Computer Engineering / Bilgisayar Mühendisliği

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

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  • Conference Object
    Cosmic Light Vs Cosmic Classic Manual: Case Studies in Functional Size Measurement
    (CEUR Workshop Proceedings, 2020) Hacaloğlu, Tuna; Ünlü, Hüseyin; Demirörs, Onur; Abran, Alain
    Functional size has been used in software engineering for more than 40 years. When measured early in the software development life cycle, it can serve as direct input for effort estimation. The COSMIC Functional Size Measurement (FSM) method developed by the Common Software Measurement Consortium (COSMIC) is the latest ISO-compliant functional sizing method. A streamlined manual titled ''Software Development Velocity with COSMIC Function Points'' summarizes the measurement process and shortens the learning time. The aim of this study is to compare the classic COSMIC FSM manual and this new “light” manual in terms of accuracy of the resulting FSM applied to case studies. The findings show that use of the light manual results in accurate measurement. In addition, there were no significant time differences between the two. With respect to the variations in COSMIC Function Points (CFP) values in the two case studies, they three causes were identified: the Object of Interest (OOI) concept and corresponding data groups, details regarding Functional Process Independence, and Error/Confirmation messages related to the scope of the information included in the manuals. Copyright © 2020 for this paper by its authors.
  • Conference Object
    Challenges and Working Solutions in Agile Adaptation: Experiences From the Industry
    (CEUR Workshop Proceedings, 2020) Özcan Top, Özden; Demirörs, Onur; McCaffery, Fergal
    Challenges in agile adaptation is inevitable in software development projects and have to be dealt with by software practitioners. The pathway to excellence in agility requires experience of challenges, failure of process scenarios; and the discovery of working solutions by software development teams. The major purpose of this study is to highlight both the challenges organizations faced when implementing agile techniques and the solutions adopted that proved successful. In order to specify these challenges and working solutions, we performed a multiple case study by using the Software Agility Assessment Reference Model (AgilityMod). In this paper, we describe two cases that achieve the highest levels of agility among eight cases and describe their experiences in achieving a good adaptation through the challenges that they faced and the solutions that were found for these challenges. Additionally, we provide two challenges that have not been resolved yet and are subject to further discussions. Copyright © 2020 for this paper by its authors.
  • Conference Object
    Sonlu Durum Makinelerinin Fourier Analizi Tabanlı Sınanması
    (CEUR Workshop Proceedings, 2018) Takan, Savaş; Ayav, Tolga
    Sonlu durum makinesi (FSM), devre ve yazılım testlerinde yaygın kullanıma sahip bir modelleme tekniğidir. FSM'lerin testi için literatürde çeşitli yöntemler bulunmakla birlikte, modellerin büyümesi sonucu test kümesinin büyüklüğü, hata yakalama oranı ve test üretim süresi gibi konularda yüksek başarıma sahip alternatif test yöntemlerine ihtiyaç bulunmaktadır. Bu çalışma ikili fonksiyonların Fourier analizine dayanan yeni bir test oluşturma yöntemi önermektedir. İlk sonuçlar, fonksiyonun frekans bileşenlerinden yararlanarak oluşturulan test takımının daha yüksek bir performansa sahip olduğunu göstermektedir. Önerilen yöntem, karakteristiği, maliyeti ve hata yakalama oranı üzerinden literatürden seçilen iki yöntemle karşılaştırılmıştır.
  • Conference Object
    Citation - Scopus: 2
    A Comparative Study of Modularity-Based Community Detection Methods for Online Social Networks
    (CEUR Workshop Proceedings, 2018) Karataş, Arzum; Şahin, Serap
    Digital data represent our daily activities and tendencies. One of its main source is Online Social Networks (OSN) such as Facebook, YouTube etc. OSN are generating continuously high volume of data and define a dynamic virtual environment. This environment is mostly represented by graphs. Analysis of OSN data (i.e.,extracting any kind of relations and tendencies) defines valuable information for economic, socio-cultural and politic decisions. Community detection is important to analyze and understand underlying structure and tendencies of OSNs. When this information can be analysed successfully, software engineering tools and decision support systems can produce more successful results for end users. In this study, we present a survey of selected outstanding modularity-based static community detection algorithms and do comparative analysis among them in terms of modularity, running time and accuracy. We use different real-world OSN test beds selected from SNAP dataset collection such as Facebook Ego network, Facebook Pages network (Facebook gemsec), LiveJournal, Orkut and YouTube networks.
  • Conference Object
    Citation - Scopus: 6
    Gender Prediction From Tweets With Convolutional Neural Networks: Notebook for Pan at Clef 2018
    (CEUR Workshop Proceedings, 2018) Sezerer, Erhan; Polatbilek, Ozan; Sevgili, Özge; Tekir, Selma
    This paper presents a system1 developed for the author profiling task of PAN at CLEF 2018. The system utilizes style-based features to predict the gender information from the given tweets of each user. These features are automatically extracted by Convolutional Neural Networks (CNN). The system mainly depends on the idea that the informativeness of each tweet is not the same in terms of the gender of a user. Thus, the attention mechanism is included to the CNN outputs in order to discriminate the tweets carrying more information. Our architecture was able to obtain competitive results on three languages provided by the PAN 2018 author profiling challenge with an average accuracy of 75.1% on local runs and 70.23% on the submission run.
