What is he best known for?
The fields of study he is best known for:
- Software
- Software engineering
- Statistics
His primary scientific interests are in Software engineering, Software development, Software, Software development process and Software quality.
The study incorporates disciplines such as Management science, Reading, Reliability, Software product line and Software construction in addition to Software engineering.
His Management science study integrates concerns from other disciplines, such as Research methodology, Experimental software engineering, Information system and Technical debt.
His Software development study combines topics in areas such as Engineering management and Systems engineering.
His Software research includes elements of Empirical research and Information retrieval.
His Social software engineering research includes themes of Presentation, Personal software process, Process and Software requirements.
His most cited work include:
- Guidelines for conducting and reporting case study research in software engineering (2284 citations)
- Experimentation in Software Engineering: An Introduction (2167 citations)
- Experimentation in Software Engineering (1403 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Software engineering, Software, Software development, Reliability engineering and Knowledge management.
His work in Software engineering covers topics such as Process which are related to areas like Product innovation.
His Software research is multidisciplinary, relying on both Empirical research, Information retrieval, Data science and Reading.
His Empirical process, Package development process and Component-based software engineering study, which is part of a larger body of work in Software development, is frequently linked to Product, bridging the gap between disciplines.
His Reliability engineering study incorporates themes from Software system, Software quality, Software reliability testing, Test case and Reliability.
His work on Software Engineering Process Group is being expanded to include thematically relevant topics such as Social software engineering.
He most often published in these fields:
- Software engineering (29.91%)
- Software (22.65%)
- Software development (22.22%)
What were the highlights of his more recent work (between 2014-2021)?
- Open innovation (6.84%)
- Software engineering (29.91%)
- Software (22.65%)
In recent papers he was focusing on the following fields of study:
Open innovation, Software engineering, Software, Knowledge management and Data science are his primary areas of study.
The concepts of his Software engineering study are interwoven with issues in Empirical evidence, Software development, Software testing, Design science and Requirements engineering.
His research in the fields of Software analytics and Software requirements overlaps with other disciplines such as Surprise and Waterfall.
His Software system study in the realm of Software interacts with subjects such as Scale.
His Personal software process, Social software engineering and Software Engineering Process Group investigations are all subjects of Software system research.
His studies in Knowledge management integrate themes in fields like Quality, Public sector and Paradigm shift.
Between 2014 and 2021, his most popular works were:
- Automated bug assignment: Ensemble-based machine learning in large scale industrial contexts (76 citations)
- Case studies synthesis: a thematic, cross-case, and narrative synthesis worked example (63 citations)
- Open innovation in software engineering: a systematic mapping study (55 citations)
In his most recent research, the most cited papers focused on:
- Software
- Statistics
- Software engineering
His primary areas of investigation include Software, Software engineering, Data science, Knowledge management and Open innovation.
His study in the field of Exploratory testing also crosses realms of Scale.
His Software engineering research is multidisciplinary, incorporating elements of Management science, Design science research, Design science, Knowledge engineering and Visualization.
His studies deal with areas such as Product innovation, Model-driven architecture, Modeling language, Open data and Process as well as Open innovation.
Per Runeson merges many fields, such as Empirical data and Software development, in his writings.
As a part of the same scientific family, Per Runeson mostly works in the field of Software development, focusing on Set and, on occasion, Artificial intelligence, Machine learning and Data mining.
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