Sixth International Workshop on Deep Learning for Testing and Testing for Deep Learning (DeepTest 2025)
Machine Learning (ML) is widely adopted in modern software systems, including safety-critical domains such as autonomous cars, medical diagnosis, and aircraft collision avoidance systems. Thus, it is crucial to rigorously test such applications to ensure high dependability. However, standard notions of software quality and reliability become irrelevant when considering ML systems, due to their non-deterministic nature and the lack of a transparent understanding of the models’ semantics. ML is also expected to revolutionize software development. Indeed, ML is being applied for devising novel program analysis and software testing techniques related to malware detection, bug-finding, and type-checking
DeepTest 2025 aims to bring together academics and industry experts to discuss practical solutions and build momentum in this rapidly evolving field. The workshop will include invited talks and research presentations, providing a platform for participants to exchange ideas and insights.
This edition of DeepTest will be co-located with ICSE 2025, taking place from Sunday, April 27 to Saturday, May 3, 2025, in Ottawa, Ontario, Canada. The exact date of the workshop will be announced soon.
Previous Editions
- DeepTest 2024 was co-located with ICSE 2024
- DeepTest 2023 was co-located with ICSE 2023
- DeepTest 2021 was co-located with ICSE 2021
- DeepTest 2020 was co-located with ICSE 2020
- DeepTest 2019 was co-located with ICSE 2019
Call for Papers
DeepTest is an interdisciplinary workshop targeting research at the intersection of software engineering and deep learning. This workshop will explore issues related to:
- Deep Learning applied to Software Engineering (DL4SE)
- Software Engineering applied to Deep Learning (SE4DL)
Although the main focus is on Deep Learning, we also encourage submissions that are more broadly related to Machine Learning.
Topics of Interest
We welcome submissions introducing technology (i.e., frameworks, libraries, program analyses and tool evaluation) for testing DL-based applications, and DL-based solutions to solve open research problems (e.g., what is a bug in a DL/RL model). Relevant topics include, but are not limited to:
- High-quality benchmarks for evaluating DL/RL approaches
- Surveys and case studies using DL/RL technology
- Techniques to aid interpretable DL/RL techniques
- Techniques to improve the design of reliable DL/RL models
- DL/RL-aided software development approaches
- DL/RL for fault prediction, localization and repair
- Fuzzing DL/RL systems
- Metamorphic testing as software quality assurance
- Fault Localization and Anomaly Detection
- Use of DL for analyzing natural language-like artefacts such as code, or user reviews
- DL/RL techniques to support automated software testing
- DL/RL to aid program comprehension, program transformation, and program generation
- Safety and security of DL/RL based systems
- New approaches to estimate and measure uncertainty in DL/RL models
Types of Submissions
We accept two types of submissions:
- Full research papers: up to 8-page papers (including references) describing original and unpublished results related to the workshop topics;
- Short papers up: to 4-page papers (including references) describing preliminary work, new insights in previous work, or demonstrations of testing-related tools and prototypes.
All submissions must conform to the ICSE 2025 formatting instructions. All submissions must be in PDF. The page limit is strict. Submissions must conform to the IEEE conference proceedings template, specified in the IEEE Conference Proceedings Formatting Guidelines.
DeepTest 2025 will employ a double-blind review process. Thus, no submission may reveal its authors’ identities. The authors must make every effort to honor the double-blind review process. In particular, the authors’ names must be omitted from the submission, and references to their prior work should be in the third person.
If you have any questions or wonder whether your submission is in scope, please do not hesitate to contact the organizers.