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Learning a strategy for adapting a program analysis via Bayesian optimisation

Abstract:

Building a cost-effective static analyser for real-world programs is still regarded an art. One key contributor to this grim reputation is the difficulty in balancing the cost and the precision of an analyser. An ideal analyser should be adaptive to a given analysis task, and avoid using techniques that unnecessarily improve precision and increase analysis cost. However, achieving this ideal is highly nontrivial, and it requires a la... Expand abstract
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1145/2814270.2814309

Authors


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Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Role:
Author
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Name:
National Research Foundation of Korea
Grant:
NRF-2008-0062609
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Name:
Korea Ministry of Science, ICT and Future Planning
Grant:
B0101-15-0557
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Name:
Engineering and Physical Sciences Research Council
Funding agency for:
Yang, H
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Name:
Samsung Electronics Software Center
Publisher:
Association for Computing Machinery
Host title:
Proceedings of the 2015 ACM SIGPLAN International Conference on Object-Oriented Programming, Systems, Languages, and Applications
Journal:
Proceedings of the 2015 ACM SIGPLAN International Conference on Object-Oriented Programming, Systems, Languages, and Applications More from this journal
Pages:
572-588
Publication date:
2015-10-23
Acceptance date:
2015-08-03
DOI:
ISBN:
9781450336895
Pubs id:
pubs:581037
UUID:
uuid:f656bcfd-ec1b-477c-9185-ff2c7490a207
Local pid:
pubs:581037
Source identifiers:
581037
Deposit date:
2016-01-03

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