  • Conference Object
    Citation - Scopus: 4
    Survey: Running and Comparing Stream Clustering Algorithms
    (CEUR Workshop Proceedings, 2018) Ahmed, Rowanda D.; Dalkılıç, Gökhan; Erten, Murat
    Recently, clustering data streams have become an incredibly important research area for knowledge discovery as applications produce more and more unstoppable streaming data. In this paper we introduce clustering, streams and data streaming clustering algorithms, as well as discussions of the most important stream clustering algorithms, considering their structure. As an additional contribution of our work and differently from review and survey papers in stream clustering, we offer the practical part of the most known stream clustering algorithms, namely: (i) CluStream; (ii) DenStream; (iii) D-Stream; and (iv) ClusTree, showing their experimental results along with some performance metrics computation of for each, depending on MOA framework.
  • Conference Object
    Özellik Yönelimli Ürün Konfigürasyonlarının Olay Sıra Çizgeleri ile Doğrulanması
    (CEUR Workshop Proceedings, 2018) Tuğlular, Tuğkan; Belli, Fevzi; Öztürk, Dilek
    This study attempts to suggest an approach to systematically test potentially very large number of product variants in feature-oriented software. Feature-oriented software forms a popular concept to efficiently realize software reuse. Developing feature-oriented software is well accepted to accomplish software reuse in an efficient way. Developing product variants by exploiting software reuse requires verification of these variants by exploiting test reuse. However, the reuse of tests in the verification of variants is an underworked topic. In this study, we propose a model-based approach to top-down testing of feature-oriented software that does not have dependency or conflict between features. In the case study, event sequence graphs (ESGs) are used to model the software under consideration and then to generate test cases for positive and negative testing. The generated tests are executed via SahiPro web test automation tool, of which scripts are also automatically generated from ESGs.
  • Conference Object
    Citation - Scopus: 7
    Challenges of Using Software Size in Agile Software Development: a Systematic Literature Review
    (CEUR Workshop Proceedings, 2018) Hacaloğlu, Tuna; Demirörs, Onur
    Software size is a fundamental measure for software management. Size is used for a variety of purposes, such as benchmarking, normalization, and portfolio measurement, and it is frequently considered as the sole input of estimation. Estimations can be produced for various reasons; e.g., to predict effort, cost and duration of software development projects. There are different types of software size measures. Particularly in projects where agile methodologies are adopted, measurement becomes a significant challenge as it is perceived as a non-value-added task and records of tasks such as requirements identification are not always consistent. The difficulties of applying traditional size measurement techniques in agile contexts, however, do not diminish the need, and new methods and techniques are introduced to improve the manageability of the agile projects. In this paper, we discuss estimation and measurement approaches in relation with ―software size in agile contexts. Based on this review, we present the perceptions of software size and related challenges, such as misinterpretation of size, difficulties in implementation, and acceptability of the measurement processes. We anticipate that providing a baseline for the state of software size measures in agile contexts and presenting related challenges, particularly in terms of its acceptability by practitioners can shed light on the development of new techniques.
  • Conference Object
    Sosyal Çizgeler için Arama Motoru Geliştirilmesi
    (CEUR Workshop Proceedings, 2016) Yafay, Erman; Tekir, Selma
    Sosyal ağlara giderek artan ilgi, beraberinde büyük ölçeklerde bağlantılı veri açığa çıkarmıştır. Bu büyük veriler üzerinde arama yapabilmek için özelleştirilmiş sistemlere gereksinim duyulmaktadır. Bu gereksinimi karşılamak üzere Facebook, 2013 yılında kendi arama motoru olan Unicorn’u[1] hizmete sunmuştur. Bu çalışmada, Unicorn’un asgari fakat temel özellikleri tasarlanıp gerçekleştirilmiştir. Yaklaşımımızda sosyal ağ bir çizge olarak modellenmiştir ve çizgedeki düğümler ve kenarlar farklı türlere sahip olabilecek şekilde genel olarak tanımlanmıştır. Düğümler, kişi veya sayfa gibi varlıkları ifade ederken; kenarlar, düğümler arasındaki arkadaşlık veya beğenme ilişkisini ortaya koyar. Verimlilik sorununu çözebilmek için tamamen bellek üzerinde çalışan bir indisleme sistemi geliştirilmiştir. Bu sistem geniş ölçekte veri işlenmesini sağlamak üzere geliştirilen dağıtık motor Spark[2] üzerinde gerçekleştirilmiştir. Son olarak, sosyal ağ yapısına uygun işleçler (ve, veya, zayıf- ve, güçlü-veya, uygula) tasarlanmıştır. Bu işleçler sayesinde kolayca kişilerin ortak arkadaşları veya arkadaşlarının arkadaşları gibi sorgular ifade edilip çalıştırılabilmektedir. Çalışmanın son bölümünde bu tip bir sistemin gerçekleştirilmesinde dikkate alınması gereken nitelikler, bu niteliklere ilişkin ödünleşimler ve karar mekanizmaları ele alınıp değerlendirilmiştir.
  • Conference Object
    Citation - Scopus: 1
    Approximate Reasoning With Fuzzy-Syllogistic Systems
    (CEUR Workshop Proceedings, 2015) Kumova, Bora İsmail
    The well known Aristotelian syllogistic system consists of 256 moods. We have found earlier that 136 moods are distinct in terms of equal truth ratios that range in τ=[0,1]. The truth ratio of a particular mood is calculated by relating the number of true and false syllogistic cases the mood matches. A mood with truth ratio is a fuzzy-syllogistic mood. The introduction of (n-1) fuzzy existential quantifiers extends the system to fuzzy-syllogistic systems nS, 1<n, of which every fuzzy-syllogistic mood can be interpreted as a vague inference with a generic truth ratio that is determined by its syllogistic structure. We experimentally introduce the logic of a fuzzy-syllogistic ontology reasoner that is based on the fuzzy-syllogistic systems nS. We further introduce a new concept, the relative truth ratio rτ=[0,1] that is calculated based on the cardinalities of the syllogistic cases.