Curiosity-Driven Testing for Sequential Decision-Making Process Article Swipe
Junda He
,
Zhou Yang
,
Jieke Shi
,
Chengran Yang
,
Kisub Kim
,
Bowen Xu
,
Xin Zhou
,
David Lo
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1145/3597503.3639149
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1145/3597503.3639149
Sequential decision-making processes (SDPs) are fundamental for complex real-world challenges, such as autonomous driving, robotic control, and traffic management. While recent advances in Deep Learning (DL) have led to mature solutions for solving these complex problems, SDMs remain vulnerable to learning unsafe behaviors, posing significant risks in safety-critical applications. However, developing a testing framework for SDMs that can identify a diverse set of crash-triggering scenarios remains an open challenge. To address this, we propose CureFuzz, a novel curiosity-driven black-box fuzz testing approach for SDMs. CureFuzz proposes a curiosity mechanism that allows a fuzzer to effectively explore novel and diverse scenarios, leading to improved detection of crash-triggering scenarios. Additionally, we introduce a multi-objective seed selection technique to balance the exploration of novel scenarios and the generation of crash-triggering scenarios, thereby optimizing the fuzzing process. We evaluate CureFuzz on various SDMs and experimental results demonstrate that CureFuzz outperforms the state-of-the-art method by a substantial margin in the total number of faults and distinct types of crash-triggering scenarios. We also demonstrate that the crash-triggering scenarios found by CureFuzz can repair SDMs, highlighting CureFuzz as a valuable tool for testing SDMs and optimizing their performance.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1145/3597503.3639149
- https://dl.acm.org/doi/pdf/10.1145/3597503.3639149
- OA Status
- gold
- Cited By
- 3
- References
- 62
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4394745802
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4394745802Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1145/3597503.3639149Digital Object Identifier
- Title
-
Curiosity-Driven Testing for Sequential Decision-Making ProcessWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-04-12Full publication date if available
- Authors
-
Junda He, Zhou Yang, Jieke Shi, Chengran Yang, Kisub Kim, Bowen Xu, Xin Zhou, David LoList of authors in order
- Landing page
-
https://doi.org/10.1145/3597503.3639149Publisher landing page
- PDF URL
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https://dl.acm.org/doi/pdf/10.1145/3597503.3639149Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://dl.acm.org/doi/pdf/10.1145/3597503.3639149Direct OA link when available
- Concepts
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Fuzz testing, Computer science, Crash, Curiosity, Process (computing), Set (abstract data type), Black box, Machine learning, Artificial intelligence, Software, Social psychology, Programming language, Operating system, PsychologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
3Total citation count in OpenAlex
- Citations by year (recent)
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2025: 3Per-year citation counts (last 5 years)
- References (count)
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62Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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