The Probabilistic Program Dependence Graph and Its Application to Fault Diagnosis

Baah, George K.; Podgurski, Andy; Harrold, Mary Jean

doi:10.1109/tse.2009.87

Cited by 90 publications

(35 citation statements)

References 30 publications

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“…Developers can use the suspiciousness score to order their search for a fault to debug. Spectrum-based fault localization (SBFL) (Abreu et al 2007;Agrawal et al 1995;Baah et al 2010;Chilimbi et al 2009;Dallmeier et al 2005;Jones et al 2002;Renieres and Reiss 2003) is a common FL approach; it compares the program behavior of a passing execution to that of a failing execution. SBFL collects information on the dynamic behavior of program statements when they are executed against each test in a test suite.…”

Section: Fault Localization Techniques (Fl)mentioning

confidence: 99%

Fault localization for automated program repair: effectiveness, performance, repair correctness

Assiri

Bieman

2016

Software Qual J

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Automated program repair (APR) tools apply fault localization (FL) techniques to identify the locations of likely faults to be repaired. The effectiveness, performance, and repair correctness of APR depends in part on the FL method used. If FL does not identify the location of a fault, the application of an APR tool will not be effective-it will fail to repair the fault. If FL assigns the actual faulty statement a low priority for repair, APR performance will be reduced by increasing the time required to find a potential repair. In addition, the correctness of a generated repair will be decreased since APR will modify fault-free statements that are assigned a higher priority for repair than an actual faulty statement. We conducted a controlled experiment to evaluate the impact of ten FL techniques on APR effectiveness, performance, and repair correctness using a brute force APR tool applied to faulty versions of the Siemens Suite and two other large programs: space and sed. All FL techniques were effective in identifying all faults; however, Wong3 and Ample1 were the least effective FL techniques since they assigned the lowest priority for repair in more than 26 % of the trials. We obtained the worst APR performance significantly when Ample1 was used since it generated a large number of variants in 29.11 % of the trials, and took the longest time to produce potential repairs. Jaccard FL improved repair correctness by generating more validated repairs-potential repairs that pass a set of regression tests, and generating potential repairs that failed fewer regression tests. Also Jaccard's performance is noteworthy in that it never generated a large number of variants during the repair process compared to the alternatives.

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Section: Fault Localization Techniques (Fl)mentioning

confidence: 99%

Fault localization for automated program repair: effectiveness, performance, repair correctness

Assiri

Bieman

2016

Software Qual J

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“…clones (Komondoor and Horwitz 2001). Baah et al build a probabilistic PDG and use it to localize bugs in programs given a set of failing and correct executions (Baah et al 2010). In this work, we focus on the usage of PDGs for automatic construction of queries for dependence-based code search.…”

Section: Program Dependence Graph Its Construction and Usagesmentioning

confidence: 99%

AutoQuery: automatic construction of dependency queries for code search

Jiang

2014

Autom Softw Eng

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Many code search techniques have been proposed to return relevant code for a user query expressed as textual descriptions. However, source code is not mere text. It contains dependency relations among various program elements. To leverage these dependencies for more accurate code search results, techniques have been proposed to allow user queries to be expressed as control and data dependency relationships among program elements. Although such techniques have been shown to be effective for finding relevant code, it remains a question whether appropriate queries can be generated by average users. In this work, we address this concern by proposing a technique, AutoQuery, that can automatically construct dependency queries from a set of code snippets. We realize AutoQuery by the following major steps: firstly, code snippets (that are not necessarily compilable) are converted into program dependence graphs (PDGs); secondly, a new graph mining solution is built to return common structures in the PDGs; thirdly, the common structures are converted to dependency queries, which are used to retrieve results by using a dependence-based code search technique. We have evaluated AutoQuery on real systems with 47 different code search tasks. The results show that the automatically constructed dependency queries retrieve relevant code with a precision, recall, and F-measure of 68.4, 72.1, and 70.2 %, respectively. We have also performed a user study to compare the effectiveness of AutoQuery with that of human generated queries. The results show that queries constructed by AutoQuery on average help to retrieve code fragments with comparable F-measures to those retrieved by human constructed queries.

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“…Buse and Weimer have presented a descriptive statistical model of path frequency based on features that can be readily obtained from a program's source code [5]. Baah and Harrold have presented a model called the probabilistic program dependence graph (PPDG) which is used to represent a program's internal behavior over a set of test inputs [2]. PPDG is an augmentation of the structural dependencies represented by a program dependence graph with estimates of statistical dependencies between node states, and it can facilitate probabilistic analysis and reasoning about uncertain program behavior.…”

Section: Related Workmentioning

confidence: 99%

Platform independent analysis of probabilities on execution paths of multithreaded programs

Chen

2013

2013 IEEE/ACIS 12th International Conference on Computer and Information Science (ICIS)

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A concurrent program is intuitively associated with probability. In this paper we propose a platform independent approach, called ProbPP, to analyzing the probabilities on the execution paths of the multithreaded programs. The main idea of ProbPP is to calculate the probabilities on the basis of two kinds of probabilities: Primitive Dependent Probabilities (PDPs) representing the control dependent probabilities among the program statements and Thread Execution Probabilities (TEPs) representing the probabilities of threads being scheduled to execute. We have also conducted two preliminary experiments to evaluate the effectiveness and performance of ProbPP, and the experimental results show that ProbPP can provide engineers with acceptable accuracy.

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The Probabilistic Program Dependence Graph and Its Application to Fault Diagnosis

Cited by 90 publications

References 30 publications

Fault localization for automated program repair: effectiveness, performance, repair correctness

Fault localization for automated program repair: effectiveness, performance, repair correctness

AutoQuery: automatic construction of dependency queries for code search

Platform independent analysis of probabilities on execution paths of multithreaded programs

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