Bug isolation via remote program sampling

By Ben Liblit, A. Aiken, Alice X. Zheng, Michael I. Jordan. ACM-SIGPLAN Symposium on Programming Language Design and Implementation, 2003

616 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Information Systems, Information Systems and Management

View Paper: https://www.semanticscholar.org/paper/30248b743465334f1454114d2bbdd5941dfa7f0d

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Citations in the corpus

Covering arrays for efficient fault characterization in complex configuration spaces (2004, methodology): “Other techniques have been used to isolate faults in code for debugging [11], [20].”
GenProg: A Generic Method for Automatic Software Repair (2012, background): “Mature software projects are forced to ship with both known and unknown bugs [1] because the number of outstanding software defects typically exceeds the resources available to address them [2].”
Fault localization with nearest neighbor queries (2003, neutral): “For example, recent work [10, 20, 22]”
Debugging Machine Learning Tasks (2016, methodology): “The CBI project and its variants [22, 23, 24] use information collected from program runs together with a statistical analysis in order to compute predicates that are highly correlated with failures.”
Locating causes of program failures (2005, background): “In the presence of multiple runs, statistical correlation between features of program runs and test failures [10] can be seen as a strong indicator of causality.”
SemFix: Program repair via semantic analysis (2013, methodology): “The technique uses the ranking produced by a statistical fault isolation [9] tool (it shares this step with the search-based techniques.)”
AVIO: detecting atomicity violations via access interleaving invariants (2006, methodology): “Its feasibility and powerful bug detection capability is shown in previous work like DAIKON [9], DIDUCE [14], AccMon [44] and Liblit’s work [20].”
An overview of JML tools and applications (2003, methodology): “In addition to aiding the task of static checking as described above, operational abstractions generated by the Daikon invariant detector have been used to generate and improve test suites [40, 44, 93], automate theorem proving [78, 79], identify refactoring opportunities [53], aid program analysis ”
HDD: hierarchical delta debugging (2006, methodology): “use a sampling technique to reduce the runtime overhead of collecting successful and failing runs [9].”
Carat: collaborative energy diagnosis for mobile devices (2013, methodology): “Such methods have been used to identify code paths correlated with failure [16, 17], concurrency bugs [14], shared influence (surprising behavior that is correlated in time) [26, 28], invariant violation [13], and configuration errors [41].”
Statistical debugging: simultaneous identification of multiple bugs (2006, methodology): “tation of software and a distributed data collection infrastructure (Liblit et al., 2003).”
SOBER: statistical model-based bug localization (2005, methodology): “on statistical debugging [14] also adopts logistic regression in sifting predicates that are correlated with program crashes.”
Catch me if you can: performance bug detection in the wild (2011, background): “[17] present an approach for finding correctness bugs by correlating the value of predicates inserted at specific program points with the occurrences of failures.”
History Driven Program Repair (2016, background): “Mature commercial software systems regularly ship with both known and unknown defects [31], despite the support of multiple developers and testers typically dedicated to such projects [3].”
An approach to detecting duplicate bug reports using natural language and execution information (2008, methodology): “Elbaum and Diep [5] suggested a strategy to collect remote execution information over Internet; Liblit et al [ 11 ] proposed a technique to sampling remote runs for bug isolation.”
Software Testing Research: Achievements, Challenges, Dreams (2007, methodology): “And fielded profiles can also be used for improving a given test suite, such as in [56, 64, 29].”
Statistical Debugging: A Hypothesis Testing-Based Approach (2006, methodology): “T HE last decade has witnessed great advances in fault localization techniques [1], [2], [3], [4], [5], [6], [7], [8], [9].”