Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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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. AuthorArticle Citation - WoS: 3Citation - Scopus: 6Model-Based Ideal Testing of Gui Programs-Approach and Case Studies(IEEE-Inst Electrical Electronics Engineers inc, 2021) Kilincceker, Onur; Silistre, Alper; Belli, Fevzi; Challenger, MoharramTraditionally, software testing is aimed at showing the presence of faults. This paper proposes a novel approach to testing graphical user interfaces (GUI) for showing both the presence and absence of faults in the sense of ideal testing. The approach uses a positive testing concept to show that the GUI under consideration (GUC) does what the user expects; to the contrary, the negative testing concept shows that the GUC does not do anything that the user does not expect, building a holistic view. The first step of the approach models the GUC by a finite state machine (FSM) that enables the model-based generation of test cases. This is always possible as the GUIs are considered as strictly sequential processes. The next step converts the FSM to an equivalent regular expression (RE) that will be analyzed first to construct test selection criteria for excluding redundant test cases and construct test coverage criteria for terminating the positive test process. Both criteria enable us to assess the adequacy and efficiency of the positive tests performed. The negative tests will be realized by systematically mutating the FSM to model faults, the absence of which are to be shown. Those mutant FSMs will be handled and assessed in the same way as in positive testing. Two case studies illustrate and validate the approach; the experiments' results will be analyzed to discuss the pros and cons of the techniques introduced.Book Part Citation - WoS: 4Citation - Scopus: 8Advances in Model-Based Testing of Graphical User Interfaces(Academic Press Inc., 2017) Belli, Fevzi; Beyazıt, Mutlu; Budnik, Christof J.; Tuğlular, TuğkanGraphical user interfaces (GUIs) enable comfortable interactions of the computer-based systems with their environment. Large systems usually require complex GUIs, which are commonly fault prone and thus are to be carefully designed, implemented, and tested. As a thorough testing is not feasible, techniques are favored to test relevant features of the system under test that will be specifically modeled. This chapter summarizes, reviews, and exemplifies conventional and novel techniques for model-based GUI testing.Article Citation - WoS: 7Citation - Scopus: 11Exploiting Model Morphology for Event-Based Testing(Institute of Electrical and Electronics Engineers Inc., 2015) Belli, Fevzi; Beyazıt, MutluModel-based testing employs models for testing. Model-based mutation testing (MBMT) additionally involves fault models, called mutants, by applying mutation operators to the original model. A problem encountered with MBMT is the elimination of equivalent mutants and multiple mutants modeling the same faults. Another problem is the need to compare a mutant to the original model for test generation. This paper proposes an event-based approach to MBMT that is not fixed on single events and a single model but rather operates on sequences of events of length k ≥ 1 and invokes a sequence of models that are derived from the original one by varying its morphology based on k. The approach employs formal grammars, related mutation operators, and algorithms to generate test cases, enabling the following: (1) the exclusion of equivalent mutants and multiple mutants; (2) the generation of a test case in linear time to kill a selected mutant without comparing it to the original model; (3) the analysis of morphologically different models enabling the systematic generation of mutants, thereby extending the set of fault models studied in related literature. Three case studies validate the approach and analyze its characteristics in comparison to random testing and another MBMT approach.