Browsing by Author "Karakaya,Z."

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Citation - Scopus: 2
Changing Our Educational Institutions: Transition From Traditional To E-Learning Programs
(2004) Yazici,A.; Karakaya,Z.; Dalgarno,B.; Altas,I.; Computer Engineering; Software Engineering; 06. School Of Engineering; 01. Atılım University
In this paper we examine basic elements of e-Learning, the features of the e-Learning model under implementation at Atilim University and the expected impact of the model on the organization of the institution. The paper also draws on examples at other institutions in discussing the issues that form the dynamics of organizational change within Universities in the 21st century. © 2004 IEEE.
Citation - Scopus: 25
A Comparison of Stream Processing Frameworks
(Institute of Electrical and Electronics Engineers Inc., 2017) Karakaya,Z.; Yazici,A.; Alayyoub,M.; Software Engineering; Computer Engineering; 06. School Of Engineering; 01. Atılım University
This study compares the performance of Big Data Stream Processing frameworks including Apache Spark, Flink, and Storm. Also, it measures the resource usage and performance scalability of the frameworks against a varying number of cluster sizes. It has been observed that, Flink outperforms both Spark and Storm under equal constraints. However, Spark can be optimized to provide the higher throughput than Flink with the cost of higher latency. © 2017 IEEE.
A Comparison of Stream Processing Frameworks
(Institute of Electrical and Electronics Engineers Inc., 2017) Karakaya,Z.; Yazici,A.; Alayyoub,M.; Software Engineering; Computer Engineering; 06. School Of Engineering; 01. Atılım University
This study compares the performance of Big Data Stream Processing frameworks including Apache Spark, Flink, and Storm. Also, it measures the resource usage and performance scalability of the frameworks against a varying number of cluster sizes. It has been observed that, Flink outperforms both Spark and Storm under equal constraints. However, Spark can be optimized to provide the higher throughput than Flink with the cost of higher latency. © 2017 IEEE.
Informatics Engineering Education in Turkey and Expectations of Software Industry;
(Institute of Electrical and Electronics Engineers Inc., 2018) Yazici,A.; Mishra,A.; Karakaya,Z.; Ustunkok,T.; Software Engineering; Computer Engineering; 06. School Of Engineering; 01. Atılım University
In this study, using the ÖSYM data, the number of intakes in Informatics Engineering programs in Turkey, accreditation data and the medium of instruction of the program are summarized for the years 2016 and 2017. In addition, the software sector's expectations from the informatics engineering graduates are reassessed based on the academic studies. The developed knowledge-skill gap set was used to evaluate the situation in Turkish informatics engineering programs. Sector expectations are discussed in the context of 2017-2019 Turkey Software Sector Strategy and Action Plan prepared by the Ministry of Science, Industry and Technology of Turkey and some proposals are made for the academia. As a result, it was observed that the expectations of the software industry were similar in all studies. Additionally, the expectations were changed in the direction of developing technologies and this change should be reflected in the informatics engineering programs. © 2018 IEEE.
Citation - Scopus: 11
Jmathnorm: a Database Normalization Tool Using Mathematica
(Springer Verlag, 2007) Yazici,A.; Karakaya,Z.; Software Engineering; Computer Engineering; 06. School Of Engineering; 01. Atılım University
This paper is about designing a complete interactive tool, named JMathNorm, for relational database (RDB) normalization using Mathematica. It is an extension of the prototype developed by the same authors [1] with the inclusion of Second Normal Form (2NF), and Boyce-Codd Normal Form (BCNF) in addition to the existing Third normal Form (3NF) module. The tool developed in this study is complete and can be used for real-time database design as well as an aid in teaching fundamental concepts of DB normalization to students with limited mathematical background. JMathNorm also supports interactive use of modules for experimenting the fundamental set operations such as closure, and full closure together with modules to obtain the minimal cover of the functional dependency set and testing an attribute for a candidate key. JMathNorm's GUI interface is written in Java and utilizes Mathematica's JLink facility to drive the Mathematica kernel. © Springer-Verlag Berlin Heidelberg 2007.
Jmathnorm: a Database Normalization Tool Using Mathematica
(Springer Verlag, 2007) Yazici,A.; Karakaya,Z.; Software Engineering; Computer Engineering; 06. School Of Engineering; 01. Atılım University
This paper is about designing a complete interactive tool, named JMathNorm, for relational database (RDB) normalization using Mathematica. It is an extension of the prototype developed by the same authors [1] with the inclusion of Second Normal Form (2NF), and Boyce-Codd Normal Form (BCNF) in addition to the existing Third normal Form (3NF) module. The tool developed in this study is complete and can be used for real-time database design as well as an aid in teaching fundamental concepts of DB normalization to students with limited mathematical background. JMathNorm also supports interactive use of modules for experimenting the fundamental set operations such as closure, and full closure together with modules to obtain the minimal cover of the functional dependency set and testing an attribute for a candidate key. JMathNorm's GUI interface is written in Java and utilizes Mathematica's JLink facility to drive the Mathematica kernel. © Springer-Verlag Berlin Heidelberg 2007.
Need for a Software Development Methodology for Research-Based Software Projects
(Institute of Electrical and Electronics Engineers Inc., 2018) Cereci,I.; Karakaya,Z.; Computer Engineering; 06. School Of Engineering; 01. Atılım University
Software development is mostly carried by a group of individuals. Software development methodologies are heavily utilized to organize these individuals and keep track of the entire software development process. Although previously proposed software development methodologies meet the needs of the industry and the firms, they are not usually suitable for research-based software projects that are carried by universities and individual researchers. In this paper, we aim to show the necessity of a new software development methodology for research-based problems carried by universities. The literature review will show the differences between industry and university software projects from certain aspects. These findings will be supported by the authors own research on the area. This qualitative research involves collecting data through interviews and applying Grounded Theory to better understand the development process. © 2018 IEEE.
