What is he best known for?
The fields of study he is best known for:
- Software
- Software engineering
- Artificial intelligence
Thomas Zimmermann mainly focuses on Software, Data mining, Software engineering, Software bug and World Wide Web.
Component-based software engineering is the focus of his Software research.
His Software engineering study incorporates themes from Codebook, Graph and Software quality, Software development.
In Software development, he works on issues like Software system, which are connected to Program analysis.
The Software bug study combines topics in areas such as False positives and false negatives, Outlier, Public domain software, Source code and Debugging.
His work on Information needs as part of general World Wide Web research is often related to Tracking system, thus linking different fields of science.
His most cited work include:
- Mining version histories to guide software changes (781 citations)
- When do changes induce fixes (599 citations)
- Predicting Defects for Eclipse (585 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Software, Software engineering, Software development, Software system and Data science.
His research investigates the connection between Software and topics such as Data mining that intersect with problems in Source code.
His study looks at the intersection of Software engineering and topics like Software quality with Reliability engineering.
His Software development study typically links adjacent topics like World Wide Web.
His study brings together the fields of Database and Software system.
His biological study spans a wide range of topics, including Personal software process, Software peer review and Software Engineering Process Group.
He most often published in these fields:
- Software (44.32%)
- Software engineering (32.58%)
- Software development (27.27%)
What were the highlights of his more recent work (between 2017-2021)?
- Software (44.32%)
- Software development (27.27%)
- Engineering management (5.30%)
In recent papers he was focusing on the following fields of study:
His main research concerns Software, Software development, Engineering management, Software engineering and Empirical research.
His Software research includes themes of Scale, Public relations, Knowledge management and Data science.
His study in Software development is interdisciplinary in nature, drawing from both Multimedia and Happiness.
His study explores the link between Engineering management and topics such as Greatness that cross with problems in Knowledge engineering and Personal software process.
He studied Software engineering and F1 score that intersect with Task analysis.
In his study, Software bug is inextricably linked to Data mining, which falls within the broad field of Empirical research.
Between 2017 and 2021, his most popular works were:
- Software engineering for machine learning: a case study (155 citations)
- Data Scientists in Software Teams: State of the Art and Challenges (58 citations)
- Four commentaries on the use of students and professionals in empirical software engineering experiments (22 citations)
In his most recent research, the most cited papers focused on:
- Software
- Programming language
- Software engineering
The scientist’s investigation covers issues in Software, Software engineering, Engineering management, Knowledge management and Job satisfaction.
A large part of his Software studies is devoted to Software development.
In the field of Software development, his study on Software analytics overlaps with subjects such as Peer support.
His Software engineering research incorporates elements of F1 score, Learning classifier system, Taxonomy, Web search query and Documentation.
His Engineering management study combines topics from a wide range of disciplines, such as Greatness, Empirical research and Open science.
His research integrates issues of Research design, Program management, Affect and Personalization in his study of Knowledge management.
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