What is he best known for?
The fields of study he is best known for:
- Programming language
- Algebra
- Functional programming
Olivier Danvy mainly focuses on Programming language, Partial evaluation, Theoretical computer science, Transformation and Continuation.
Programming language is closely attributed to Representation in his research.
His Partial evaluation research incorporates elements of Algorithm, Compiler, Galois connection and Programmer.
His work in the fields of Theoretical computer science, such as Abstract interpretation, overlaps with other areas such as Iterated function.
His Transformation research includes themes of Continuation-passing style, Virtual machine, Closure, A-normal form and Scheme.
His Continuation research incorporates themes from Coroutine, Rewriting, Calculus and Metalanguage.
His most cited work include:
- Abstracting control (323 citations)
- Representing Control: a Study of the CPS Transformation (280 citations)
- Tutorial notes on partial evaluation (277 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Programming language, Partial evaluation, Algorithm, Abstract machine and Theoretical computer science.
His works in Continuation, Semantics, Operational semantics, Functional programming and Compiler are all subjects of inquiry into Programming language.
His research in Partial evaluation intersects with topics in Pattern matching, Abstract syntax, Residual, Code generation and Program transformation.
Olivier Danvy combines subjects such as Transformation, Algebra and String with his study of Algorithm.
His work carried out in the field of Abstract machine brings together such families of science as Delimited continuation, Reduction, Interpreter and Evaluation function.
His biological study spans a wide range of topics, including Scheme and Denotational semantics.
He most often published in these fields:
- Programming language (53.42%)
- Partial evaluation (27.78%)
- Algorithm (24.36%)
What were the highlights of his more recent work (between 2007-2019)?
- Programming language (53.42%)
- Abstract machine (23.08%)
- Theoretical computer science (20.51%)
In recent papers he was focusing on the following fields of study:
Olivier Danvy spends much of his time researching Programming language, Abstract machine, Theoretical computer science, Semantics and Operational semantics.
His research on Programming language frequently connects to adjacent areas such as Operations research.
His Abstract machine study incorporates themes from Normalization, Functional programming and Evaluation function.
His Normalization research focuses on Expressive power and how it connects with Partial evaluation.
His Graph reduction study, which is part of a larger body of work in Theoretical computer science, is frequently linked to Work, bridging the gap between disciplines.
His research integrates issues of Delimited continuation, Monad, Correctness and Transformation in his study of Continuation-passing style.
Between 2007 and 2019, his most popular works were:
- Defunctionalized interpreters for programming languages (53 citations)
- From reduction-based to reduction-free normalization (37 citations)
- On the equivalence between small-step and big-step abstract machines: a simple application of lightweight fusion (36 citations)
In his most recent research, the most cited papers focused on:
- Programming language
- Algebra
- Functional programming
Olivier Danvy focuses on Abstract machine, Theoretical computer science, Programming language, Functional programming and Operational semantics.
His Abstract machine research is classified as research in Algorithm.
His Theoretical computer science research integrates issues from Scheme, Semantics and Discrete mathematics.
His work on Programming language is being expanded to include thematically relevant topics such as Relevance.
In his study, Formal semantics is strongly linked to Denotational semantics, which falls under the umbrella field of Functional programming.
His Operational semantics research is multidisciplinary, incorporating perspectives in Rewriting, Theory of computation, Lazy evaluation and Evaluation strategy.
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