Computer Engineering / Bilgisayar Mühendisliği

Permanent URI for this collectionhttps://hdl.handle.net/11147/10

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Start date: 2001Scopus Q: search.filters.scopusQuartile.Q3

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Now showing 1 - 10 of 55
  • Conference Object
    Citation - Scopus: 1
    Computing a Parametric Reveals Relation for Bounded Equal-Conflict Petri Nets
    (Springer, 2024) Adobbati, Federica; Bernardinello, Luca; Kılınç Soylu, Görkem; Pomello, Lucia
    In a distributed system, in which an action can be either “hidden” or “observable”, an unwanted information flow might arise when occurrences of observable actions give information about occurrences of hidden actions. A collection of relations, i.e. reveals and its variants, is used to model such information flow among transitions of a Petri net. This paper recalls the reveals relations defined in [3], and proposes an algorithm to compute them on bounded equal-conflict PT systems, using a smaller structure than the one defined in [3]. © 2024, The Author(s), under exclusive license to Springer-Verlag GmbH, DE, part of Springer Nature.
  • Article
    Spectral Test Generation for Boolean Expressions
    (World Scientific Publishing, 2023) Ayav, Tolga
    This paper presents a novel method for testing Boolean expressions. It is based on spectral, aka Fourier analysis of Boolean functions which is exploited to generate test inputs. The approach has three important contributions: (i) It generates a relatively small test suite with a high capability of fault detection, (ii) The test suite is prioritized such that expected fault detection time is shorter, (iii) It is entirely mathematical relying on a simple and straightforward formula. The proposed method is formulated and evaluations are performed on both synthetic and real expressions. It is also compared with two common test generation criteria, MC/DC and Minimal MUMCUT. Evaluations show that the test suite generated by the spectral approach is relatively small while expressing the capability of a better and quicker fault detection. The approach presented in this paper provides a useful insight into how spectral/Fourier analysis of Boolean functions can be exploited in software testing.
  • Article
    Citation - WoS: 2
    Citation - Scopus: 3
    Mutation-Based Minimal Test Suite Generation for Boolean Expressions
    (World Scientific Publishing, 2023) Ayav, Tolga; Belli, Fevzi
    Boolean expressions are highly involved in control flows of programs and software specifications. Coverage criteria for Boolean expressions aim at producing minimal test suites to detect software faults. There exist various testing criteria, efficiency of which is usually evaluated through mutation analysis. This paper proposes an integer programming-based minimal test suite generation technique relying on mutation analysis. The proposed technique also takes into account the cost of fault detection. The technique is optimal such that the resulting test suite guarantees to detect all the mutants under given fault assumptions, while maximizing the average percentage of fault detection of a test suite. Therefore, the approach presented can also be considered as a reference method to check the efficiency of any common technique. The method is evaluated using four well-known real benchmark sets of Boolean expressions and is also exemplary compared with MCDC criterion. The results show that the test suites generated by the proposed method provide better fault coverage values and faster fault detection.
  • Article
    Studying the Co-Evolution of Source Code and Acceptance Tests
    (World Scientific Publishing, 2023) Yalçın, Ali Görkem; Tuğlular, Tuğkan
    Testing is a vital part of achieving good-quality software. Deploying untested code can cause system crashes and unexpected behavior. To reduce these problems, testing should evolve with coding. In addition, test suites should not remain static throughout the software versions. Since whenever software gets updated, new functionalities are added, or existing functionalities are changed, test suites should be updated along with the software. Software repositories contain valuable information about the software systems. Access to older versions and differentiating adjacent versions' source code and acceptance test changes can provide information about the evolution process of the software. This research proposes a method and implementation to analyze 21 open-source real-world projects hosted on GitHub regarding the co-evolution of both software and its acceptance test suites. Related projects are retrieved from repositories, their versions are analyzed, graphs are created, and analysis related to the co-evolution process is performed. Observations show that the source code is getting updated more frequently than the acceptance tests. They indicate a pattern that source code and acceptance tests do not evolve together. Moreover, the analysis showed that a few acceptance tests test most of the functionalities that take a significant line of code.
  • Conference Object
    Citation - WoS: 3
    Citation - Scopus: 4
    The Relation Between Bug Fix Change Patterns and Change Impact Analysis
    (Institute of Electrical and Electronics Engineers, 2021) Ufuktepe,E.; Tuglular,T.; Palaniappan,K.
    Change impact analysis analyzes the changes that are made in the software and finds the ripple effects, in other words, finds the affected software components. In this study, we analyze the bug fix change patterns to have a better understanding of what types of changes are common in fixing bugs. To achieve this, we implemented a tool that compares two versions of codes and detects the changes that are made. Then, we investigated how these changes are related to change impact analysis. In our case study, we used 13 of the projects and 621 bugs from Defects4J to identify the common change types in bug fixed. Then, to find the change types related to cause an impact in 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 on 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. © 2021 IEEE.
