What is he best known for?
The fields of study he is best known for:
- Software
- Software engineering
- Operating system
Adam Porter mainly investigates Software, Software engineering, Software development, Reliability engineering and Software system.
His studies deal with areas such as Empirical research, Software deployment and Formal specification as well as Software.
He has included themes like Software measurement, Software quality, Software project management, Package development process and Software requirements in his Software engineering study.
The Software quality control and Software quality analyst research Adam Porter does as part of his general Software quality study is frequently linked to other disciplines of science, such as Quality assurance, therefore creating a link between diverse domains of science.
The Software development study combines topics in areas such as Machine learning, Data mining and Artificial intelligence.
The various areas that Adam Porter examines in his Reliability engineering study include Cost–benefit analysis, Software inspection, Test suite, Test case and Regression testing.
His most cited work include:
- Comparing detection methods for software requirements inspections: a replicated experiment (380 citations)
- A history-based test prioritization technique for regression testing in resource constrained environments (327 citations)
- An empirical study of regression test selection techniques (318 citations)
What are the main themes of his work throughout his whole career to date?
Software, Software engineering, Software system, Software development and Software quality are his primary areas of study.
His studies in Software integrate themes in fields like Cost–benefit analysis, Reliability engineering and Data mining.
His research integrates issues of Software maintenance, Regression testing, Formal verification and Non-regression testing in his study of Reliability engineering.
His Data mining research is multidisciplinary, incorporating perspectives in Machine learning and Artificial intelligence.
His research in Software engineering intersects with topics in Software requirements specification, Software metric, Systems engineering and Software requirements.
When carried out as part of a general Software system research project, his work on Software measurement is frequently linked to work in Configuration space, therefore connecting diverse disciplines of study.
He most often published in these fields:
- Software (39.47%)
- Software engineering (36.84%)
- Software system (28.95%)
What were the highlights of his more recent work (between 2012-2020)?
- Software system (28.95%)
- Machine learning (10.53%)
- Artificial intelligence (10.53%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Software system, Machine learning, Artificial intelligence, Software and Software engineering.
His Software system study combines topics from a wide range of disciplines, such as Theoretical computer science, Data mining, Set, Software fault tolerance and Test set.
As part of one scientific family, Adam Porter deals mainly with the area of Software fault tolerance, narrowing it down to issues related to the Computerized adaptive testing, and often Reliability engineering.
His work on Deep learning as part of general Machine learning research is frequently linked to Facial recognition system, bridging the gap between disciplines.
His work on Component-based software engineering as part of general Software research is often related to Reuse, thus linking different fields of science.
His Software engineering study deals with Regression testing intersecting with Test data generation and Systems engineering.
Between 2012 and 2020, his most popular works were:
- Moving Forward with Combinatorial Interaction Testing (46 citations)
- Reducing Masking Effects in CombinatorialInteraction Testing: A Feedback DrivenAdaptive Approach (30 citations)
- The past, present, and future of MOOCs and their relevance to software engineering (26 citations)
In his most recent research, the most cited papers focused on:
- Software
- Operating system
- Software engineering
His main research concerns Software system, Software fault tolerance, Set, Machine learning and Artificial intelligence.
His Software system research is classified as research in Software.
His Software fault tolerance study combines topics in areas such as Computerized adaptive testing, Combinatorial interaction testing, Theoretical computer science, Software testing and Software engineering.
His study in Set is interdisciplinary in nature, drawing from both Test, Model-based testing, Autonomous system and System under test.
The study incorporates disciplines such as Test design, Reliability engineering, Software quality assurance and Scenario testing in addition to Machine learning.
His study on Classifier is often connected to Naive Bayes classifier as part of broader study in Artificial intelligence.
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