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Locating bugs is challenging but one of the most important activities in software development and maintenance phase because there are no certain rules to identify all types of bugs.
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A theoretical analysis of the risk evaluation formulas for spectrum-based fault localization
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Syntax errors just aren’t natural: improving error reporting with language models
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Extended comprehensive study of association measures for fault localization
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Comparing static bug finders and statistical prediction
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Code completion with statistical language models
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A practical evaluation of spectrum-based fault localization
R. Abreu, P. Zoeteweij, R. Golsteijn, and A. J. Van Gemund · 2009
Cited alongside, same era.
Cross-project defect prediction: a large scale experiment on data vs. domain vs. process
T. Zimmermann, N. Nagappan, H. Gall, E. Giger, and B. Murphy · 2009
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A systematic and comprehensive investigation of methods to build and evaluate fault prediction models
E. Arisholm, L. C. Briand, and E. B. Johannessen · 2010
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An extensive comparison of bug prediction approaches
M. D’Ambros, M. Lanza, and R. Robbes · 2010
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A study of the uniqueness of source code
M. Gabel and Z. Su · 2010
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Retrieval from software libraries for bug localization: a comparative study of generic and composite text models
S. Rao and A. Kak · 2011
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V. Raychev, M. Vechev, and E. Yahav · 2014
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On the localness of software
Z. Tu, Z. Su, and P. Devanbu · 2014
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On the localness of software
Z. Tu, Z. Su, and P. Devanbu · 2014
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Predicting vulnerable components: Software metrics vs text mining
J. Walden, J. Stuckman, and R. Scandariato · 2014
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Learning to combine multiple ranking metrics for fault localization
J. Xuan and M. Monperrus · 2014
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Learning to rank relevant files for bug reports using domain knowledge
X. Ye, R. Bunescu, and C. Liu · 2014
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http://findbugs.sourceforge.net/
FindBugs · 2015
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Cacheca: A cache language model based code suggestion tool
C. Franks, Z. Tu, P. Devanbu, and V. Hellendoorn · 2015
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Will they like this?: evaluating code contributions with language models
V. J. Hellendoorn, P. T. Devanbu, and A. Bacchelli · 2015
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Information retrieval and spectrum based bug localization: better together
T.-D. B. Le, R. J. Oentaryo, and D. Lo · 2015
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The manybugs and introclass benchmarks for automated repair of c programs
C. Le Goues, N. Holtschulte, E. K. Smith, Y. Brun, P. Devanbu, S. Forrest, and W. Weimer · 2015
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A learning-to-rank based fault localization approach using likely invariants
T.-D. B Le, D. Lo, C. Le Goues, and L. Grunske · 2016
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On the naturalness of buggy code
B. Ray, V. Hellendoorn, S. Godhane, Z. Tu, A. Bacchelli, and P. Devanbu · 2016
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Bugram: bug detection with n-gram language models
S. Wang, D. Chollak, D. Movshovitz-Attias, and L. Tan · 2016
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Automatically learning semantic features for defect prediction
S. Wang, T. Liu, and L. Tan · 2016
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