What is he best known for?
The fields of study he is best known for:
- Programming language
- Artificial intelligence
- Algorithm
The scientist’s investigation covers issues in Programming language, Reactive system, Theoretical computer science, Unified Modeling Language and Artificial intelligence.
The study incorporates disciplines such as Complex system, Software, Requirements engineering and Software engineering in addition to Reactive system.
David Harel interconnects Modular decomposition, Concurrency, Cluster analysis and Relational database, Conjunctive query in the investigation of issues within Theoretical computer science.
His Unified Modeling Language research is multidisciplinary, incorporating elements of Semantics, Sequence, Message sequence chart and Modeling language.
His study of Higraph is a part of Artificial intelligence.
His Higraph research is multidisciplinary, relying on both SCXML, Knowledge representation and reasoning, Modular design and Esterel, Synchronous programming language.
His most cited work include:
- Statecharts: A visual formalism for complex systems (6039 citations)
- Dynamic Logic (1514 citations)
- On visual formalisms (1160 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Programming language, Theoretical computer science, Reactive system, Artificial intelligence and Software engineering.
Unified Modeling Language, Programming paradigm, Dynamic logic, Sequence diagram and Executable are the core of his Programming language study.
David Harel combines subjects such as Algorithm, Graph drawing and Concurrency with his study of Theoretical computer science.
His research links Finite-state machine with Concurrency.
The various areas that David Harel examines in his Reactive system study include Visualization, Semantics, Human–computer interaction and Live sequence charts.
He is studying Complex system, which is a component of Artificial intelligence.
He most often published in these fields:
- Programming language (27.30%)
- Theoretical computer science (17.87%)
- Reactive system (14.89%)
What were the highlights of his more recent work (between 2010-2021)?
- Programming language (27.30%)
- Programming paradigm (6.20%)
- Software engineering (13.40%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Programming language, Programming paradigm, Software engineering, Reactive system and Artificial intelligence.
His study focuses on the intersection of Programming language and fields such as Theoretical computer science with connections in the field of Concurrent computing.
His work deals with themes such as Object, Robot and Software, Software development, which intersect with Software engineering.
The Software development study combines topics in areas such as Layer and Component.
His Reactive system research incorporates themes from Context, System model, Correctness, Semantics and Visualization.
His work in Artificial intelligence covers topics such as Executable which are related to areas like Computational model.
Between 2010 and 2021, his most popular works were:
- Behavioral programming (112 citations)
- Biology as reactivity (48 citations)
- Model-checking behavioral programs (32 citations)
In his most recent research, the most cited papers focused on:
- Programming language
- Artificial intelligence
- Algorithm
David Harel spends much of his time researching Programming language, Programming paradigm, Reactive system, Behavioral programming and Distributed computing.
His study in Programming language is interdisciplinary in nature, drawing from both Theoretical computer science and Code generation.
David Harel has researched Programming paradigm in several fields, including AspectJ, Construct and Compiler.
His Reactive system research includes elements of Correctness, Immunology, Human–computer interaction, Semantics and Visualization.
His studies in Distributed computing integrate themes in fields like Computational biology, Temporal modeling and Tumor growth.
His Formal verification research is multidisciplinary, incorporating perspectives in Concurrency, Software engineering, Intelligent verification and Software verification.
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