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ICSE 2022
Sun 8 - Fri 27 May 2022
Mon 9 May 2022 21:15 - 21:20 at ICSE room 5-odd hours - Program Analysis 3 Chair(s): Travis Breaux
Tue 10 May 2022 13:20 - 13:25 at ICSE room 3-odd hours - Program Analysis 4 Chair(s): Miguel Goulao
Thu 26 May 2022 11:15 - 11:20 at Room 306+307 - Papers 14: Program Analysis Chair(s): Frank Tip

Deep Neural Networks (DNNs) are used in a wide variety of applications. However, as in any software application, DNN-based apps are afflicted with bugs. Previous work observed that DNN bug fix patterns are different from traditional bug fix patterns. Furthermore, those buggy models are non-trivial to diagnose and fix due to inexplicit errors with several options to fix them. To support developers in locating and fixing bugs, we propose DeepDiagnosis, a novel debugging approach that localizes the faults, reports error symptoms and suggests fixes for DNN programs. In the first phase, our technique monitors a training model, periodically checking for eight types of error conditions. Then, in case of problems, it reports messages containing sufficient information to perform actionable repairs to the model. In the evaluation, we thoroughly examine 444 models – 53 real-world from GitHub and Stack Overflow, and 391 curated by AUTOTRAINER. DeepDiagnosis provides superior accuracy when compared to UMLUAT and DeepLocalize. Our technique is faster than AUTOTRAINER for fault localization. The results show that our approach can support additional types of models, while state-of-the-art was only able to handle classification ones. Our technique was able to report bugs that do not manifest as numerical errors during training. Also, it can provide actionable insights for fix whereas DeepLocalize can only report faults that lead to numerical errors during training. DeepDiagnosis manifests the best capabilities of fault detection, bug localization, and symptoms identification when compared to other approaches.

Mon 9 May

Displayed time zone: Eastern Time (US & Canada) change

21:00 - 22:00
21:00
5m
Talk
Learning to Find Usages of Library Functions in Optimized Binaries
Journal-First Papers
Toufique Ahmed University of California at Davis, Prem Devanbu Department of Computer Science, University of California, Davis, Anand Ashok Sawant University of California, Davis
Link to publication DOI Pre-print Media Attached
21:05
5m
Talk
InspectJS: Leveraging Code Similarity and User-Feedback for Effective Taint Specification Inference for JavaScript
SEIP - Software Engineering in Practice
Saikat Dutta University of Illinois at Urbana-Champaign, Diego Garbervetsky University of Buenos Aires and CONICET, Argentina, Shuvendu K. Lahiri Microsoft Research, Max Schaefer GitHub, Inc.
DOI Pre-print Media Attached
21:10
5m
Talk
Static Inference Meets Deep Learning: A Hybrid Type Inference Approach for PythonNominated for Distinguished Paper
Technical Track
Yun Peng The Chinese University of Hong Kong, Cuiyun Gao Harbin Institute of Technology, Zongjie Li The Hong Kong University of Science and Technology, Bowei Gao Harbin Institute of Technology, Shenzhen, David Lo Singapore Management University, Qirun Zhang Georgia Institute of Technology, USA, Michael Lyu The Chinese University of Hong Kong
DOI Pre-print Media Attached
21:15
5m
Talk
DeepDiagnosis: Automatically Diagnosing Faults and Recommending Actionable Fixes in Deep Learning Programs
Technical Track
Mohammad Wardat Dept. of Computer Science, Iowa State University, Breno Dantas Cruz Dept. of Computer Science, Iowa State University, Wei Le Iowa State University, Hridesh Rajan Iowa State University
Pre-print Media Attached
21:20
5m
Talk
Striking a Balance: Pruning False-Positives from Static Call GraphsNominated for Distinguished Paper
Technical Track
Akshay Utture University of California, Los Angeles (UCLA), Shuyang Liu University of California, Los Angeles, Christian Gram Kalhauge Technical University of Denmark, Jens Palsberg University of California at Los Angeles
DOI Pre-print Media Attached

