WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7150
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Article Link Prediction for Completing Graphical Software Models Using Neural Networks(IEEE, 2023) Leblebici, Onur; Tuğlular, Tuğkan; Belli, FevziDeficiencies and inconsistencies introduced during the modeling of software systems may result in high costs and negatively impact the quality of all developments performed using these models. Therefore, developing more accurate models will aid software architects in developing software systems that match and exceed expectations. This paper proposes a graph neural network (GNN) method for predicting missing connections, or links, in graphical models, which are widely employed in modeling software systems. The proposed method utilizes graphs as allegedly incomplete, primitive graphical models of the system under consideration (SUC) as input and proposes links between its elements through the following steps: (i) transform the models into graph-structured data and extract features from the nodes, (ii) train the GNN model, and (iii) evaluate the performance of the trained model. Two GNN models based on SEAL and DeepLinker are evaluated using three performance metrics, namely cross-entropy loss, area under curve, and accuracy. Event sequence graphs (ESGs) are used as an example of applying the approach to an event-based behavioral modeling technique. Examining the results of experiments conducted on various datasets and variations of GNN reveals that missing connections between events in an ESG can be predicted even with relatively small datasets generated from ESG models. AuthorConference Object Kurt saldırıları için sentetik irislerde örnek seçilimi(IEEE, 2023) Akdeniz, Eyüp Kaan; Erdoğmuş, NesliIn this study, samples with higher potential to succeed in wolf attacks are picked among synthetically generated iris images, and the composed subset is shown to pose a more significant threat toward an iris recognition system backed by a Presentation Attack Detection (PAD) module with respect to randomly selected samples. Iris images generated by Deep Convolutional Generative Adversarial Networks (DCGAN) are firstly filtered by rejection sampling on PAD score distribution of real iris image PAD scores. Next, the probability of zero success in all attack attempts is calculated for each synthetic iris image, using real iris images in the training set, and match and non-match score distributions are calculated on those. Synthetic images with the lowest probabilities of zero success are included in the final set. Our hypothesis that this set would be more successful in wolf attacks is tested by comparing its spoofing performances with randomly selected sample sets.Article Citation - WoS: 3Citation - Scopus: 4Application of the Law of Minimum and Dissimilarity Analysis To Regression Test Case Prioritization(IEEE, 2023) Ufuktepe, Ekincan; Tuğlular, TuğkanRegression testing is one of the most expensive processes in testing. Prioritizing test cases in regression testing is critical for the goal of detecting the faults sooner within a large set of test cases. We propose a test case prioritization (TCP) technique for regression testing called LoM-Score inspired by the Law of Minimum (LoM) from biology. This technique calculates the impact probabilities of methods calculated by change impact analysis with forward slicing and orders test cases according to LoM. However, this ordering doesn't consider the possibility that consecutive test cases may be covering the same methods repeatedly. Thereby, such ordering can delay the time of revealing faults that exist in other methods. To solve this problem, we enhance the LoM-Score TCP technique with an adaptive approach, namely with a dissimilarity-based coordinate analysis approach. The dissimilarity-based coordinate analysis uses Jaccard Similarity for calculating the similarity coefficients between test cases in terms of covered methods and the enhanced technique called Dissimilarity-LoM-Score (Dis-LoM-Score) applies a penalty with respective on the ordered test cases. We performed our case study on 10 open-source Java projects from Defects4J, which is a dataset of real bugs and an infrastructure for controlled experiments provided for software engineering researchers. Then, we hand-seeded multiple mutants generated by Major, which is a mutation testing tool. Then we compared our TCP techniques LoM-Score and Dis-LoM-Score with the four traditional TCP techniques based on their Average Percentage of Faults Detected (APFD) results.Data Paper Citation - WoS: 15Citation - Scopus: 20Database Covering the Prayer Movements Which Were Not Available Previously(Nature Publishing Group, 2023) Mihçin, Şenay; Şahin, Ahmet Mert; Yılmaz, Mehmet; Alpkaya, Alican Tuncay; Tuna, Merve; Akdeniz, Sevinç; Can, Nuray Korkmaz; Tosun, Aliye; Şahin, SerapLower body implants are designed according to the boundary conditions of gait data and tested against. However, due to diversity in cultural backgrounds, religious rituals might cause different ranges of motion and different loading patterns. Especially in the Eastern part of the world, diverse Activities of Daily Living (ADL) consist of salat, yoga rituals, and different style sitting postures. A database covering these diverse activities of the Eastern world is non-existent. This study focuses on data collection protocol and the creation of