IZTECH Software Engineering and Artificial Intelligence Research Group

IZTECH Software Engineering and Artificial Intelligence Research Group

About Us

IZTECH Software Engineering and Artificial Intelligence Research Group was founded to develop AI-based solutions for software engineering foundations. Our team is dedicated to advancing the foundations of software engineering through the innovative application of artificial intelligence. By integrating cutting-edge AI technologies with core software engineering principles, we strive to develop robust, efficient, and intelligent solutions that address complex challenges in the field.  We aim to lead the advancement of software practice in Turkey and bring forth experts and scientists in the field. Our research is directed mainly towards the following areas:

        • AI-based Solutions for Software Measurement and Estimation
        • Software Estimation
        • Software Measurement
        • Microservice-based Architecture
        • Software Project Management
        • Business Process Management
        • People

People

            Prof. Dr.                   Onur Demirörs

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Hüseyin Ünlü
PhD Candidate

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Samet Tenekeci
PhD Candidate

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     Ali Yıldız
PhD Candidate 

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    Melih Yenel
Master’s Student

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Past Members

  • Assist. Prof. Dr. Tuna Hacaloğlu  
  • Dr. Neslihan Küçkateş Ömüral
  • Assist. Prof. Dr. Görkem Kılınç Soylu
  • Eyüp Fatih Ersoy
  • Dhia Eddine Kennouche
  • Uğurcan Selçuk
  • Muhammed Efe İncir
  • Burak Keçeci
  • Can Çiftçi
  • İbrahim Baran Oral
  • Tunahan Atalay
  • Fatma Büber
  • Kıvılcım Berrak
  • İhsan Can Yalabuk
  • Berk Önal
  • Mehmet Kutay Akpınar

Research

  • Completed Theses
    • Graduate Project
      • Using Natural Language Processing for Software Size Prediction: A Company-Specific Approach by Muhammed Efe İncir
      • Functional Size Prediction of Turkish Software Requirements Using Natural Language Processing by Burak Keçeci
      • AI-Based Software Size Estimation for Different Requirements Abstraction Levels by Can Çiftçi, İbrahim Baran Oral, and Tunahan Atalay
      • Using Machine Learning for Predicting Software Size from Requirements by Fatma Büber and Kıvılcım Berrak
      • Task Scheduling and Resource Allocation with Genetic Algorithm by Berk Önal and İhsan Can Yalabuk
    • Master’s Theses
      • Predicting Software Size From Requirements Written In Natural Language: A Generative AI Approach by Dhia Eddine Kennouche
      • Modeling Microservice-Based Applications: Model Lives Inside Code Approach by Eyüh Fatih Ersoy
      • Effort and Size Estimation in Video Game Development Through Fine-Tuned NLP Models by Uğurcan Selçuk
    • PhD Theses
      • Event Points: A Software Size Measurement Model by Tuna Hacaloğlu
      • A Software Size Measurement Method for Enterprise Applications by Neslihan Küçükateş Ömüral
  • Ongoing Theses
    • Graduate Project
      • Predicting COSMIC Size From The Code Using Natural Language Processing by Bedir Arda Gül
      • Predicting MicroM Size From The Code Using Natural Language Processing by  Murat Küçük and Damla Keleş
    • Master’s Theses
      • A Size Measurement Method for Changes in Requirements of a Microservice-Based Application by Melih Yenel
    • PhD Theses
      • MicroM: A Size Measurement Method for Microservice-based Architectures by Hüseyin Ünlü
      • MicroArc: An Analysis and Design Method for Microservice Based Systems by Ali Yıldız

Projects

  • Ongoing Projects
    • A Software Size Measurement Method and Automated Tool for Microservice-Based Architectures:  This project aims to develop a software size measurement method based on the units that better define new generation architectures, such as microservices. In addition, the method will include the measurement of change requests, and it will be supported by a software tool to automate the measurements. The project is supported by the TUBITAK 1001 program.
    • AI-Estimator: AI-Based Size Measurement and Effort Prediction Tool: This project aims to provide software size measurement and effort estimation by using LLM models of traditional software architectures and microservice-based architectures. Software organizations can use the pre-trained model to predict a project’s software size and effort using its requirements, or a tailored model can be established using historical project requirements. The project is carried out with our sector partner, Bilgi Grubu, and is supported by the TUBITAK-TEYDEB 1501 program.
  • Completed Projects
    • Microarc: An Analysis and Design Method for Microservices Architectures: This project aims to provide a method and modeling notations to analyze and design Microservice-based software systems. Software organizations use Microarc to model processes, identify microservices,  and make early size estimations of software systems to be developed. The project is carried out with our sector partner, Bilgi Grubu, and is supported by the TUBITAK-TEYDEB 1501 program.

Announcements

  • We are glad to announce that our paper titled “Predicting Software Functional Size Using Natural Language Processing: An Exploratory Case Study” has been accepted for the 50th Euromicro Conference Series on Software Engineering and Advanced Applications (SEAA) 2024. The paper will be presented by Hüseyin Ünlü at the conference, which will be held in Paris from August 28-30, 2024. Congratulations to the authors Hüseyin Ünlü, Samet Tenekeci, Can Çiftçi, İbrahim Baran Oral, Tunahan Atalay, Tuna Hacaloğlu, Burcu Musaoğlu, and Onur Demirörs. Details can be found on the conference website https://dsd-seaa.com.
  • We are glad to announce that our paper titled “Towards the Construction of a Software Benchmarking Dataset via Systematic Literature Review” has been accepted for the 50th Euromicro Conference Series on Software Engineering and Advanced Applications (SEAA) 2024. The paper will be presented by Hüseyin Ünlü at the conference, which will be held in Paris from August 28-30, 2024. Congratulations to the authors Ozan Raşit Yürüm, Hüseyin Ünlü, and Onur Demirörs. Details can be found on the conference website https://dsd-seaa.com.
  • We are glad to announce that our paper titled “Predicting Software Size and Effort from Code Using Natural Language Processing” has been accepted for the Joint Conference of the 33rd International Workshop on Software Measurement (IWSM) and the 18th International Conference on Software Process and Product Measurement (MENSURA). The paper will be presented by Samet Tenekeci at the conference, which will be held in Montreal from October 3-4, 2024. Congratulations to the authors Samet Tenekeci, Hüseyin Ünlü, Emre Dikenelli, Uğurcan Selçuk, Görkem Kılınç Soylu and Onur Demirörs. Details can be found on the conference website https://www.iwsm-mensura.org.
 
  • Onur Demirörs will be giving a workshop titled “Event-based Size Measurement for Reactive Microservice-based Systems” at The Joint Conference of the 33rd International Workshop on Software Measurement (IWSM) and the 18th International Conference on Software Process and Product Measurement (MENSURA), taking place on October 3-4 in Montreal, Canada. Details can be found on the website https://www.iwsm-mensura.org.
 
  • Samet Tenekeci will be giving a workshop titled “Automated Size and Effort Estimation with Natural Language Processing” at The Joint Conference of the 33rd International Workshop on Software Measurement (IWSM) and the 18th International Conference on Software Process and Product Measurement (MENSURA), taking place on October 3-4 2024 in Montreal, Canada. Details can be found on the conference website https://www.iwsm-mensura.org.

Contact

Prof. Dr. Onur Demirors

    • İzmir Yüksek Teknoloji Enstitüsü – Bilgisayar Mühendisliği Bölümü
    • Gülbahçe Kampüsü 35430 Urla İzmir Türkiye
    • onurdemirors@iyte.edu.tr
    • +90 232 750 7881

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