WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7150

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Access type: Open accessAuthor: search.filters.author.Tuğlular, Tuğkan

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  • Article
    Link Prediction for Completing Graphical Software Models Using Neural Networks
    (IEEE, 2023) Leblebici, Onur; Tuğlular, Tuğkan; Belli, Fevzi
    Deficiencies 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. Author
  • Article
    Citation - WoS: 3
    Citation - Scopus: 4
    Application of the Law of Minimum and Dissimilarity Analysis To Regression Test Case Prioritization
    (IEEE, 2023) Ufuktepe, Ekincan; Tuğlular, Tuğkan
    Regression 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.
  • Article
    Citation - WoS: 2
    Citation - Scopus: 6
    Incremental Testing in Software Product Lines-An Event Based Approach
    (IEEE, 2023) Beyazıt, Mutlu; Tuğlular, Tuğkan; Öztürk Kaya, Dilek
    One 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: 3
    Citation - Scopus: 3
    A Domain-Specific Language for the Document-Based Model-Driven Engineering of Business Applications
    (IEEE, 2022) Leblebici, Onur; Kardaş, Geylani; Tuğlular, Tuğkan
    To 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.
  • Conference Object
    Citation - WoS: 3
    Citation - Scopus: 3
    Assessment of Human-Robot Interaction Between Householders and Robotic Vacuum Cleaners
    (IEEE, 2022) Yapıcı, Nur Beril; Tuğlular, Tuğkan; Başoğlu, Ahmet Nuri
    The study presented in this paper investigates the application of the Hybrid Model, which is the combination of the two strategies of the Built-to-Order Model and the Dynamic Eco-strategy Explorer Model, to robotic vacuum cleaners. The Hybrid Model aims to switch the market power from seller-driven perception to buyer-driven one by creating an individual perspective from the eye of users rather than traditional customer segmentation. The human-centered approach established theoretically has been tested with a determined procedure that includes prototyping, testing, and evaluating the proposed customization system for robotic vacuum cleaners to increase the interaction degree with purchasers. In this case, robotic vacuum cleaners have been chosen to implement and assess the hypothesis. Firstly, the successful prototyping of the Hybrid Model requires well customer analysis and habits determination to build well-constructed and coherent interaction between the purchaser and the robot. We utilized a content analysis of robotic vacuum cleaners and elaborative, conventional interviews with early adopters and early majority of this technology in Turkey to establish credible scenarios and product options during the phases of the Hybrid Model practice. The results of the interview were discussed, and the evaluations have been reported.
  • Conference Object
    Citation - WoS: 3
    Citation - Scopus: 2
    Heterogeneous Modeling and Testing of Software Product Lines
    (IEEE, 2021) Belli, Fevzi; Tuğlular, Tuğkan; Ufuktepe, Ekincan
    Software product line (SPL) engineering is a widely accepted approach to systematically realizing software reuse in an industrial environment. Feature models, a centerpiece of most SPL engineering techniques, are appropriate to model the variability and the structure of SPLs, but not their behavior. This paper uses the idea to link feature modeling to model-based behavior modeling and to determine the test direction (top-down or bottom-up) based on the variability binding. This heterogeneous modeling enables a holistic system testing for validating both desirable (positive) and undesirable (negative) properties of the SPL and variants. The proposed approach is validated by a non-trivial example and evaluated by comparison.
  • Conference Object
    Citation - Scopus: 1
    Mutation Analysis of Specification-Based Contracts in Software Testing [conference Object]
    (IEEE, 2021) Khalilov, Abbas; Tuğlular, Tuğkan; Belli, Fevzi
    This work focuses on checking the adequacy of the test cases generated using Decision-Table-augmented Event Sequence Graphs (ESG-DTs), which represents the specification of a system under test, by using mutation analysis. Test cases are represented in the Complete Event Sequence (CES) and Faulty CES (FCES) forms. We present a new set of mutation operators for mutation of contracts represented in Multi-Terminal Binary Decision Diagram (MTBDD) and introduce a new approach to mutation of the ESG-DT model by using the proposed mutation operators. The approach is evaluated on three cases. The results show the drawback of specific FCES test sequences and the relationship between the mutant detection by CES/FCES sequences and proposed mutation operators.
  • Conference Object
    Citation - WoS: 1
    Citation - Scopus: 1
    Application of Human-Robot Interaction Features To Design and Purchase Processes of Home Robots
    (Springer, 2021) Yapıcı, Nur Beril; Tuğlular, Tuğkan; Başoğlu, Ahmet Nuri
    Production of home robots, such as robotic vacuum cleaners, currently focuses more on the technology and its engineering than the needs of people and their interaction with robots. An observation supporting this view is that the home robots are not customizable. In other words, buyers cannot select the features and built their home robots to order. Stemmed from this observation, the paper proposes an approach that starts with a classification of features of home robots. This classification concerns robot interaction with humans and the environment, a home in our case. Following the classification, the proposed approach utilizes a new hybrid model based on a built-to-order model and dynamic eco-strategy explorer model, enabling designers to develop a production line and buyers to customize their home robots with the classified features. Finally, we applied the proposed approach to robotic vacuum cleaners. We developed a feature model for robotic vacuum cleaners, from which we formed a common uses scenario model.
  • Article
    Citation - WoS: 7
    Citation - Scopus: 8
    Tracking Code Bug Fix Ripple Effects Based on Change Patterns Using Markov Chain Models
    (Institute of Electrical and Electronics Engineers Inc., 2022) Ufuktepe, Ekincan; Tuğlular, Tuğkan; Palaniappan, Kanappan
    Change impact analysis evaluates the changes that are made in the software and finds the ripple effects, in other words, finds the affected software components. Code changes and bug fixes can have a high impact on code quality by introducing new vulnerabilities or increasing their severity. A recent high-visibility example of this is the code changes in the log4j web software CVE-2021-45105 to fix known vulnerabilities by removing and adding method called change types. This bug fix process exposed further code security concerns. In this article, we analyze the most common set of bug fix change patterns to have a better understanding of the distribution of software changes and their impact on code quality. To achieve this, we implemented a tool that compares two versions of the code and extracts the changes that have been made. Then, we investigated how these changes are related to change impact analysis. In our case study, we identified the change types for bug-inducing and bug fix changes using the Quixbugs dataset. Furthermore, we used 13 of the projects and 621 bugs from Defects4J to identify the common change types in bug fixes. Then, to find the change types that cause an impact on the software, we performed an impact analysis on a subset of projects and bugs of Defects4J. The results have shown that, on average, 90% of the bug fix change types are adding a new method declaration and changing the method body. Then, we investigated if these changes cause an impact or a ripple effect in the software by performing a Markov chain-based change impact analysis. The results show that the bug fix changes had only impact rates within a range of 0.4-5%. Furthermore, we performed a statistical correlation analysis to find if any of the bug fixes have a significant correlation with the impact of change. The results have shown that there is a negative correlation between caused impact with the change types adding new method declaration and changing method body. On the other hand, we found that there is a positive correlation between caused impact and changing the field type.
  • Conference Object
    Coverage Guided Multiple Base Choice Testing
    (IEEE, 2020) Tuğlular, Tuğkan; Leblebici, Onur
    A coverage guided input domain testing approach is presented with a feedback loop-controlled testing workflow and a tool is developed to support this workflow. Multiple base choices coverage criterion (MBCC) is chosen for systematic unit test generation in the proposed approach and branch coverage information is utilized as feedback to improve selection of bases, which results in improved branch coverage. The proposed workflow is supported with the tool designed and developed for coverage guided MBCC-based unit testing.