What is he best known for?
The fields of study he is best known for:
- Programming language
- Operating system
- Artificial intelligence
His primary scientific interests are in Programming language, Symbolic execution, Model checking, Theoretical computer science and Java.
His Programming language study integrates concerns from other disciplines, such as Ranking, Task and Code.
The various areas that he examines in his Symbolic execution study include Class, Probabilistic logic, Program synthesis and Symbolic trajectory evaluation.
In his study, Intelligent verification, Data type and Loop invariant is strongly linked to Software verification, which falls under the umbrella field of Model checking.
Willem Visser combines subjects such as Computer programming, Counterexample, Interface, Syntax and Container with his study of Theoretical computer science.
His studies in Java integrate themes in fields like Tree, Software and Software engineering.
His most cited work include:
- Model checking programs (1316 citations)
- Generalized symbolic execution for model checking and testing (518 citations)
- Test input generation with java PathFinder (443 citations)
What are the main themes of his work throughout his whole career to date?
Willem Visser mainly focuses on Programming language, Model checking, Symbolic execution, Theoretical computer science and Java.
His work on Promela, Java pathfinder, Real time Java and Concurrency is typically connected to The Symbolic as part of general Programming language study, connecting several disciplines of science.
His Model checking research integrates issues from Software, Computer programming and State space.
His Software study incorporates themes from Formal methods and Software engineering.
His research integrates issues of Program analysis, Probabilistic logic, Data structure and Symbolic trajectory evaluation in his study of Symbolic execution.
He has included themes like Thread and State in his Java study.
He most often published in these fields:
- Programming language (45.38%)
- Model checking (44.62%)
- Symbolic execution (38.46%)
What were the highlights of his more recent work (between 2017-2020)?
- Symbolic execution (38.46%)
- Programming language (45.38%)
- Java (26.92%)
In recent papers he was focusing on the following fields of study:
Willem Visser spends much of his time researching Symbolic execution, Programming language, Java, Java bytecode and Pathfinder.
Willem Visser has researched Symbolic execution in several fields, including Model checking, Component and Constraint satisfaction problem.
Willem Visser connects Programming language with Competition in his research.
His Java research is multidisciplinary, incorporating elements of Program analysis and Android.
His Program analysis research incorporates themes from Theoretical computer science, Satisfiability modulo theories, Constraint, Bottleneck and Key.
His work deals with themes such as State, Software model checker, Static analysis, Benchmark and PATH, which intersect with Java bytecode.
Between 2017 and 2020, his most popular works were:
- Author ranking evaluation at scale (9 citations)
- How to evaluate rankings of academic entities using test data (7 citations)
- Saffron: Adaptive Grammar-based Fuzzing for Worst-Case Analysis (6 citations)
In his most recent research, the most cited papers focused on:
- Programming language
- Artificial intelligence
- Operating system
His main research concerns Ranking, Learning to rank, Java, Programming language and Citation.
Stability, Measure, Rank and Discriminative model is closely connected to Test data in his research, which is encompassed under the umbrella topic of Ranking.
The concepts of his Java study are interwoven with issues in Concolic execution, Concolic testing, Program analysis and Concurrency.
His work on Symbolic execution, Extension and Java bytecode as part of general Programming language study is frequently linked to Executor, bridging the gap between disciplines.
Willem Visser interconnects Percentile, Field, Information retrieval, PageRank and Bibliometrics in the investigation of issues within Citation.
His PageRank research incorporates elements of Citation analysis, Statistics, Author citation and Citation impact.
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