an online database of previously excluded ADL activities, targeting 200 healthy subjects via Qualisys and IMU motion capture systems, and force plates, from West and Middle East Asian populations with a special focus on the lower body joints. The current version of the database covers 50 volunteers for 13 different activities. The tasks are defined and listed in a table to create a database to search based on age, gender, BMI, type of activity, and motion capture system. The collected data is to be used for designing implants to allow these sorts of activities to be performed.Article Citation - WoS: 16Citation - Scopus: 25A Privacy-Preserving Scheme for Smart Grid Using Trusted Execution Environment(IEEE, 2023) Akgün, Mete; Üstündağ Soykan, Elif; Soykan, GürkanThe increasing transformation from the legacy power grid to the smart grid brings new opportunities and challenges to power system operations. Bidirectional communications between home-area devices and the distribution system empower smart grid functionalities. More granular energy consumption data flows through the grid and enables better smart grid applications. This may also lead to privacy violations since the data can be used to infer the consumer's residential behavior, so-called power signature. Energy utilities mostly aggregate the data, especially if the data is shared with stakeholders for the management of market operations. Although this is a privacy-friendly approach, recent works show that this does not fully protect privacy. On the other hand, some applications, like nonintrusive load monitoring, require disaggregated data. Hence, the challenging problem is to find an efficient way to facilitate smart grid operations without sacrificing privacy. In this paper, we propose a privacy-preserving scheme that leverages consumer privacy without reducing accuracy for smart grid applications like load monitoring. In the proposed scheme, we use a trusted execution environment (TEE) to protect the privacy of the data collected from smart appliances (SAs). The scheme allows customer-oriented smart grid applications as the scheme does not use regular aggregation methods but instead uses customer-oriented aggregation to provide privacy. Hence the accuracy loss stemming from disaggregation is prevented. Our scheme protects the transferred consumption data all the way from SAs to Utility so that possible false data injection attacks on the smart meter that aims to deceive the energy request from the grid are also prevented. We conduct security and game-based privacy analysis under the threat model and provide performance analysis of our implementation. Our results demonstrate that the proposed method overperforms other privacy methods in terms of communication and computation cost. The execution time of aggregation for 10,000 customers, each has 20 SAs is approximately 1 second. The decryption operations performed on the TEE have a linear complexity e.g., 172800 operations take around 1 second while 1728000 operations take around 10 seconds. These results can scale up using cloud or hyper-scalers for real-world applications as our scheme performs offline aggregation.Article Citation - WoS: 5Citation - Scopus: 9P/Key: Puf Based Second Factor Authentication(Public Library of Science, 2023) Uysal, Ertan; Akgün, MeteOne-time password (OTP) mechanisms are widely used to strengthen authentication processes. In time-based one-time password (TOTP) mechanisms, the client and server store common secrets. However, once the server is compromised, the client’s secrets are easy to obtain. To solve this issue, hash-chain-based second-factor authentication protocols have been proposed. However, these protocols suffer from latency in the generation of OTPs on the client side because of the hash-chain traversal. Secondly, they can generate only a limited number of OTPs as it depends on the length of the hash-chain. In this paper, we propose a second-factor authentication protocol that utilizes Physically Unclonable Functions (PUFs) to overcome these problems. In the proposed protocol, PUFs are used to store the secrets of the clients securely on the server. In case of server compromise, the attacker cannot obtain the seeds of clients’ secrets and can not generate valid OTPs to impersonate the clients. In the case of physical attacks, including side-channel attacks on the server side, our protocol has a mechanism that prevents attackers from learning the secrets of a client interacting with the server. Furthermore, our protocol does not incur any client-side delay in OTP generation.Article Citation - WoS: 41Citation - Scopus: 50Bim-Carem: Assessing the Bim Capabilities of Design, Construction and Facilities Management Processes in the Construction Industry(Elsevier, 2023) Gökçen, Yılmaz; Akçamete, Aslı; Demirörs, OnurBIM adoption has accelerated worldwide since it is an important enabling technology for digitalisation in the construction industry. Adopting BIM requires transforming the traditional building life cycle stages (planning, design, construction and facilities management) into BIM-integrated project deliveries. Assessing the BIM ca- pabilities of these stages helps organisations to identify gaps in their BIM uses and improve them. There is a lack of a comprehensive model in the literature for assessing the BIM capabilities of individual building life cycle stages and their processes. Existing