SSBSE 2022
Thu 17 - Fri 18 November 2022 Singapore
co-located with ESEC/FSE 2022

Applications of Search-based Software Testing to Trustworthy Artificial Intelligence

Lionel C. Briand / University of Ottawa & University of Luxembourg

Lionel C. Briand

Abstract

Increasingly, many systems, including critical ones, rely on machine learning (ML) components to achieve autonomy or adaptiveness. Such components, having no specifications or source code, impact the way we develop but also verify such systems. This talk will report on experiences and lessons learned in applying search-based solutions to test and analyse such ML-enabled systems. Indeed, our results have shown that metaheuristic search plays a key role in enabling the effective test automation of ML models and the systems they are integrated into. Though other techniques are also required to achieve scalability and enable safety analysis, for example, the black-box nature of ML components naturally lends itself to search-based solutions.

Bio

Lionel C. Briand is a professor of software engineering and has shared appointments between (1) The University of Ottawa, Canada and (2) The SnT centre for Security, Reliability, and Trust, University of Luxembourg. In collaboration with colleagues, over 25 years, he has run many collaborative research projects with companies in the automotive, satellite, aerospace, energy, financial, and legal domains. Lionel was elevated to the grades of IEEE Fellow and ACM Fellow for his work on software testing and verification. He was granted the IEEE Computer Society Harlan Mills award, the ACM SIGSOFT outstanding research award, and the IEEE Reliability Society engineer-of-the-year award, respectively in 2012, 2022, and 2013. He received an ERC Advanced grant in 2016 — on the topic of modelling and testing cyber-physical systems — which is the most prestigious individual research award in the European Union. He currently holds a Canada Research Chair (Tier 1) on “Intelligent Software Dependability and Compliance”. His research interests include: software testing and verification, applications of AI in software engineering, model-driven software development, requirements engineering, and empirical software engineering.

Genetic Improvement of Software

Justyna Petke / University College London

Justyna Petke

Abstract

Genetic improvement uses computational search to improve existing software with respect to a user-defined objective function, while retaining some existing behaviour, usually captured by testing. Work on genetic improvement has already resulted in several awards. GI has been used, for instance, to automate the process of program repair, to speed up software for a particular domain, and to minimize memory and energy consumption. GI has also been used to transplant functionality from one software to another in an automated way. I will give an overview of the genetic improvement area and present key components of a GI framework.

Bio

Justyna Petke is a Principal Research Fellow and a Proleptic Associate Professor at the Centre for Research on Evolution, Search and Testing (CREST), located in the Department of Computer Science, University College London, UK. She is also a member of the Software Optimisation, Learning and Analytics Research (SOLAR) group at UCL. Her research focuses on Genetic Improvement, in particular use of search approaches to optimise software’s various properties, such as runtime and energy consumption, as well as to fix bugs and transplant new functionality. Her work on GI was awarded, among others, two SSBSE Challenge Track prizes, and two `Humies’, awarded for human-competitive results. She holds an EPSRC Early Career Fellowship on Automated Software Specialisation Using Genetic Improvement. Justyna was PC co-Chair of SSBSE 2017 and serves on the Editorial Board for the ASE, EMSE, GPEM and EAAI journals.