  • 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
    Performance and Accuracy Predictions of Approximation Methods for Shortest-Path Algorithms on Gpus
    (Elsevier, 2022) Aktılav, Busenur; Öz, Işıl
    Approximate computing techniques, where less-than-perfect solutions are acceptable, present performance-accuracy trade-offs by performing inexact computations. Moreover, heterogeneous architectures, a combination of miscellaneous compute units, offer high performance as well as energy efficiency. Graph algorithms utilize the parallel computation units of heterogeneous GPU architectures as well as performance improvements offered by approximation methods. Since different approximations yield different speedup and accuracy loss for the target execution, it becomes impractical to test all methods with various parameters. In this work, we perform approximate computations for the three shortest-path graph algorithms and propose a machine learning framework to predict the impact of the approximations on program performance and output accuracy. We evaluate random predictions for both synthetic and real road-network graphs, and predictions of the large graph cases from small graph instances. We achieve less than 5% prediction error rates for speedup and inaccuracy values.
  • Article
    Citation - WoS: 1
    Citation - Scopus: 1
    Author Reputation Measurement on Question and Answer Sites by the Classification of Author-Generated Content
    (World Scientific Publishing, 2021) Sezerer, Erhan; Tenekeci, Samet; Acar, Ali; Baloğlu, Bora; Tekir, Selma
    In the field of software engineering, practitioners' share in the constructed knowledge cannot be underestimated and is mostly in the form of grey literature (GL). GL is a valuable resource though it is subjective and lacks an objective quality assurance methodology. In this paper, a quality assessment scheme is proposed for question and answer (Q&A) sites. In particular, we target stack overflow (SO) and stack exchange (SE) sites. We model the problem of author reputation measurement as a classification task on the author-provided answers. The authors' mean, median, and total answer scores are used as inputs for class labeling. State-of-the-art language models (BERT and DistilBERT) with a softmax layer on top are utilized as classifiers and compared to SVM and random baselines. Our best model achieves 63.8% accuracy in binary classification in SO design patterns tag and 71.6% accuracy in SE software engineering category. Superior performance in SE software engineering can be explained by its larger dataset size. In addition to quantitative evaluation, we provide qualitative evidence, which supports that the system's predicted reputation labels match the quality of provided answers.
  • Article
    Citation - WoS: 6
    Citation - Scopus: 7
    Human-Robot Interfaces of the Neuroboscope: a Minimally Invasive Endoscopic Pituitary Tumor Surgery Robotic Assistance System
    (ASME, 2021) Dede, Mehmet İsmet Can; Kiper, Gökhan; Ayav, Tolga; Özdemirel, Barbaros; Tatlıcıoğlu, Enver; Hanalioğlu, Şahin; Işıkay, İlkay
    Endoscopic endonasal surgery is a commonly practiced minimally invasive neurosurgical operation for the treatment of a wide range of skull base pathologies including pituitary tumors. A common shortcoming of this surgery is the necessity of a third hand when the endoscope has to be handled to allow active use of both hands of the main surgeon. The robot surgery assistant NeuRoboScope system has been developed to take over the endoscope from the main surgeon's hand while providing the surgeon with the necessary means of controlling the location and direction of the endoscope. One of the main novelties of the NeuRoboScope system is its human-robot interface designs which regulate and facilitate the interaction between the surgeon and the robot assistant. The human-robot interaction design of the NeuRoboScope system is investigated in two domains: direct physical interaction (DPI) and master-slave teleoperation (MST). The user study indicating the learning curve and ease of use of the MST is given and this paper is concluded via providing the reader with an outlook of possible new human-robot interfaces for the robot assisted surgery systems.
  • Article
    Citation - WoS: 3
    Citation - Scopus: 3
    Catadioptric Hyperspectral Imaging, an Unmixing Approach
    (Institution of Engineering and Technology, 2020) Özışık Başkurt, Didem; Baştanlar, Yalın; Yardımcı Çetin, Yasemin
    Hyperspectral imaging systems provide dense spectral information on the scene under investigation by collecting data from a high number of contiguous bands of the electromagnetic spectrum. The low spatial resolutions of these sensors frequently give rise to the mixing problem in remote sensing applications. Several unmixing approaches are developed in order to handle the challenging mixing problem on perspective images. On the other hand, omnidirectional imaging systems provide a 360-degree field of view in a single image at the expense of lower spatial resolution. In this study, we propose a novel imaging system which integrates hyperspectral cameras with mirrors so on to yield catadioptric omnidirectional imaging systems to benefit from the advantages of both modes. Catadioptric images, incorporating a camera with a reflecting device, introduce radial warping depending on the structure of the mirror used in the system. This warping causes a non-uniformity in the spatial resolution which further complicates the unmixing problem. In this context, a novel spatial-contextual unmixing algorithm specifically for the large field of view of the hyperspectral imaging system is developed. The proposed algorithm is evaluated on various real-world and simulated cases. The experimental results show that the proposed approach outperforms compared methods.