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His research interests span an arc from semantic models of programming languages to actually building optimising compilers. A core interest is that of static analysis of programs to extract properties of their run-time behaviour. Such properties can be used to enable optimisations or to facilitate ``compile-time debugging''. His PhD created the subject of ``strictness analysis'' when he argued that apparent run-time inefficiencies in modern high-level languages can often be removed by program analysis and optimisation phases. Other work has encompassed type-based decompilation and also language and compilation issues for ``Silicon Compilers'', i.e.\ compiling specifications directly to hardware. In 2005/06 he held a ``Visiting Faculty'' position with Intel Research Cambridge involving developing languages and techniques for compiling to `multi-core' processors; this research illuminates the benefits of type-like systems of program analysis at enabling programmers to express and manage their implicit treaty with a compiler (``optimise as much as you can, but don't step over the line'').
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arXiv (Cornell University)no. 1 (2022): 32:1-32:19
AI & SOCIETYno. 2 (2022): 963-965
SPLASHpp.88-96, (2021)
ACM Transactions on Programming Languages and Systemsno. 2 (2020): 1-78
ACM TRANSACTIONS ON PROGRAMMING LANGUAGES AND SYSTEMSno. 2 (2020): 1-78
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