assessment models focus on assessing the BIM maturity of construction projects and organisations which do not inform the required BIM improvements for individual stages and their processes. Hence, we iteratively developed the Building Information Modelling (BIM) Capability Assessment REference Model (BIM-CAREM) and demonstrated its usability through multiple explanatory case studies per- formed with two international design and engineering companies and two general contractors in Turkey. We assessed the BIM capabilities of design, construction and facility management processes of various buildings i.e. residential, stadiums, hospitals and airports. The results showed that the BIM capability levels of design, con- struction and facility management processes vary within and across the companies.Article Citation - WoS: 2Citation - Scopus: 6Incremental Testing in Software Product Lines-An Event Based Approach(IEEE, 2023) Beyazıt, Mutlu; Tuğlular, Tuğkan; Öztürk Kaya, DilekOne way of developing fast, effective, and high-quality software products is to reuse previously developed software components and products. In the case of a product family, the software product line (SPL) approach can make reuse more effective. The goal of SPLs is faster development of low-cost and high-quality software products. This paper proposes an incremental model-based approach to test products in SPLs. The proposed approach utilizes event-based behavioral models of the SPL features. It reuses existing event-based feature models and event-based product models along with their test cases to generate test cases for each new product developed by adding a new feature to an existing product. Newly introduced featured event sequence graphs (FESGs) are used for behavioral feature and product modeling; thus, generated test cases are event sequences. The paper presents evaluations with three software product lines to validate the approach and analyze its characteristics by comparing it to the state-of-the-art ESG-based testing approach. Results show that the proposed incremental testing approach highly reuses the existing test sets as intended. Also, it is superior to the state-of-the-art approach in terms of fault detection effectiveness and test generation effort but inferior in terms of test set size and test execution effort.Article Citation - WoS: 3Citation - Scopus: 3A Domain-Specific Language for the Document-Based Model-Driven Engineering of Business Applications(IEEE, 2022) Leblebici, Onur; Kardaş, Geylani; Tuğlular, TuğkanTo facilitate the development of business applications, a domain-specific language (DSL), called DARC, is introduced in this paper. Business documents including the descriptions of the responsibilities, authorizations, and collaborations, are used as the first-class entities during model-driven engineering (MDE) with DARC. Hence the implementation of the business applications can be automatically achieved from the corresponding document models. The evaluation of using DARC DSL for the development of commercial business software was performed in an international sales, logistics, and service solution provider company. The results showed that the code for all business documents and more than 50% of the responsibility descriptions composing the business applications could be generated automatically by modeling with DARC. Finally, according to the users' feedback, the assessment clearly revealed the adoption of DARC features in terms of the DSL quality characteristics, namely functional suitability, usability, reliability, maintainability, productivity, extensibility, compatibility, and expressiveness.Article Asking the Right Questions To Solve Algebraic Word Problems(TÜBİTAK - Türkiye Bilimsel ve Teknolojik Araştırma Kurumu, 2022) Çelik, Ege Yiğit; Orulluoğlu, Zeynel; Mertoğlu, Rıdvan; Tekir, SelmaWord algebra problems are among challenging AI tasks as they combine natural language understanding with a formal equation system. Traditional approaches to the problem work with equation templates and frame the task as a template selection and number assignment to the selected template. The recent deep learning-based solutions exploit contextual language models like BERT and encode the natural language text to decode the corresponding equation system. The proposed approach is similar to the template-based methods as it works with a template and fills in the number slots. Nevertheless, it has contextual understanding because it adopts a question generation and answering pipeline to create tuples of numbers, to finally perform the number assignment task by custom sets of rules. The inspiring idea is that by asking the right questions and answering them using a state-of-the-art language model-based system, one can learn the correct values for the number slots in an equation system. The empirical results show that the proposed approach outperforms the other methods significantly on the word algebra benchmark dataset alg514 and performs the second best on the AI2 corpus for arithmetic word problems. It also has superior performance on the challenging SVAMP dataset. Though it is a rule-based system, simple rule sets and relatively slight differences between rules for different templates indicate that it is highly probable to develop a system that can learn the patterns for the collection of all possible templates, and produce the correct equations for an example instance.