What is he best known for?
The fields of study he is best known for:
- Operating system
- Software
- Programming language
Alexander Pretschner spends much of his time researching Model-based testing, Computer security, Test case, World Wide Web and Software engineering.
His Model-based testing research is multidisciplinary, incorporating elements of Test strategy, Model checking, Data mining and Taxonomy.
His biological study spans a wide range of topics, including Virtualization, Semantics and Resilience.
His work in Test case addresses issues such as System testing, which are connected to fields such as Non-regression testing.
His research integrates issues of Control and Information retrieval in his study of World Wide Web.
His work deals with themes such as Computational science and Reactive system, Systems engineering, which intersect with Software engineering.
His most cited work include:
- A taxonomy of model-based testing approaches (402 citations)
- Model-Based Testing of Reactive Systems, Advanced Lectures (393 citations)
- Ontology based personalized search (361 citations)
What are the main themes of his work throughout his whole career to date?
Alexander Pretschner mainly investigates Computer security, Software engineering, Control, Software and Model-based testing.
His work is connected to Access control and Malware, as a part of Computer security.
His Software engineering research is multidisciplinary, incorporating perspectives in Software development, Systems engineering and Social software engineering.
His Software study integrates concerns from other disciplines, such as Machine learning and Artificial intelligence.
His work in Model-based testing covers topics such as Programming language which are related to areas like Theoretical computer science.
His Test case research incorporates elements of System testing and Reliability engineering.
He most often published in these fields:
- Computer security (18.95%)
- Software engineering (15.32%)
- Control (11.29%)
What were the highlights of his more recent work (between 2018-2021)?
- Artificial intelligence (7.66%)
- Machine learning (6.85%)
- Causal model (3.23%)
In recent papers he was focusing on the following fields of study:
Alexander Pretschner mainly investigates Artificial intelligence, Machine learning, Causal model, Software system and Process.
Alexander Pretschner has included themes like Domain, Test case, Parameterized complexity and Functional specification in his Artificial intelligence study.
His research in Machine learning intersects with topics in Test suite, Scenario testing, Data modeling and Malware.
Alexander Pretschner has researched Causal model in several fields, including Computer security and Preemption.
His Software system research is within the category of Software.
His work in Process addresses subjects such as Task, which are connected to disciplines such as Task analysis.
Between 2018 and 2021, his most popular works were:
- Leveraging Compression-Based Graph Mining for Behavior-Based Malware Detection (18 citations)
- Did We Test All Scenarios for Automated and Autonomous Driving Systems (16 citations)
- Fitness Functions for Testing Automated and Autonomous Driving Systems (11 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Software
- Artificial intelligence
Alexander Pretschner mostly deals with Machine learning, Artificial intelligence, Scenario testing, Causality and Causal model.
His Machine learning study incorporates themes from Domain, Software, Symbolic execution and Baseline.
His studies in Artificial intelligence integrate themes in fields like Data modeling, Data flow diagram, Data mining and Fuzz testing.
His Scenario testing research includes themes of Reliability engineering, Test case, Process and Functional specification.
His Test case research integrates issues from Envelope, Collision and Parameterized complexity.
He combines subjects such as Optimization problem and Inference with his study of Theoretical computer science.
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