World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
35
Citations
5648
World Ranking
11646
National Ranking
457

Overview

Ayse Bener is affiliated with Toronto Metropolitan University in Canada and has contributed extensively to the field of computer science with a focus on software engineering and artificial intelligence. Their research spans multiple subfields including information systems, software, computer vision and pattern recognition, and electrical and electronic engineering.

Their work addresses several main topics such as software engineering research, software reliability and analysis research, software engineering techniques and practices, advanced text analysis techniques, stock market forecasting methods, topic modeling, and generative adversarial networks and image synthesis.

Ayse Bener's recent publications include:

  • A deep reinforcement learning approach for the meal delivery problem, 2022, Knowledge-Based Systems
  • Machine Learning-Based Radio Coverage Prediction in Urban Environments, 2020, IEEE Transactions on Network and Service Management
  • Courier routing and assignment for food delivery service using reinforcement learning, 2021, Computers & Industrial Engineering
  • Does biomarker use in oncology improve clinical trial failure risk? A large-scale analysis, 2021, Cancer Medicine
  • Order dispatching for an ultra-fast delivery service via deep reinforcement learning, 2021, Applied Intelligence

Frequent co-authors collaborating with Ayse Bener include Mücahit Çevik, Aysun Bozanta, Hadi Jahanshahi, Sanaz Mohammadjafari, and Ozan Ozyegen.

The researcher has published most often in venues such as arXiv (Cornell University), Applied Intelligence, SN Computer Science, Journal of Systems and Software, and SSRN Electronic Journal.

Best Publications

  • On the relative value of cross-company and within-company data for defect prediction

    Burak Turhan;Tim Menzies;Ayşe B. Bener;Justin Di Stefano

  • Defect prediction from static code features: current results, limitations, new approaches

    Tim Menzies;Zach Milton;Burak Turhan;Bojan Cukic

  • Exploiting the Essential Assumptions of Analogy-Based Effort Estimation

    E. Kocaguneli;T. Menzies;A. Bener;J. W. Keung

  • Implications of ceiling effects in defect predictors

    Tim Menzies;Burak Turhan;Ayse Bener

  • Analysis of Naive Bayes' assumptions on software fault data: An empirical study

    Burak Turhan;Ayse Bener

  • Empirical evaluation of the effects of mixed project data on learning defect predictors

    Burak Turhan;Ayşe Tosun Mısırlı;Ayşe Bener

  • Semantic matchmaker with precondition and effect matching using SWRL

    Ayse B. Bener;Volkan Ozadali;Erdem Savas Ilhan

  • Software effort estimation using machine learning methods

    B. Baskeles;B. Turhan;A. Bener

  • Validation of network measures as indicators of defective modules in software systems

    Ayşe Tosun;Burak Turhan;Ayşe Bener

  • Practical considerations in deploying statistical methods for defect prediction: A case study within the Turkish telecommunications industry

    Ayşe Tosun;Ayşe Bener;Burak Turhan;Tim Menzies

  • Software Defect Identification Using Machine Learning Techniques

    Evren Ceylan;F. Kutlubay;Ayse Bener

  • An industrial case study of classifier ensembles for locating software defects

    Ayşe Tosun Mısırlı;Ayşe Başar Bener;Burak Turhan

  • Bayesian Networks For Evidence-Based Decision-Making in Software Engineering

    Ayse Tosun Misirli;Ayse Basar Bener

  • Data mining source code for locating software bugs

    Burak Turhan;Gozde Kocak;Ayse Bener

  • Reducing false alarms in software defect prediction by decision threshold optimization

    Ayse Tosun;Ayse Bener

  • Mobile Web services: a new agent-based framework

    Unknown

  • Ensemble of neural networks with associative memory (ENNA) for estimating software development costs

    Yigit Kultur;Burak Turhan;Ayse Bener

  • Feature weighting heuristics for analogy-based effort estimation models

    Ayse Tosun;Burak Turhan;Ayse Basar Bener

  • Practical considerations in deploying AI for defect prediction: a case study within the Turkish telecommunication industry

    Ayşe Tosun;Burak Turhan;Ayşe Bener

  • AI-Based Software Defect Predictors: Applications and Benefits in a Case Study

    Ayse Tosun Misirli;Ayse Basar Bener;Resat Kale

  • Predicting bug-fixing time: A replication study using an open source software project

    Shirin Akbarinasaji;Bora Caglayan;Ayse Bener

Frequent Co-Authors

Burak Turhan
Burak Turhan Monash University
Tim Menzies
Tim Menzies North Carolina State University
Leandro L. Minku
Leandro L. Minku University of Birmingham
Massimiliano Di Penta
Massimiliano Di Penta University of Sannio
Bojan Cukic
Bojan Cukic University of North Carolina at Charlotte
Tracy Hall
Tracy Hall Lancaster University
Steve Counsell
Steve Counsell Brunel University London
Markku Oivo
Markku Oivo University of Oulu
Stefan Wagner
Stefan Wagner University of Stuttgart
Ian Gorton
Ian Gorton Northeastern University

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