People › Dr. Arif Ali Khan
Dr. Arif Ali Khan
PhD Graduate (2017) 2017Now Associate Professor (tenured), M3S Unit of Empirical Software Engineering, University of Oulu, Finland
Personal website ↗About
Dr. Arif Ali Khan is a PhD graduate in the Department of Computer Science, City University of Hong Kong.
Now Associate Professor (tenured), M3S Unit of Empirical Software Engineering, University of Oulu, Finland.
Research Interests
Publications (20)
- Methodology for the quantification of the effect of patterns and anti-patterns association on the software quality.
- GSEPIM: A roadmap for software process assessment and improvement in the domain of global software development.
- Automated framework for classification and selection of software design patterns.
- A methodology to rank the design patterns on the base of text relevancy.
- Systematic literature study for dimensional classification of success factors affecting process improvement in global software development: client-vendor perspective.
- Implications of deep learning for the automation of design patterns organization.
- Towards a hypothetical framework of humans related success factors for process improvement in global software development: systematic review.
- The Effect of Gang-of-Four Design Patterns Usage on Design Quality Attributes.
- Systematic literature review and empirical investigation of barriers to process improvement in global software development: Client-vendor perspective.
- Systematic Literature Reviews of Software Process Improvement: A Tertiary Study.
- Software design patterns classification and selection using text categorization approach.
- SPIIMM: Toward a Model for Software Process Improvement Implementation and Management in Global Software Development.
- Correlation between the Frequent Use of Gang-of-Four Design Patterns and Structural Complexity.
- A Framework for Ranking of Software Design Patterns.
- Understanding software process improvement in global software development
- Systematic review of success factors and barriers for software process improvement in global software development.
- Detection of Fault-Prone Classes Using Logistic Regression Based Object-Oriented Metrics Thresholds.
- A Methodology to Automate the Selection of Design Patterns.
- Performance Evaluation of Ensemble Methods For Software Fault Prediction: An Experiment.
- Effects of Geographical, Socio-cultural and Temporal Distances on Communication in Global Software Development during Requirements Change Management - A Pilot Study.