. This approach to test automation, often coined as “Search-based Software Testing” (SBST), has been used for a wide variety of test case generation purposes. Since SBST techniques are heuristic by nature, they must be empirically investigated in terms of how costly and effective they are at reaching their test objectives and whether they scale up to realistic development artifacts. However, approaches to empirically study SBST techniques have shown wide variation in the literature. This paper presents the results of a systematic, comprehensive review that aims at characterizing how empirical studies have been designed to investigate SBST cost-effectiveness and what empirical evidence is available in the literature regarding SBST cost-effectiveness and scalability. We also provide a framework that drives the data collection process of this systematic review and can be the starting point of guidelines on how SBST techniques can be empirically assessed. The intent is to aid future researchers doing empirical studies in SBST by providing an unbiased view of the body of empirical evidence and by guiding them in performing well designed and executed empirical studies references.
Atif M Memon. Using GUI Run-Time State as Feedback to Generate Test Cases
- 29th International Conference on Software Engineering (ICSE’07
, 2007
"... This paper presents a new automated model-driven tech-nique to generate test cases by using feedback from the ex-ecution of a seed test suite on an application under test (AUT). The test cases in the seed suite are designed to be generated automatically and executed very quickly. During their execu ..."
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Cited by 51 (13 self)
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This paper presents a new automated model-driven tech-nique to generate test cases by using feedback from the ex-ecution of a seed test suite on an application under test (AUT). The test cases in the seed suite are designed to be generated automatically and executed very quickly. During their execution, feedback obtained from the AUT's run-time state is used to generate new, improved test cases. The new test cases subsequently become part of the seed suite. This anytime technique continues iteratively, generating and executing additional test cases until resources are ex-hausted or testing goals have been met. The feedback-based technique is demonstrated for auto-mated testing of graphical user interfaces (GUIs). An ex-isting abstract model of the GUI is used to automatically generate the seed test suite. It is executed; during its ex-ecution, state changes in the GUI pinpoint important rela-tionships between GUI events, which evolve the model and help to generate new test cases. Together with a reverse-engineering algorithm used to obtain the initial model and seed suite, the feedback-based technique yields a fully au-tomatic, end-to-end GUI testing process. A feasibility study on four large elded open-source software (OSS) applica-tions demonstrates that this process is able to signicantly improve existing techniques and help identify/report serious problems in the OSS. In response, these problems have been xed by the developers of the OSS in subsequent versions. 1
Search Based Software Engineering: A Comprehensive Analysis and Review of Trends Techniques and Applications
, 2009
"... In the past five years there has been a dramatic increase in work on Search Based Software Engineering (SBSE), an approach to software engineering in which search based optimisation algorithms are used to address problems in Software Engineering. SBSE has been applied to problems throughout the Sof ..."
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Cited by 48 (18 self)
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In the past five years there has been a dramatic increase in work on Search Based Software Engineering (SBSE), an approach to software engineering in which search based optimisation algorithms are used to address problems in Software Engineering. SBSE has been applied to problems throughout the Software Engineering lifecycle, from requirements and project planning to maintenance and re-engineering. The approach is attractive because it offers a suite of adaptive automated and semi-automated solutions in situations typified by large complex problem spaces with multiple competing and conflicting objectives. This paper 1 provides a review and classification of literature on SBSE. The paper identifies research trends and relationships between the techniques applied and the applications to which they have been applied and highlights gaps in the literature and avenues for further research.
Improveing test suites for efficient fault localization
- In Proceedings 28th International Conference on Software Engineering (ICSE’2006
, 2006
"... ABSTRACT The need for testing-for-diagnosis strategies has been identified for a long time, but the explicit link from testing to diagnosis (fault localization) is rare. Analyzing the type of information needed for efficient fault localization, we identify the attribute (called Dynamic Basic Block) ..."
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Cited by 48 (4 self)
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ABSTRACT The need for testing-for-diagnosis strategies has been identified for a long time, but the explicit link from testing to diagnosis (fault localization) is rare. Analyzing the type of information needed for efficient fault localization, we identify the attribute (called Dynamic Basic Block) that restricts the accuracy of a diagnosis algorithm. Based on this attribute, a test-for-diagnosis criterion is proposed and validated through rigorous case studies: it shows that a test suite can be improved to reach a high level of diagnosis accuracy. So, the dilemma between a reduced testing effort (with as few test cases as possible) and the diagnosis accuracy (that needs as much test cases as possible to get more information) is partly solved by selecting test cases that are dedicated to diagnosis.