Tue 10 May

Displayed time zone: Eastern Time (US & Canada) change

13:00 - 14:00
13:00
5m
Talk
TaintBench: Automatic Real-World Malware Benchmarking of Android Taint Analyses
Journal-First Papers
Linghui Luo Amazon Web Services, Felix Pauck Paderborn University, Germany, Goran Piskachev Fraunhofer IEM, Manuel Benz Paderborn University, Ivan Pashchenko University of Trento, Martin Mory Paderborn University, Eric Bodden , Ben Hermann Technical University Dortmund, Fabio Massacci University of Trento; Vrije Universiteit Amsterdam
Link to publication DOI Pre-print Media Attached File Attached
13:05
5m
Talk
Statistical Reasoning About Programs
NIER - New Ideas and Emerging Results
Marcel Böhme MPI-SP, Germany and Monash University, Australia
DOI Pre-print Media Attached
13:10
5m
Talk
InspectJS: Leveraging Code Similarity and User-Feedback for Effective Taint Specification Inference for JavaScript
SEIP - Software Engineering in Practice
Saikat Dutta University of Illinois at Urbana-Champaign, Diego Garbervetsky University of Buenos Aires and CONICET, Argentina, Shuvendu K. Lahiri Microsoft Research, Max Schaefer GitHub, Inc.
DOI Pre-print Media Attached
13:15
5m
Talk
Striking a Balance: Pruning False-Positives from Static Call GraphsNominated for Distinguished Paper
Technical Track
Akshay Utture University of California, Los Angeles (UCLA), Shuyang Liu University of California, Los Angeles, Christian Gram Kalhauge Technical University of Denmark, Jens Palsberg University of California at Los Angeles
DOI Pre-print Media Attached
13:20
5m
Talk
DeepDiagnosis: Automatically Diagnosing Faults and Recommending Actionable Fixes in Deep Learning Programs
Technical Track
Mohammad Wardat Dept. of Computer Science, Iowa State University, Breno Dantas Cruz Dept. of Computer Science, Iowa State University, Wei Le Iowa State University, Hridesh Rajan Iowa State University
Pre-print Media Attached

Thu 26 May

Displayed time zone: Eastern Time (US & Canada) change

11:00 - 12:30
Papers 14: Program AnalysisTechnical Track / SEIP - Software Engineering in Practice / Journal-First Papers at Room 306+307
Chair(s): Frank Tip Northeastern University
11:00
5m
Talk
Static Inference Meets Deep Learning: A Hybrid Type Inference Approach for PythonNominated for Distinguished Paper
Technical Track
Yun Peng The Chinese University of Hong Kong, Cuiyun Gao Harbin Institute of Technology, Zongjie Li The Hong Kong University of Science and Technology, Bowei Gao Harbin Institute of Technology, Shenzhen, David Lo Singapore Management University, Qirun Zhang Georgia Institute of Technology, USA, Michael Lyu The Chinese University of Hong Kong
DOI Pre-print Media Attached
11:05
5m
Talk
TaintBench: Automatic Real-World Malware Benchmarking of Android Taint Analyses
Journal-First Papers
Linghui Luo Amazon Web Services, Felix Pauck Paderborn University, Germany, Goran Piskachev Fraunhofer IEM, Manuel Benz Paderborn University, Ivan Pashchenko University of Trento, Martin Mory Paderborn University, Eric Bodden , Ben Hermann Technical University Dortmund, Fabio Massacci University of Trento; Vrije Universiteit Amsterdam
Link to publication DOI Pre-print Media Attached File Attached
11:10
5m
Talk
InspectJS: Leveraging Code Similarity and User-Feedback for Effective Taint Specification Inference for JavaScript
SEIP - Software Engineering in Practice
Saikat Dutta University of Illinois at Urbana-Champaign, Diego Garbervetsky University of Buenos Aires and CONICET, Argentina, Shuvendu K. Lahiri Microsoft Research, Max Schaefer GitHub, Inc.
DOI Pre-print Media Attached
11:15
5m
Talk
DeepDiagnosis: Automatically Diagnosing Faults and Recommending Actionable Fixes in Deep Learning Programs
Technical Track
Mohammad Wardat Dept. of Computer Science, Iowa State University, Breno Dantas Cruz Dept. of Computer Science, Iowa State University, Wei Le Iowa State University, Hridesh Rajan Iowa State University
Pre-print Media Attached
11:20
5m
Talk
Inference and Test Generation Using Program Invariants in Chemical Reaction Networks
Technical Track
Michael C. Gerten Iowa State University, Alexis L. Marsh Iowa State University, James I. Lathrop Iowa State University, Myra Cohen Iowa State University, Andrew S. Miner Iowa State University, Titus H. Klinge Drake University
DOI Pre-print Media Attached
11:25
5m
Talk
PUS: A Fast and Highly Efficient Solver for Inclusion-based Pointer AnalysisDistinguished Paper Award
Technical Track
Peiming Liu Texas A&M University, Yanze Li University of British Columbia, Bradley Swain Texas A&M University, Jeff Huang Texas A&M University
Pre-print Media Attached
11:30
5m
Talk
Fast and Precise Application Code Analysis using a Partial Library
Technical Track
Akshay Utture University of California, Los Angeles (UCLA), Jens Palsberg University of California at Los Angeles
DOI Pre-print Media Attached

Information for Participants
Mon 9 May 2022 21:00 - 22:00 at ICSE room 5-odd hours - Program Analysis 3 Chair(s): Travis Breaux
Info for room ICSE room 5-odd hours:

Click here to go to the room on Midspace

Tue 10 May 2022 13:00 - 14:00 at ICSE room 3-odd hours - Program Analysis 4 Chair(s): Miguel Goulao
Info for room ICSE room 3-odd hours:

Click here to go to the room on Midspace