WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7150
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Conference Object Enhancing Genomic Data Sharing With Blockchain-Enabled Dynamic Consent in Beacon V2(Springernature, 2024) Binokay, Leman; Celik, Hamit Mervan; Gurdal, Gultekin; Ayav, Tolga; Tuglular, Tugkan; Oktay, Yavuz; Karakulah, GokhanConference Object Avoidance of Feature Configuration Faults in Software Product Lines(IEEE Computer Soc, 2025) Ergun, Burcu; Tuglular, Tugkan; Belli, FevziThis paper presents a validation approach to feature selection in software product lines (SPL). SPLs consist of similar products tailored to different needs, while SPLs sharing a common platform where feature configurations define product families. Validating feature configurations is critical to avoid defective shipments, recalls, and disposal. Exhaustive, pairwise, and combinatorial testing, among others, aim at ensuring configuration correctness. This paper introduces a novel method for improving feature selection and validation in SPLs by minimizing redundancy while ensuring configurations align with customer needs. The method emphasizes uncovering the differences in feature structures through "complex" and "simple" models, which helps identify and helps identify and tolerate potential errors arising from incorrect feature configurations. This ensures broader coverage while effectively managing dependencies. A case study using the Access Point (AP) SPL model, which is a networking device designed to enhance the strength of an existing wireless signal and expand its coverage area. The AP can enable or disable specific features on AP SPL depending on the characteristics of the third-party gateway with which it is integrated. AP SPL model with 66 features lead to 266 configurations, generated by Exhaustive Testing. Pairwise testing achieves 87% coverage with 132 test cases, while combinatorial testing reaches 94% with 45,760 cases. Our method ensures 100% feature coverage with just 3 test configurations. Thus, the approach introduced in this paper enhances product quality while reducing costs by avoiding redundant tests, making the approaches valuable for large-scale SPLs.Conference Object Enhancing genomic data sharing with blockchain-enabled dynamic consent in beacon V2(Springernature, 2024) Binokay, Leman; Celik, Hamit Mervan; Gurdal, Gultekin; Ayav, Tolga; Tuglular, Tugkan; Oktay, Yavuz; Karakulah, GokhanConference Object Citation - WoS: 1Konteyner Görüntülerini Kullanarak Hasar Tespiti ve Sınıflandırması(IEEE, 2020) Imamoglu, Zeynep Ekici; Tuglular, Tugkan; Bastanlar, YalinIn the logistics sector, digital transformation is of great importance in terms of competition. In the present case, container warehouse entry / exit operations are carried out manually by the logistics personnel including container damage detection. During container warehouse entry / exit process, the process of detecting damaged containers is carried out by the personnel and several minutes are required to upload to the IT system. The aim of our work is to automate the detection of damaged containers. This way, the mistakes made by the personnel will be eliminated and the process will be accelerated. In this work, we propose to use a convolutional neural network (CNN) that takes the container images and classify them as damaged or undamaged. We modeled the problem as a binary classification and employed different CNN models. The result we obtained shows that there is no single best method for the classification. It is shown how the dataset was created and how the parameters used in the layered structures affect the models employed in this study.Article Citation - WoS: 5Unifying Behavioral and Feature Modeling for Testing of Software Product Lines(World Scientific Publ Co Pte Ltd, 2024) Belli, Fevzi; Tuglular, Tugkan; Ufuktepe, EkincanExisting software product line (SPL) engineering testing approaches generally provide positive testing that validates the SPL's functionality. Negative testing is commonly neglected. This research aims to unify behavioral and feature models of an SPL, enable testing before and after variability binding for domain-centric and product-centric testing, and combine positive and negative testing for a holistic testing view. This study suggests behavioral modeling with event sequence graphs (ESGs). This heterogeneous modeling strategy supports bottom-up domain testing and top-down product testing with the feature model. This new feature-oriented ESG test creation method generates shorter test sequences than the original ESG optimum test sequences. Statechart and original ESG test-generating methods are compared. Positive testing findings are similar. The Statechart technique generated 12 test cases with 59 events, whereas the ESG technique created six test cases with 60 events. The ESG technique generated 205 negative test cases with 858 events with the Test Suite Designer tool. However, the Conformiq Designer tool for the Statechart technique does not have a negative test case generation capability. It is shown that the proposed ESG-based holistic approach confirms not only the desirable (positive) properties but also the undesirable (negative) ones. As an additional research, the traditional ESG test-generating approach is compared to the new feature-oriented method on six SPLs of different sizes and features. Our case study results show that the traditional ESG test generation approach demonstrated higher positive test generation scores compare to the proposed feature-oriented test generation approach. However, our proposed feature-oriented test generation approach is capable of generating shorter test sequences, which could be beneficial for reducing the execution time of test cases compared to traditional ESG approach. Finally, our case study has also shown that regardless of the test generation approach, there has been found no significant difference between the Bottom-up and Top-down test strategies with respect to their positive test generation scores.Article Citation - WoS: 1Citation - Scopus: 3Automatic Test Sequence Generation and Functional Coverage Measurement From Uml Sequence Diagrams(Igi Global, 2023) Ekici, Nazim Umut; Tuglular, TugkanSequence diagrams define functional requirements through use cases. However, their visual form limits their usability in the later stages of the development life cycle. This work proposes a method to transform sequence diagrams into graph-based event sequence graphs, allowing the application of graph analysis methods and defining graph-based coverage criteria. This work explores these newfound abilities in two directions. The first is to use coverage criteria along with existing tests to measure their coverage levels, providing a metric of how well they address the scenarios defined in sequence diagrams. The second is to use coverage criteria to automatically generate effective and efficient acceptance test cases based on the scenarios defined in sequence diagrams. The transformation method is validated with over eighty non-trivial projects. The complete method is validated through a non-trivial example. The results show that the test cases generated with the proposed method are more effective at exposing faults and more efficient in test input size than user-generated test cases.