Master Degree / Yüksek Lisans Tezleri

Permanent URI for this collectionhttps://hdl.handle.net/11147/3008

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Author: search.filters.author.Demirörs, Onur

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  • Master Thesis
    Predicting Software Size From Requirements Written in Natural Language: a Generative Ai Approach
    (01. Izmir Institute of Technology, 2024) Kennouche, Dhıa Eddıne; Demirörs, Onur
    In project management, software size measurement represents a critical process aimed at visualizing a project. This quantification is pursued independently of the specific technologies or technical decisions adopted during the project's development phase. Among the various methodologies employed for this purpose, the COSMIC Functional Size Measurement (FSM) and Event Points are used to facilitate such assessments. These methodologies are instrumental in offering a standardized approach for measuring software size, yet they inherently demand a considerable amount of manual effort. Furthermore, these methods require the manual extraction of Objects of Interest and Event Names, adding to the labor-intensive nature of the process. In response to these challenges, this thesis implements a suite of Artificial Intelligence (AI)-based methods that have dramatically transformed the measurement process. These innovative approaches encompass the creation of a Regression Model that predicts software sizes with remarkable accuracy, a Summarization Model that automates the extraction of Event Names, and a finely tuned Large Language Model (LLM) that generates Objects of Interest with a significant precision. The adoption of these AI-driven techniques has proven to be highly successful, substantially minimizing the manual effort traditionally required in software size measurement and thereby greatly enhancing both efficiency and reliability of estimation practices. Together, these AI-based methodologies represent a significant advancement in software size measurements, offering a more streamlined and efficient approach. By reducing the reliance on manual processes, these methods not only enhance the accuracy and reliability of measurements but also contribute to a more agile project management environment.
  • Master Thesis
    Modeling Microservice Based Applications: Model Lives Inside Code Approach
    (01. Izmir Institute of Technology, 2024) Ersoy, Eyüp Fatih; Demirörs, Onur
    In today's software development, maintaining consistent documentation is crucial for sharing and preserving team knowledge. As projects grow more complex, developers need to quickly understand and maintain code. However, keeping documentation aligned with business logic without unnecessary technical details is challenging. Traditional visualization tools like UML, sequence, and activity diagrams focus on object-oriented approaches and often require manual updates, making them less suitable for event-based systems like microservices. To address these issues, the tool Docupyt was developed using eEPC (Extended Event Process Chains) as the main modeling approach. Docupyt is designed with three key principles: ease of use, simplicity (including only necessary logic), and reactivity (representing event-based systems). eEPC notation helps analyze problems and represent changing logic during development, accommodating fast-changing requirements. It supports both high and low-level process definitions and focuses on business logic without extraneous technical details. Generated directly from code through simple commenting, this approach simplifies updating documentation as the code changes, reducing maintenance costs. Using the design science research method, Docupyt was validated in a case study, demonstrating it is user-friendly and provides adequate detail without being overly technical. Its main advantage is keeping documentation in sync with code logic, easing updates.
  • Master Thesis
    Testing Microservice Applications
    (2023) Öztürk, Özgür; Ayav, Tolga; Demirörs, Onur
    This thesis contributes to the testing processes of microservice architecture. Microservices provide a scalable, reliable and cloud-based environment that is frequently preferred in today's technology applications. It consists of small, loosely coupled, isolated applications that work in harmony. In this study, microservice application is modeled using timed automata and model checker-based testing methods are exploited to generate test cases automatically. To this end, UPPAAL model checker tool is utilized. The model of the microservice application is mutated with respect to a set of fault hypotheses and these mutant models are verified against certain properties defined by system or application specifications. The returned counterexamples from the model checker are used to constitute the test cases. The entire process is automated and experimentally run for an example application. The generated test cases are also shown to be efficiently detect the errors. The proposed testing methodology has the benefits like a faster test generation process and achieving test cases with better fault detection capability
  • Master Thesis
    A Mutation-Based Approach To Alleviate the Class Imbalance Problem in Software Defect Prediction
    (01. Izmir Institute of Technology, 2023) Güner, Dinçer; Demirörs, Onur; Demirörs, Onur; Giray, Görkem
    Highly imbalanced training datasets considerably degrade the performance of software defect predictors. Software Defect Prediction (SDP) datasets have a general problem, which is class imbalance. Therefore, a variety of methods have been developed to alleviate Class Imbalance Problem (CIP). However, these classical methods, like data-sampling, balance datasets without connecting any relation with SDP. Over-sampling techniques generate synthetic minor class instances, which generalize a small number of minor class instances and result in less diverse instances, whereas under-sampling techniques eliminate major class instances, resulting in significant information loss. In this study, we present an approach that uses software mutations to balance software repositories. Mutation-based Approach (MBA) injects mutants into defect-free instances, causing them to transform into defective instances. In this way, MBA balances datasets with diverse data produced by mutation operators, and there is no loss on instances as in under-sampling. For recall scores, almost all rebalancing methods outperformed Baseline in Inter-release Defect Prediction (IRDP) scenario but only MBA significantly outperformed Baseline in Cross-project Defect Prediction (CPDP) scenario. The performance increase in recall resulted in the production of more false alarms. We can not generalize that MBA outperforms Baseline and the five over-sampling strategies in terms of AUC scores. In terms of recall values, the MBA performed better in CPDP than IRDP. For both IRDP and CPDP scenarios, there were significant and positive correlations between SMC (the change percentage of software measures) and recall, and SMC and false alarm but there was no significant correlation between SMC and AUC.
  • Master Thesis
    Blockchain Based Context Aware Access Control Structure Implementation for Security of Internet of Things System
    (01. Izmir Institute of Technology, 2022) Kul, Aslı; Demirörs, Onur; Erten, Yusuf Murat
    Nowadays, Internet of Things (IoT) devices, which have started to be included in our lives with the developing technology, are one of the popular working topics. While they are a means of transporting many important data in terms of usage areas, IoT devices have brought security concerns due to their being a new technology and technical limitations. The use of standard access control algorithms is insufficient for IoT environments due to their complexity and dynamism. In this study, considering the importance of sensitive critical data carried by IoT environments, Context Aware IoT Rule Based Access Control Algorithm, which is a proposed algorithm to ensure the security of interaction with IoT environments, is aimed to be integrated and used to create a reliable IoT environment by taking advantage of the security promising Blockchain technology. It is due to the use of distributed and cryptography methods that are widely used today.