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ECOOP and ISSTA 2021
Sun 11 - Sat 17 July 2021 Online
Mon 12 Jul 2021 09:00 - 09:30 at AISTA - Main Session Chair(s): Lei Ma, Shuai Wang, Xiaofei Xie

Automated debugging, or fault localization, has long been classical research problem. In both industry and academics, programmers usually spend hours (if not days) for investigating their code line by line or step by step, looking for the root cause of the software failure.

One fundamental challenge of automated debugging is the specification/reference missing problem. Conceptually, a software fault is essentially an inconsistent implementation of the program specification. Therefore, if with detailed specification of the program behaviors as reference, the program debugging problem can be naturally transformed into a consistency checking problem. However, in practice, the detailed specification exist nowhere but in programmers’ mind, which makes the automated-debugging extremely hard, if not impossible.

In this talk, I will introduce our trace-travelling debugging framework (a further step based on time-travelling debugging or omniscient debugging), aiming to mitigate the general reference missing problem. Our approach takes as input the execution trace of a buggy program, and transform the program debugging problem into a problem of locating the first buggy step on the trace. Metaphorically, the debugging process can be regarded as a process of travelling on the buggy trace towards the root cause, and we design techniques to expedite the process of such a “travel”. I will first introduce a feedback-based approach to take user feedback on the trace steps. User feedbacks can be considered as partial specification, and guide and speed-up the trace-travelling process towards the root cause. Next, I will introduce a trace-alignment approach to align a buggy trace and its correct version, which facilitate us to automatically generate the user feedbacks on the buggy trace. Finally, I will introduce an AI-based approach to estimate/recommend user feedback on buggy traces without any reference, and further discuss the potential of “autonomous debugging”, i.e., a fully automated walking process on the buggy trace towards the root cause.

Mon 12 Jul

Displayed time zone: Brussels, Copenhagen, Madrid, Paris change

09:00 - 11:50
Main SessionAISTA at AISTA
Chair(s): Lei Ma University of Alberta, Shuai Wang Hong Kong University of Science and Technology, Xiaofei Xie Kyushu University
09:00
30m
Keynote
Towards Automated Debugging: A Trace Travelling Oriented and AI-based Approach
AISTA
Yun Lin National University of Singapore
09:30
20m
Talk
NerdBug: Automated Bug Detection in Neural Networks
AISTA
Foad Jafarinejad Technical University of Darmstadt, Krishna Narasimhan TU Darmstadt, Mira Mezini TU Darmstadt, Germany
09:50
20m
Talk
Automated Cell Header Generator for Jupyter Notebooks
AISTA
DOI
10:10
20m
Talk
Impact of Programming Languages on Machine Learning Bugs
AISTA
Sebastian Sztwiertnia Technical University of Darmstadt, Maximilian Grübel Technical University of Darmstadt, Amine Chouchane Technical University of Darmstadt, Daniel Sokolowski TU Darmstadt, Krishna Narasimhan TU Darmstadt, Mira Mezini TU Darmstadt, Germany
Link to publication DOI Pre-print
10:30
20m
Talk
On the use of Evolutionary Algorithms for Test Case Prioritization in Regression Testing considering Requirements Dependencies
AISTA
Andreea Vescan Babes-Bolyai University, Camelia Chisalita-Cretu Babes-Bolyai University Cluj-Napoca, Camelia Serban Department of Computer Science, Babes-Bolyai University, Laura Diosan Babes-Bolyai University
10:50
60m
Panel
Panel discussion
AISTA