What is he best known for?
The fields of study he is best known for:
- Software
- Operating system
- Programming language
Andy Zaidman spends much of his time researching Software engineering, Software, Software maintenance, Software system and Program comprehension.
He interconnects Process, KPI-driven code analysis, Unit testing, Code review and Data science in the investigation of issues within Software engineering.
His Software research is multidisciplinary, incorporating perspectives in Java, Field and Data mining.
His biological study spans a wide range of topics, including Software as a service and Clipboard.
His work deals with themes such as Business process reengineering, Multitenancy and Software architecture, which intersect with Software system.
His Program comprehension research incorporates elements of Scalability, Theoretical computer science, Documentation and Software visualization.
His most cited work include:
- A Systematic Survey of Program Comprehension through Dynamic Analysis (314 citations)
- Work practices and challenges in pull-based development: the contributor's perspective (214 citations)
- Multi-tenant SaaS applications: maintenance dream or nightmare? (170 citations)
What are the main themes of his work throughout his whole career to date?
Andy Zaidman focuses on Software engineering, Software, Software system, Software maintenance and Test case.
His Software engineering study combines topics in areas such as Java, Reverse engineering, Software quality, Process and Software construction.
His Software research is multidisciplinary, incorporating elements of Agile software development, Data mining, Reliability engineering, Code and Data science.
His Software system research is multidisciplinary, relying on both Software development and Source code.
His Software maintenance research includes themes of Business process reengineering and Program comprehension.
The study incorporates disciplines such as Machine learning, Unit testing, Artificial intelligence and Code coverage in addition to Test case.
He most often published in these fields:
- Software engineering (39.41%)
- Software (26.11%)
- Software system (26.11%)
What were the highlights of his more recent work (between 2019-2021)?
- Test case (13.79%)
- Software (26.11%)
- Artificial intelligence (9.36%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Test case, Software, Artificial intelligence, Machine learning and Debugging.
While the research belongs to areas of Test case, Andy Zaidman spends his time largely on the problem of Code coverage, intersecting his research to questions surrounding Unit testing, Theoretical computer science and Code.
Andy Zaidman studies Software, focusing on Software system in particular.
In his study, Set, Orthogonality, Feature and Code smell is strongly linked to Process, which falls under the umbrella field of Artificial intelligence.
His Debugging research is multidisciplinary, relying on both Software engineering, Crash and Benchmark.
His Software engineering study incorporates themes from Software testing and Body of knowledge.
Between 2019 and 2021, his most popular works were:
- Beyond Technical Aspects: How Do Community Smells Influence the Intensity of Code Smells? (26 citations)
- How developers engage with static analysis tools in different contexts (16 citations)
- How bugs are born: a model to identify how bugs are introduced in software components (11 citations)
In his most recent research, the most cited papers focused on:
- Software
- Operating system
- Programming language
Andy Zaidman mainly focuses on Data science, Software development, Code smell, Context and Artificial intelligence.
His work carried out in the field of Data science brings together such families of science as Software evolution, Code review, Software quality, Joint and Workflow.
His studies deal with areas such as Source lines of code, Software engineering, Root cause and Source code as well as Software development.
His research integrates issues of Software system and Software in his study of Root cause.
The concepts of his Software study are interwoven with issues in Mathematical optimization and Fault detection and isolation.
His research investigates the connection between Code smell and topics such as Code that intersect with problems in Metric.
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