Uzunbayır, Serhat
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Uzunbayir, Serhat
Uzunbayir, S.
Uzunbayir, S.
Job Title
Email Address
uzunbayir.serhat@ieu.edu.tr
Main Affiliation
05.04. Software Engineering
Status
Current Staff
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Scopus Author ID
Turkish CoHE Profile ID
Google Scholar ID
WoS Researcher ID
Sustainable Development Goals
8
DECENT WORK AND ECONOMIC GROWTH
1
Research Products
9
INDUSTRY, INNOVATION AND INFRASTRUCTURE
1
Research Products
10
REDUCED INEQUALITIES
0
Research Products
17
PARTNERSHIPS FOR THE GOALS
0
Research Products
12
RESPONSIBLE CONSUMPTION AND PRODUCTION
0
Research Products
7
AFFORDABLE AND CLEAN ENERGY
0
Research Products
1
NO POVERTY
0
Research Products
5
GENDER EQUALITY
0
Research Products
13
CLIMATE ACTION
0
Research Products
4
QUALITY EDUCATION
1
Research Products
14
LIFE BELOW WATER
0
Research Products
2
ZERO HUNGER
0
Research Products
15
LIFE ON LAND
0
Research Products
16
PEACE, JUSTICE AND STRONG INSTITUTIONS
0
Research Products
6
CLEAN WATER AND SANITATION
0
Research Products
3
GOOD HEALTH AND WELL-BEING
0
Research Products
11
SUSTAINABLE CITIES AND COMMUNITIES
0
Research Products
Documents
9
Citations
14
h-index
2
Documents
4
Citations
5
Scholarly Output
12
Articles
2
Views / Downloads
11/21
Supervised MSc Theses
1
Supervised PhD Theses
1
WoS Citation Count
5
Scopus Citation Count
14
WoS h-index
1
Scopus h-index
2
Patents
0
Projects
0
WoS Citations per Publication
0.42
Scopus Citations per Publication
1.17
Open Access Source
2
Supervised Theses
2
| Journal | Count |
|---|---|
| UBMK 2024 - Proceedings: 9th International Conference on Computer Science and Engineering -- 9th International Conference on Computer Science and Engineering, UBMK 2024 -- 26 October 2024 through 28 October 2024 -- Antalya -- 204906 | 2 |
| Proceedings - 7th International Conference on Computer Science and Engineering, UBMK 2022 | 2 |
| Computing and Informatics | 1 |
| International Journal of Intelligent Systems and Applications in Engineering | 1 |
| 14th International Symposium on Image and Signal Processing and Analysis-ISPA-Biennial -- Oct 29-31, 2025 -- Coimbra, Portugal | 1 |
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12 results
Scholarly Output Search Results
Now showing 1 - 10 of 12
Conference Object Citation - Scopus: 1Reverse Ant Colony Optimization for the Winner Determination Problem in Combinatorial Auctions(Institute of Electrical and Electronics Engineers Inc., 2022) Uzunbayır, SerhatAn auction is an effective process of trading items among bidders and sellers. Combinatorial auctions are auctions in which bidders can place bids on a bundle of items rather than bidding on a single item. As a result, they lead to more efficient allocations compared to traditional auctions. Determining the winners whose bids maximize the auctioneer's profit is known as the winner determination problem. The problem is NP-complete since it is not possible to solve it in polynomial time as the inputs increase. In this paper, reverse ant colony optimization algorithm is proposed for the problem which focuses on maximization of the ants' route instead of minimization of the regular version. The experimental results are compared using different size data sets with a previously proposed genetic algorithm and a random search algorithm. The experiments indicate that, as the search space expands, the proposed algorithm finds better solutions than the others. © 2022 IEEE.Article Citation - Scopus: 1Leveraging Genetic Algorithms for Efficient Search-Based Higher Order Mutation Testing(Slovak acad sciences inst informatics, 2024) Uzunbayır, Serhat; Kurtel, KaanHigher order mutation testing is a type of white -box testing in which the source code is changed repeatedly using two or more mutation operators to generate mutated programs. The objective of this procedure is to improve the design and execution phases of testing by allowing testers to automatically evaluate their test cases. However, generating higher order mutants is challenging due to the large number of mutants needed and the complexity of the mutation search space. To address this challenge, the problem is modeled as a search problem. The purpose of this study is to propose a genetic algorithm-based search technique for mutation testing. The expected outcome is a reduction in the number of equivalent high order mutants produced, leading to a minimum number of mutant sets that produce an adequate mutation score. The experiments were carried out and the results were compared with a random search algorithm and four different versions of the proposed genetic algorithm which use different selection methods: roulette wheel, tournament, rank, and truncation selection. The results indicate that the number of equivalent mutants and the execution cost can be reduced using the proposed genetic algorithm with respect to the selection method.Conference Object Citation - Scopus: 3Relational Database and Nosql Inspections Using Mongodb and Neo4j on a Big Data Application(Institute of Electrical and Electronics Engineers Inc., 2022) Uzunbayır, SerhatThe importance of big data, one of the most popular and researched topics of today, has been a subject of constant debate. Big data appear in almost every aspect of our lives, such as healthcare, education, shopping, social media, and industry; however, its storage and processing is not very efficient when using traditional methods. Therefore, the aim of this study is to obtain big data using a novel