What is he best known for?
The fields of study he is best known for:
- Programming language
- Artificial intelligence
- Software
Mark Harman spends much of his time researching Search-based software engineering, Software, Software engineering, Data mining and Empirical research.
His work carried out in the field of Search-based software engineering brings together such families of science as Simulated annealing, Theoretical computer science, Genetic algorithm, Hill climbing and Project planning.
His research investigates the connection between Software and topics such as Genetic programming that intersect with problems in Code.
The various areas that Mark Harman examines in his Software engineering study include Software peer review, Software development, Software Engineering Process Group, Software construction and Model checking.
Mark Harman has researched Data mining in several fields, including Fitness function, Software system, Cluster analysis, Fault detection and isolation and Test case.
His work focuses on many connections between Empirical research and other disciplines, such as Test, that overlap with his field of interest in Test data generation, Evolutionary algorithm and Mathematical optimization.
His most cited work include:
- An Analysis and Survey of the Development of Mutation Testing (1131 citations)
- Regression testing minimization, selection and prioritization: a survey (883 citations)
- Search-based software engineering (677 citations)
What are the main themes of his work throughout his whole career to date?
Mark Harman mainly investigates Software engineering, Search-based software engineering, Software, Programming language and Theoretical computer science.
The study incorporates disciplines such as Software system, Software development, Social software engineering, Software construction and Systems engineering in addition to Software engineering.
His Search-based software engineering study integrates concerns from other disciplines, such as Test data generation, Artificial intelligence, Data mining and Software Engineering Process Group.
His Data mining research incorporates themes from Machine learning and Test case.
He interconnects Genetic programming and Data science in the investigation of issues within Software.
His Programming language research includes elements of Code and Slicing.
He most often published in these fields:
- Software engineering (22.32%)
- Search-based software engineering (18.51%)
- Software (16.70%)
What were the highlights of his more recent work (between 2013-2021)?
- Software (16.70%)
- Artificial intelligence (12.16%)
- Software engineering (22.32%)
In recent papers he was focusing on the following fields of study:
Mark Harman mostly deals with Software, Artificial intelligence, Software engineering, Machine learning and Search-based software engineering.
His work deals with themes such as Task, Code, Source code, Genetic programming and Data science, which intersect with Software.
His Artificial intelligence research includes themes of Test, Empirical research and Natural language processing.
His study in Software engineering is interdisciplinary in nature, drawing from both Software system, Software development and Social software engineering.
Mark Harman works mostly in the field of Machine learning, limiting it down to topics relating to Data mining and, in certain cases, Software metric, as a part of the same area of interest.
His Search-based software engineering research is under the purview of Software construction.
Between 2013 and 2021, his most popular works were:
- The Oracle Problem in Software Testing: A Survey (427 citations)
- Sapienz: multi-objective automated testing for Android applications (262 citations)
- A Survey of App Store Analysis for Software Engineering (235 citations)
In his most recent research, the most cited papers focused on:
- Programming language
- Artificial intelligence
- Software
His main research concerns Software, Search-based software engineering, Software engineering, Artificial intelligence and Genetic programming.
His Software research integrates issues from Field, Baseline and Task.
His Search-based software engineering study necessitates a more in-depth grasp of Software construction.
Mark Harman combines subjects such as Smart device, Online and offline, Commit, Chunking and Adaptive software with his study of Software engineering.
In his study, Workflow and Correctness is inextricably linked to Machine learning, which falls within the broad field of Artificial intelligence.
The concepts of his Genetic programming study are interwoven with issues in Systems engineering, CUDA, Graphics hardware and General-purpose computing on graphics processing units.
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