Dates
Tracks
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Thu 17 Nov

Displayed time zone: Beijing, Chongqing, Hong Kong, Urumqi change

09:00 - 10:30
Plenary + Keynote 1Keynotes at ERC SR 9
Chair(s): Mike Papadakis University of Luxembourg, Luxembourg
09:00
90m
Keynote
Applications of Search-based Software Testing to Trustworthy Artificial Intelligence
Keynotes
Lionel Briand University of Luxembourg; University of Ottawa
11:00 - 12:30
Session 1Research Papers / RENE / NIER at ERC SR 9
Chair(s): Ezekiel Soremekun SnT, University of Luxembourg
11:00
30m
Talk
Guess What: Test Case Generation for Javascript with Unsupervised Probabilistic Type Inference
Research Papers
Dimitri Stallenberg Delft University of Technology, Mitchell Olsthoorn Delft University of Technology, Annibale Panichella Delft University of Technology
Pre-print
11:30
30m
Talk
Improving Search-based Android Test Generation using Surrogate Models
Research Papers
Michael Auer University of Passau, Felix Adler University of Passau, Gordon Fraser University of Passau
12:00
30m
Talk
Applying Combinatorial Testing to Verification-Based Fairness Testing
RENE / NIER
Takashi Kitamura , Zhenjiang Zhao Graduate School of Informatics and Engineering, University of Electro-Communications, Tokyo, Japan, Takahisa Toda The University of Electro-Communications
14:00 - 15:30
Session 2Research Papers / Challenge Track at ERC SR 9
Chair(s): Renzo Degiovanni SnT, University of Luxembourg
14:00
30m
Talk
An Empirical Comparison of EvoSuite and DSpot for Improving Developer-Written Test Suites with Respect to Mutation Score
Research Papers
Muhammad Firhard Roslan University of Sheffield, José Miguel Rojas The University of Sheffield, Phil McMinn University of Sheffield
14:30
30m
Talk
Efficient Fairness Testing through Hash-Based Sampling
Research Papers
Zhenjiang Zhao Graduate School of Informatics and Engineering, University of Electro-Communications, Tokyo, Japan, Takahisa Toda The University of Electro-Communications, Takashi Kitamura
15:00
30m
Talk
Multi-Objective Genetic Improvement: A Case Study with EvoSuite
Challenge Track
James Callan UCL, Justyna Petke University College London
16:00 - 17:30
Session 3Research Papers at ERC SR 9
Chair(s): Mitchell Olsthoorn Delft University of Technology
16:00
30m
Talk
EvoAttack: An Evolutionary Search-based Adversarial Attack for Object Detection Models
Research Papers
Kenneth Chan Michigan State University, Betty H.C. Cheng Michigan State University
16:30
30m
Talk
Search-based Test Suite Generation for Rust
Research Papers
Vsevolod Tymofyeyev University of Passau, Gordon Fraser University of Passau

Fri 18 Nov

Displayed time zone: Beijing, Chongqing, Hong Kong, Urumqi change

11:00 - 12:30
Future of SSBSE 1Future of SBSE at Virtual 3 (Whova)
Chair(s): Thiago Ferreira University of Michigan - Flint
11:00
30m
Talk
ML is the new SBSE
Future of SBSE
Myra Cohen Iowa State University
11:30
30m
Talk
Reverse engineering the new SBSE
Future of SBSE
Tim Menzies North Carolina State University
14:00 - 15:30
TutorialTutorial at Virtual 3 (Whova)
Chair(s): Jeongju Sohn University of Luxembourg, Luxembourg
14:30
60m
Tutorial
Methodology and Guidelines for Evaluating Multi-Objective Search-Based Software Engineering
Tutorial
Miqing Li University of Birmingham, Tao Chen Loughborough University
Link to publication Pre-print
16:00 - 17:30
Keynote 2Keynotes at Virtual 3 (Whova)
Chair(s): Annibale Panichella Delft University of Technology
16:00
90m
Keynote
Genetic Improvement of Software
Keynotes
Justyna Petke University College London
18:30 - 20:00
Future of SSBSE 2Future of SBSE at Virtual 3 (Whova)
Chair(s): Giovani Guizzo University College London
18:30
30m
Talk
Online software safety: a new paradigm for SBSE research
Future of SBSE
Mark Harman Meta Platforms, Inc. and UCL
19:00
30m
Talk
"SSBSE 2050: 14-18 November, Oxia Palus, Mars"
Future of SBSE
Andrea Arcuri Kristiania University College and Oslo Metropolitan University
19:30
30m
Talk
Data Mining Algorithms Using/Used-by Optimisers: a DUO Approach to Software Engineering
Future of SBSE
Leandro Minku University of Birmingham, UK