What is he best known for?
The fields of study he is best known for:
- Programming language
- Software
- Artificial intelligence
His scientific interests lie mostly in Programming language, Software, Software engineering, Software development and Java.
His Programming language study frequently links to related topics such as Product.
As a part of the same scientific family, Sven Apel mostly works in the field of Software, focusing on Variable and, on occasion, Structure and Text processing.
Sven Apel combines subjects such as Program comprehension, Feature and Legacy system with his study of Software engineering.
His work on Software construction, Component-based software engineering and Software measurement as part of general Software development study is frequently connected to Reuse, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
His Software product line study combines topics in areas such as Theoretical computer science and Data mining.
His most cited work include:
- Feature-Oriented Software Product Lines (395 citations)
- Granularity in software product lines (394 citations)
- An Overview of Feature-Oriented Software Development. (327 citations)
What are the main themes of his work throughout his whole career to date?
Sven Apel focuses on Software, Programming language, Software engineering, Software system and Software development.
His Software research focuses on Software product line in particular.
His Software product line study integrates concerns from other disciplines, such as Feature model, Theoretical computer science and Feature selection.
His Programming language and Feature-oriented programming, Java, Aspect-oriented programming, Code refactoring and Correctness investigations all form part of his Programming language research activities.
His research in Software engineering intersects with topics in Program comprehension, Preprocessor, Source code and Code.
His studies deal with areas such as Machine learning, Set and Artificial intelligence as well as Software system.
He most often published in these fields:
- Software (30.90%)
- Programming language (25.58%)
- Software engineering (25.25%)
What were the highlights of his more recent work (between 2017-2021)?
- Software system (20.60%)
- Software (30.90%)
- Code (8.64%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Software system, Software, Code, Program comprehension and Sampling.
The various areas that Sven Apel examines in his Software system study include Machine learning, Computer engineering and Artificial intelligence.
His research on Software focuses in particular on Search-based software engineering.
His Code research is multidisciplinary, relying on both Static analysis, Debugging and Software engineering, White box.
Sven Apel interconnects Software portability, Preprocessor, Software development and Source code in the investigation of issues within Software engineering.
His Source code research focuses on Software maintenance and how it connects with Conditional compilation and Feature-oriented programming.
Between 2017 and 2021, his most popular works were:
- Finding Faster Configurations Using FLASH (39 citations)
- Data-efficient performance learning for configurable systems (36 citations)
- Faster discovery of faster system configurations with spectral learning (28 citations)
In his most recent research, the most cited papers focused on:
- Programming language
- Software
- Artificial intelligence
Sven Apel mostly deals with Software system, Software, Program comprehension, Computer engineering and Configuration space.
His work on Software configuration management as part of general Software system research is frequently linked to Sampling, thereby connecting diverse disciplines of science.
Software is often connected to Algorithm in his work.
His study in Program comprehension is interdisciplinary in nature, drawing from both Eye tracking, Functional magnetic resonance imaging and Cognition.
Sven Apel has included themes like Optimization problem and Set in his Computer engineering study.
His Task analysis study combines topics from a wide range of disciplines, such as Java and Source code.
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