Citation - Scopus: 4
Need for a Software Development Methodology for Research-Based Software Projects
(Institute of Electrical and Electronics Engineers Inc., 2018) Cereci,I.; Karakaya,Z.; Computer Engineering; 06. School Of Engineering; 01. Atılım University
Software development is mostly carried by a group of individuals. Software development methodologies are heavily utilized to organize these individuals and keep track of the entire software development process. Although previously proposed software development methodologies meet the needs of the industry and the firms, they are not usually suitable for research-based software projects that are carried by universities and individual researchers. In this paper, we aim to show the necessity of a new software development methodology for research-based problems carried by universities. The literature review will show the differences between industry and university software projects from certain aspects. These findings will be supported by the authors own research on the area. This qualitative research involves collecting data through interviews and applying Grounded Theory to better understand the development process. © 2018 IEEE.
Citation - Scopus: 7
Normalizing relational database schemas using mathematica
(Springer Verlag, 2006) Yazici,A.; Karakaya,Z.; Software Engineering; Computer Engineering; 06. School Of Engineering; 01. Atılım University
In this paper, basic relational database (DB) normalization algorithms are implemented efficiently as Mathematica modules. It was observed that, Mathematica provided a straightforward platform as opposed to previous ones, mainly Prolog based tools which required complex data structures such as linked list representations with pointers. A Java user interface called JMath-Norm was designed to execute the Mathematica modules in a systematic way. For this purpose, Mathematical Java link facility (JLink) is utilized to drive the Mathematica kernel. JMath-Norm provides an effective interactive tool in an educational setting for teaching DB normalization theory. © Springer-Verlag Berlin Heidelberg 2006.
Perceptions, Expectations and Implementations of Big Data in Public Sector : Kamuda Buÿük Veri: Alglar, Beklentiler Ve Uygulamalar
(Institute of Electrical and Electronics Engineers Inc., 2018) Dogdu,E.; Ozbayoglu,M.; Yazici,A.; Karakaya,Z.; Software Engineering; Computer Engineering; 06. School Of Engineering; 01. Atılım University
Big Data is one of the most commonly encountered buzzwords among IT professionals nowadays. Technological advancements in data acquisition, storage, telecommunications, embedded systems and sensor technologies resulted in huge inflows of streaming data coming from variety of sources, ranging from financial streaming data to social media tweets, or wearable health gadgets to drone flight logs. The processing and analysis of such data is a difficult task, but as appointed by many IT experts, it is crucial to have a Big Data Implementation plan in today's challenging industry standards. In this study, we performed a survey among IT professionals working in the public sector and tried to address some of their implementation issues and their perception of Big Data today and their expectations about how the industry will evolve. The results indicate that most of the public sector professionals are aware of the current Big Data requirements, embrace the Big Data challenge and are optimistic about the future. © 2018 IEEE.
Citation - Scopus: 4
Software engineering issues in big data application development
(Institute of Electrical and Electronics Engineers Inc., 2017) Karakaya,Z.; Computer Engineering; 06. School Of Engineering; 01. Atılım University
Big Data has become one of the most important concepts that is being studied in Computer/Software Engineering. The data produced in recent years have increased rapidly and exponentially, necessitating the solution of major problems such as the collection, processing and storage of huge volume of data. Big Data Frameworks are developed specifically to solve these problems that facilitates application developers by providing opportunities to collect, process, manage, monitor and analyze these data. A few examples of these frameworks are Hadoop, Spark, Storm, and Flink, which are developed by Software Engineers as open source projects. Although the challenges raised from coordination of IT resources such as huge amounts of computation power, storage area, memory, and network bandwidth in a distributed manner solved by these frameworks, there still remains many Software Engineering problems in application development phase, even if they based on these frameworks. High scalability, fault tolerance, flexibility, reliability and testability can be listed as the main issues need to be carefully considered in terms of Software Engineering. In this paper, we first clarify the terms Framework-Application, and then the overview information about Big Data and related frameworks are given before emphasizing the problems arising in terms of Software Engineering. Nevertheless, we tried to provide guidance to the people who would develop software for Big Data and tried to give the further research guidance. © 2017 IEEE.
Citation - Scopus: 2
Systematic Mapping for Big Data Stream Processing Frameworks
(Institute of Electrical and Electronics Engineers Inc., 2016) Alayyoub,M.; Yazıcı, Ali; Yazici,A.; Karakaya,Z.; Karakaya, Ziya; Yazıcı, Ali; Karakaya, Ziya; Software Engineering; Computer Engineering; Computer Engineering; Software Engineering; Computer Engineering; 06. School Of Engineering; 01. Atılım University
There has been lots of discussions about the choice of a stream processing framework (SPF) for Big Data. Each of the SPFs has different cutting edge technologies in their steps of processing the data in motion that gives them a better advantage over the others. Even though, the cutting edge technologies used in each stream processing framework might better them, it is still hard to say which framework bests the rest under different scenarios and conditions. In this study, we aim to show trends and differences about several SPFs for Big Data by using the Systematic Mapping (SM) approach. To achieve our objectives, we raise 6 research questions (RQs), in which 91 studies that conducted between 2010 and 2015 were evaluated. We present the trends by classifying the research on SPFs with respect to the proposed RQs which can help researchers to obtain an overview of the field. © 2016 IEEE.