Ayşe Tosun

About Ayşe Tosun

Ayşe Tosun, With an exceptional h-index of 27 and a recent h-index of 19 (since 2020), a distinguished researcher at Istanbul Teknik Üniversitesi, specializes in the field of Software engineering, Artificial Intelligence.

His recent articles reflect a diverse array of research interests and contributions to the field:

Analyzing the concept of technical debt in the context of agile software development: A systematic literature review

Exploring the relationship between refactoring and code debt indicators

Automated Fairness Testing with Representative Sampling

A Comparison of Source Code Representation Methods to Predict Vulnerability Inducing Code Changes.

Profiling developers to predict vulnerable code changes

The Evaluation of BH-AllStar Approach in the Industry: A Case Study

Measuring Bug Reporter's Reputation and Its Effect on Bug Resolution Time Prediction

A deep reinforcement learning approach for the meal delivery problem

Ayşe Tosun Information

University

Position

Assistant Prof. at Faculty of Computer and Informatics Engineering

Citations(all)

2458

Citations(since 2020)

1322

Cited By

1594

hIndex(all)

27

hIndex(since 2020)

19

i10Index(all)

50

i10Index(since 2020)

36

Email

University Profile Page

Google Scholar

Ayşe Tosun Skills & Research Interests

Software engineering

Artificial Intelligence

Top articles of Ayşe Tosun

Analyzing the concept of technical debt in the context of agile software development: A systematic literature review

2024/1

Exploring the relationship between refactoring and code debt indicators

Journal of Software: Evolution and Process

2024/1

Automated Fairness Testing with Representative Sampling

2023/12/8

A Comparison of Source Code Representation Methods to Predict Vulnerability Inducing Code Changes.

2023

Profiling developers to predict vulnerable code changes

2022/11/7

The Evaluation of BH-AllStar Approach in the Industry: A Case Study

2022/9/14

Ayşe Tosun
Ayşe Tosun

H-Index: 19

Measuring Bug Reporter's Reputation and Its Effect on Bug Resolution Time Prediction

2022/9/14

A deep reinforcement learning approach for the meal delivery problem

Knowledge-Based Systems

2022/5/11

Predicting vulnerability inducing function versions using node embeddings and graph neural networks

Information and Software Technology

2022/5/1

Order dispatching for an ultra-fast delivery service via deep reinforcement learning

Applied Intelligence

2022/3/1

Courier routing and assignment for food delivery service using reinforcement learning

Computers & Industrial Engineering

2022/2/1

An Automated Approach for Mapping Between Software Requirements and Design Items: An Industrial Case from Turkey

2022/1/21

Ayşe Tosun
Ayşe Tosun

H-Index: 19

A Condition Coverage-Based Black Hole Inspired Meta-Heuristic for Test Data Generation

2021/12

Deployment of a change‐level software defect prediction solution into an industrial setting

Journal of Software: Evolution and Process

2021/11

Investigating the performance of personalized models for software defect prediction

Journal of Systems and Software

2021/11/1

Deep learning based topic classification for sensitivity assignment to personal data

2021/9/15

Ayşe Tosun
Ayşe Tosun

H-Index: 19

Ensemble and Cross-Project Software Reliability Growth Models for Safety-Critical Systems

2021/9/15

Predicting Requirements Volatility: An Industry Case Study

2021

An empirical study on the effect of community smells on bug prediction

Software Quality Journal

2021/3

See List of Professors in Ayşe Tosun University(Istanbul Teknik Üniversitesi)

Co-Authors

academic-engine