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Conference Object Yazilim Mühendisliǧi Alaninda Yayimlanan Tez ve Makalelerin Swebok'a Göre Degerlendirilmesi ve Yazilim Mühendisliǧi Eǧitiminin Iyilestirilmesi için Öneriler(CEUR-WS, 2016) Karakaya,M.; Karakaya, Kasım Murat; Yazici,A.; Yazıcı, Ali; Karakaya, Kasım Murat; Yazıcı, Ali; Computer Engineering; Software Engineering; Computer Engineering; Software Engineering[No abstract available]Conference Object A Decentralized Application for Secure Messaging in a Trustless Environment(Institute of Electrical and Electronics Engineers Inc., 2019) Abdulaziz,M.; Yazıcı, Ali; Culha,D.; Yazici,A.; Çulha, Davut; Yazıcı, Ali; Çulha, Davut; Software Engineering; Software EngineeringBlockchain technology has been seeing widespread interest as a means to ensure the integrity, confidentiality and availability of data in a trustless environment. They are designed to protect data from both internal and external cyberattacks by utilizing the aggregated power of the network to resist malicious efforts. In this article, we will create our own decentralized messaging application utilizing the Ethereum Whisper protocol. Our application will be able to send encrypted messages both securely and anonymously. We will utilize the Ethereum platform to deploy our blockchain network. This application would be resistant to most suppression tactics due to its distributed nature and adaptability of its communication protocol. © 2018 IEEE.Conference Object Citation - Scopus: 2Systematic 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; Software Engineering; Computer EngineeringThere 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.
