What is he best known for?
The fields of study he is best known for:
- Programming language
- Software
- Operating system
His main research concerns Theoretical computer science, Software, Graph drawing, Visualization and Programming language.
The study incorporates disciplines such as Algorithm and Enhanced Data Rates for GSM Evolution in addition to Theoretical computer science.
His work is dedicated to discovering how Software, Data mining are connected with Software prototyping and Change impact analysis and other disciplines.
His research in Software prototyping intersects with topics in Program analysis, Software maintenance and Set.
His study in Graph drawing is interdisciplinary in nature, drawing from both Modular decomposition and Force-directed graph drawing.
His Visualization research incorporates elements of Software visualization and Human–computer interaction.
His most cited work include:
- Mining version histories to guide software changes (781 citations)
- Mining version histories to guide software changes (462 citations)
- Software Visualization: Visualizing the Structure, Behaviour, and Evolution of Software (211 citations)
What are the main themes of his work throughout his whole career to date?
Stephan Diehl mainly investigates Software, Visualization, Programming language, Software visualization and Software engineering.
His work deals with themes such as World Wide Web and Source code, which intersect with Software.
His Visualization study incorporates themes from Theoretical computer science and Data science.
His study looks at the intersection of Theoretical computer science and topics like Graph drawing with Readability, Scalability and Modular decomposition.
As part of one scientific family, Stephan Diehl deals mainly with the area of Programming language, narrowing it down to issues related to the VRML, and often Scene graph and Graphics.
His research in Data mining focuses on subjects like Software evolution, which are connected to Software maintenance.
He most often published in these fields:
- Software (30.51%)
- Visualization (22.03%)
- Programming language (19.77%)
What were the highlights of his more recent work (between 2015-2021)?
- Software (30.51%)
- Stack overflow (4.52%)
- Information retrieval (6.21%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Software, Stack overflow, Information retrieval, Software development and Source code.
His research integrates issues of Java and Relation in his study of Software.
His Information retrieval research is multidisciplinary, incorporating elements of Graph drawing and Empirical research.
His Graph drawing study also includes
- Data complexity which intersects with area such as Information visualization,
- Human–computer interaction most often made with reference to Scalability.
His Software development research integrates issues from Software system and Software engineering.
The subject of his Source code research is within the realm of Programming language.
Between 2015 and 2021, his most popular works were:
- A Taxonomy and Survey of Dynamic Graph Visualization (161 citations)
- SOTorrent: reconstructing and analyzing the evolution of stack overflow posts (50 citations)
- Towards a theory of software development expertise (36 citations)
In his most recent research, the most cited papers focused on:
- Programming language
- Software
- Operating system
Stephan Diehl mostly deals with Software, Information retrieval, Stack overflow, Empirical research and Graph drawing.
His studies deal with areas such as Software engineering, Relation and Management science as well as Software.
His Software engineering research includes elements of Requirements engineering, Requirements analysis and Software construction.
He has researched Empirical research in several fields, including Data complexity, Readability, Complex network and Graph visualisation.
His biological study spans a wide range of topics, including Visual complexity, Scalability and Information visualization.
His Software development research integrates issues from Iterative and incremental development and Systems engineering.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
