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ICSE 2021
Mon 17 May - Sat 5 June 2021
Wed 26 May 2021 21:00 - 21:20 at Blended Sessions Room 4 - 2.6.4. Fault Localization #1 Chair(s): Leonardo Mariani
Thu 27 May 2021 09:00 - 09:20 at Blended Sessions Room 4 - 2.6.4. Fault Localization #1

Fault localization is a practical research topic that helps developers identify code locations that might cause bugs in a program. Most existing fault localization techniques are designed for imperative programs (e.g., C and Java) and rely on analyzing correct and incorrect executions of the program to identify suspicious statements. In this work, we introduce a fault localization approach for models written in a declarative language, where the models are not “executed,” but rather converted into a logical formula and solved using backend constraint solvers. We present FLACK, a tool that takes as input an Alloy model consisting of some violated assertion and returns a ranked list of suspicious expressions contributing to the assertion violation. The key idea is to analyze the differences between counterexamples (cex’s), i.e., instances of the model that do not satisfy the assertion, and instances that do satisfy the assertion to find suspicious expressions in the input model. The experimental results show that FLACK is efficient (can handle complex, real-world Alloy models with thousand lines of code within 5 seconds), accurate (can consistently rank buggy expressions in the top 1.9% of the suspicious list), and useful (can often narrow down the error to the exact location within the suspicious expressions).

Wed 26 May

Displayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change

20:40 - 21:40
2.6.4. Fault Localization #1Technical Track / SEIP - Software Engineering in Practice at Blended Sessions Room 4 +12h
Chair(s): Leonardo Mariani University of Milano Bicocca
20:40
20m
Paper
Industry-scale IR-based Bug Localization: A Perspective from FacebookSEIP
SEIP - Software Engineering in Practice
Vijayaraghavan Murali Facebook, Inc., Lee Gross Facebook, Rebecca Qian Facebook, Inc., Satish Chandra Facebook, USA
Pre-print Media Attached
21:00
20m
Paper
FLACK: Counterexample-Guided Fault Localization for Alloy ModelsArtifact ReusableTechnical TrackArtifact Available
Technical Track
Guolong Zheng University of Nebraska Lincoln, ThanhVu Nguyen University of Nebraska, Lincoln, Simón Gutiérrez Brida University of Rio Cuarto and CONICET, Argentina, Germán Regis University of Rio Cuarto, Argentina, Marcelo F. Frias Dept. of Software Engineering Instituto Tecnológico de Buenos Aires, Nazareno Aguirre University of Rio Cuarto and CONICET, Argentina, Hamid Bagheri University of Nebraska-Lincoln
Pre-print Media Attached
21:20
20m
Paper
Improving Fault Localization by Integrating Value and Predicate Based Causal Inference TechniquesACM SIGSOFT Distinguished PaperArtifact ReusableTechnical TrackArtifact Available
Technical Track
Yigit Kucuk Case Western Reserve University, Tim A. D. Henderson Google, Andy Podgurski Case Western Reserve University
Pre-print Media Attached

Thu 27 May

Displayed time zone: Amsterdam, Berlin, Bern, Rome, Stockholm, Vienna change

08:40 - 09:40
08:40
20m
Paper
Industry-scale IR-based Bug Localization: A Perspective from FacebookSEIP
SEIP - Software Engineering in Practice
Vijayaraghavan Murali Facebook, Inc., Lee Gross Facebook, Rebecca Qian Facebook, Inc., Satish Chandra Facebook, USA
Pre-print Media Attached
09:00
20m
Paper
FLACK: Counterexample-Guided Fault Localization for Alloy ModelsArtifact ReusableTechnical TrackArtifact Available
Technical Track
Guolong Zheng University of Nebraska Lincoln, ThanhVu Nguyen University of Nebraska, Lincoln, Simón Gutiérrez Brida University of Rio Cuarto and CONICET, Argentina, Germán Regis University of Rio Cuarto, Argentina, Marcelo F. Frias Dept. of Software Engineering Instituto Tecnológico de Buenos Aires, Nazareno Aguirre University of Rio Cuarto and CONICET, Argentina, Hamid Bagheri University of Nebraska-Lincoln
Pre-print Media Attached
09:20
20m
Paper
Improving Fault Localization by Integrating Value and Predicate Based Causal Inference TechniquesACM SIGSOFT Distinguished PaperArtifact ReusableTechnical TrackArtifact Available
Technical Track
Yigit Kucuk Case Western Reserve University, Tim A. D. Henderson Google, Andy Podgurski Case Western Reserve University
Pre-print Media Attached