Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Conference Object Analysis, Design, Test, and Devops in Microservice-Based Software Architectures: Results From Pakistan(Springer international Publishing Ag, 2024) Unlu, Huseyin; Soylu, Gorkem Kilinc; Ahmad, Isra Shafique; Demirors, OnurIn today's software industry, Microservice-based Software Architecture (MSSA) has been a common practice and has been adopted by many companies. MSSA differs from traditional object-oriented architecture in several ways. The architecture moved away from being data-driven and evolved into a behavior-oriented structure. The usage of a single database is replaced by the structures in which each microservice is developed independently and has its own database. Therefore, adaptation demands software organizations to transform their culture. However, there is no de facto method for analyzing, designing, and testing systems for these architectures, similar to object-oriented analysis and design practices. This study aimed to understand how Pakistani software organizations undertake analysis, design, test, and DevOps processes in software projects adopting the MSSA paradigm. To achieve this goal, we surveyed 49 participants from various agile organizations in Pakistan, encompassing different roles and domains. The results reveal that Pakistani software organizations continue using familiar object-oriented analysis and design approaches. However, they have already started exploring event-oriented analysis and design methods for MSSA projects.Conference Object Citation - Scopus: 7From Requirements to Data Analytics Process: An Ontology-Based Approach(Springer International Publishing AG, 2019) Bandara, Madhushi; Behnaz, Ali; Rabhi, Fethi A.; Demirors, OnurComprehensively describing data analytics requirements is becoming an integral part of developing enterprise information systems. It is a challenging task for analysts to completely elicit all requirements shared by the organization's decision makers. With a multitude of data available from e-commerce sites, social media and data warehouses selecting the correct set of data and suitable techniques for an analysis itself is difficult and time-consuming. The reason is that analysts have to comprehend multiple dimensions such as existing analytics techniques, background knowledge in the domain of interest and the quality of available data. In this paper, we propose to use semantic models to represent different spheres of knowledge related to data analytics space and use them to assist in analytics requirements definition. By following this approach users can create a sound analytics requirements specification, linked with concepts from the operation domain, available data, analytics techniques and their implementations. Such requirements specifications can be used to drive the creation and management of analytics solutions, well aligned with organizational objectives. We demonstrate the capabilities of the proposed method by applying on a data analytics project for house price prediction.