social shopping application that collects data from its users. The application is designed to collect information about people, products, and friendships among people, as well as product relationships, and post creations, and also enables setting up various options to mark products, such as like, buy, have, or help. The data gathered by the system is analyzed using both relational and non-relational databases, and the performance of these databases is then compared using specific queries, to reveal the model which performs better and more efficiently. Three different database models were designed and implemented for the system; a relational database, a document database, and a graph database. As a result of the experiments, there is no single model that is superior to the others as all three databases have their advantages and disadvantages. Therefore, the database selection should be decided based on the application domain. © 2022 IEEE.Article Citation - Scopus: 1Evocolony: a Hybrid Approach To Search-Based Mutation Test Suite Reduction Using Genetic Algorithm and Ant Colony Optimization(Ismail Saritas, 2024) Uzunbayır, Serhat; Kurtel, K.The increasing complexity of software systems requires robust and efficient test suites to ensure software quality. In this context, mutation testing emerges as an invaluable method for evaluating a test suite’s the fault detection capability. Traditional approaches to test case generation and evaluation are often inadequate, particularly when applied to mutation testing, which aims to evaluate the quality of a test suite by introducing minor changes or mutations to the code. As software projects increase in scale, there is greater computational cost of employing exhaustive mutation testing techniques, leading to a need for more efficient approaches. Incorporating metaheuristics into the realm of mutation testing offers a synergistic advantage in optimizing test suites for better fault detection. Especially, combining test suite reduction methods with mutation testing produces a more computationally efficient approach compared to more exhaustive ones. This study presents a novel approach, called EvoColony, which combines intelligent search-based algorithms, specifically genetic algorithms and ant colony optimization, to reduce test cases and enhance the effectiveness of the test suit for mutation testing. Integrating both metaheuristic techniques, the research aims to optimize existing test suites, and to improve mutant detection with fewer test cases, thus improving the overall testing quality. The results of experiments conducted were compared with traditional methods, demonstrating the superior effectiveness and efficiency of the proposed hybrid approach. The findings show a significant advancement in test case reduction when using the hybrid algorithm with mutation testing methodologies, and thus ensure the quality of test suites. © 2024, Ismail Saritas. All rights reserved.Conference Object Mining Software Requirements From Turkish Texts: Techniques and Challenges(Institute of Electrical and Electronics Engineers Inc., 2024) Uzunbayir, S.; Metin, S.K.Extraction of software requirements from natural language texts becomes more important in requirements engi-neering for the identification o f stakeholder needs hidden in big documentation. However, it ensures that the system goals will be completely understood. This step is principal for improving communication, refining documentation, and providing a clear set of requirements that guide software development and quality as-surance. The complexity and ambiguity of natural languages are significant, and mostly result in misinterpretations or incomplete requirements. The relevant information is usually scattered over several documents and communication channels, thus accurate capture remains still difficult. Extracting requirements from Turkish texts adds further challenges due to its unique features, such as high level of agglutination. This linguistic complexity makes natural language processing (NLP) tasks like tokenization, morphological and syntactic analysis more challenging. The great problem is even further amplified b y t he fact that t here are very few comprehensive NLP tools and resources available for the Turkish language. This paper reviews NLP methods used for software requirement extraction, emphasizing challenges and techniques that are applicable to Turkish texts in general and, specifically, the richness of morphology and word order flexibility and the tight-associated inherent ambiguities in this language. Moreover, we cover current studies in this area and describe the available libraries, tools, and resources for NLP in Turkish, pointing out the limitations and possible lines of future research. © 2024 IEEE.Conference Object Citation - Scopus: 2A Genetic Algorithm for the Winner Determination Problem in Combinatorial Auctions(Institute of Electrical and Electronics Engineers Inc., 2018) Uzunbayır, SerhatAuctions are a very popular way of allocating multiple items. There are three different auction types, such as sequential auctions, parallel auctions, and combinatorial auctions. This study focuses on combinatorial auctions. Combinatorial auctions allow bidders to bid on a collection of items rather than a single item. This results in more efficient allocations than traditional auctions. The problem is determining the winners of all bids in a way that maximizes the auctioneer's profit. Some instances of the problem may be solvable in polynomial time with