What is he best known for?
The fields of study he is best known for:
- Operating system
- Software
- Programming language
His main research concerns Software, Software engineering, Data mining, Software quality and World Wide Web.
His Software research incorporates themes from Code and Source code.
Ahmed E. Hassan has researched Software engineering in several fields, including Software as a service, Software maintenance, Software development, KPI-driven code analysis and Software peer review.
His Data mining research includes elements of Predictive modelling, Machine learning, Random forest and Artificial intelligence.
His study in Software quality is interdisciplinary in nature, drawing from both Empirical research and Software construction.
His World Wide Web research integrates issues from Android and Internet privacy.
His most cited work include:
- Predicting faults using the complexity of code changes (487 citations)
- What are developers talking about? An analysis of topics and trends in Stack Overflow (324 citations)
- A large-scale empirical study of just-in-time quality assurance (266 citations)
What are the main themes of his work throughout his whole career to date?
Software, Software engineering, World Wide Web, Software system and Source code are his primary areas of study.
Ahmed E. Hassan has included themes like Data science, Data mining, Database and Code in his Software study.
The study incorporates disciplines such as Software quality, Software maintenance, Software development, KPI-driven code analysis and Software peer review in addition to Software engineering.
His study focuses on the intersection of World Wide Web and fields such as Empirical research with connections in the field of Software development process.
His work carried out in the field of Software system brings together such families of science as Reliability engineering and Real-time computing.
Ahmed E. Hassan interconnects Topic model and Software build in the investigation of issues within Source code.
He most often published in these fields:
- Software (29.75%)
- Software engineering (25.34%)
- World Wide Web (20.11%)
What were the highlights of his more recent work (between 2016-2021)?
- Software (29.75%)
- World Wide Web (20.11%)
- Empirical research (12.67%)
In recent papers he was focusing on the following fields of study:
Ahmed E. Hassan spends much of his time researching Software, World Wide Web, Empirical research, Artificial intelligence and Mobile apps.
His Software study combines topics in areas such as Software engineering, Information retrieval and Source code.
In general World Wide Web, his work in Download is often linked to Publishing linking many areas of study.
His research integrates issues of License and Internet privacy in his study of Empirical research.
His study on Artificial intelligence also encompasses disciplines like
- Classifier, Software development and Quality assurance most often made with reference to Machine learning,
- Pattern recognition, which have a strong connection to Feature.
His Software bug study combines topics from a wide range of disciplines, such as Source lines of code and Software quality.
Between 2016 and 2021, his most popular works were:
- An Empirical Comparison of Model Validation Techniques for Defect Prediction Models (201 citations)
- The Impact of Automated Parameter Optimization on Defect Prediction Models (101 citations)
- What do developers search for on the web (73 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Software
- Programming language
His primary areas of study are Software, World Wide Web, Data mining, Artificial intelligence and Software bug.
His study on Software analytics is often connected to Experience report as part of broader study in Software.
His studies deal with areas such as User interface, Android and Central processing unit as well as World Wide Web.
His Data mining research incorporates elements of Data modeling, Categorical variable and Resolution.
His Artificial intelligence research is multidisciplinary, incorporating perspectives in Machine learning and Pattern recognition.
His Software bug study also includes fields such as
- Task, which have a strong connection to Software engineering, Readability and Implementation,
- Contrast which is related to area like Empirical research.
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