a few items and bidders. However, with excessive numbers of items and bidders, the problem becomes NP-complete. In this paper, a genetic algorithm is proposed and compared with a random search algorithm on various sized datasets. The results for experiments indicate that the proposed genetic algorithm performs better than random search as the size of the problem increases. © 2018 IEEE.Conference Object Citation - WoS: 1Citation - Scopus: 2A Review of Source Code Management Tools for Continuous Software Development(IEEE, 2018) Uzunbayir, Serhat; Kurtel, KaanContinuous software development practices are very important in all organizations to deploy latest improvements of their products rapidly, reliably, and in a repeatable manner. In order to achieve these features, software development processes should provide a stable source code management. Nowadays many organizations are producing multiple releases per day, and this is also possible even with large projects and complex code bases. To facilitate such continuous activities, various tools have been developed over the years. In this article, we identify, review, and reveal the characteristics of available tools to summarize their best features, as well as to identify which tools can be used for specific continuous software practices.Doctoral Thesis Enhancing Mutation Testing: Search-Based Optimization To Improve Testing Quality(İzmir Ekonomi Üniversitesi, 2024) Uzunbayır, Serhat; Kurtel, KaanYazılım testi, yazılım geliştirme yaşam döngüsünün önemli bir aşamasıdır. Kapsamlı test faaliyetleri olmadan ortaya çıkan ürün kullanışsız veya güvenilmezdir. Kaynak kodundaki değişiklikler test paketlerinin yeniden yürütülmesini gerektirdiği için, kod kapsamı projenin gereksinimleriyle uyumlu olmalıdır. Hata odaklı bir şeffaf kutu birim test tekniği olan mutasyon testi, test paketlerinin kalitesinin değerlendirilmesi ve test prosedürlerindeki zayıflıkların belirlenmesi için kullanılır. Mutasyon testinin uygulanması her ne kadar etkili olsa da, yüksek maliyetler, eşdeğer mutantların varlığı ve test paketlerindeki test fazlalıkları nedenlerinden dolayı uygulamada zorluklar göstermektedir. Bu çalışmada, yazılım mühendisliğinde mutasyon testi araştırılmış, klasik metodolojilerden yapay zeka ve yenilikçi hibrit tekniklerin entegrasyonuna kadar gelişiminin izini sürülmüştür. Mutasyon testinin geleneksel ilkeleri ve problemleri incelenmiş ve C\# programlama dili için mutasyon test araçlarının derinlemesine analizi yapılmıştır. Test grubu azaltma problemini optimize etmek için iki metasezgisel yöntemi (genetik algoritmalar ve karınca kolonisi optimizasyonu) birleştiren arama tabanlı mutaston testi için yeni bir hibrit yöntem sunulmuştur. Eşdeğer mutantlar sorunu, daha üst düzey mutasyon testlerinin verimliliğini artırmak için genetik algoritmalar kullanılarak ele alınmıştır. Sonuç olarak bu çalışma, test kalitesinin iyileştirilmesi için mutasyon testine katkı sağlamaktadır. Gelişmiş hesaplama tekniklerini entegre eden, böylece daha etkili, verimli ve gelişmiş yazılım kalite güvence uygulamalarının önünü açan yaklaşımlar önermiştir.Conference Object Citation - WoS: 4Citation - Scopus: 4An Analysis on Mutation Testing Tools for C# Programming Language(Institute of Electrical and Electronics Engineers Inc., 2019) Uzunbayır, Serhat; Kurtel, KaanMutation testing is a fault-based white-box software testing technique which uses artificial defects known as mutants to represent faulty versions of the application to evaluate the quality of the test suite. It is a costly method in terms of time and efficiency, since it requires a vast amount of mutants to be generated. For this reason, mutant generation should be performed automatically with the help of automated tools. There are a number of mutation testing tools available and each one is supported by a single programming language. In this study, we analyze mutation testing tools for C#. We focus on different characteristics of the tools and aim to help the testers when deciding which tool they can use for their implementations by providing a comparative analysis. © 2019 IEEE.Conference Object Shieldir: AI-Powered Real-Time Threat Detection System To Reduce Crime Response Time(IEEE, 2025) Arda, Berkay; Samur, Ahmet Alp; Marifoglu, Furkan; Bulut, Fikri Barca; Uzunbayir, SerhatThe rapid growth of urban populations and increasing social inequalities have contributed to a rise in violent crimes in public spaces. Traditional surveillance systems, relying mainly on passive CCTV cameras, often fail to support timely interventions. Although these systems record incidents, their inability to interpret real-time behaviors-such as weapon use and violent acts-limits their effectiveness. As a result, critical crimes like armed robbery, assault, arson, vandalism, and domestic violence frequently go unnoticed, especially in areas without active human monitoring. To address this challenge, we propose ShielDir, a threat detection system powered by artificial intelligence (AI) that performs real-time analysis of human behaviors and weapon presence using deep learning models, identifying threats across 14 categories of criminal activity. The system provides instant alerts to authorities, reducing response times and enhancing public safety in live or recorded video streams. ShielDir integrates YOLOv11 for weapon detection and OPear, a VideoMAE-based model for behavior analysis, within a containerized microservice architecture supported by Kafka to enable seamless, real-time data streaming and processing.
