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Review Citation - WoS: 247Citation - Scopus: 446Transformative Effects of Iot, Blockchain and Artificial Intelligence on Cloud Computing: Evolution, Vision, Trends and Open Challenges(Elsevier, 2019) Gill, Sukhpal Singh; Tuli, Shreshth; Xu, Minxian; Singh, Inderpreet; Singh, Karan Vijay; Lindsay, Dominic; Garraghan, PeterCloud computing plays a critical role in modern society and enables a range of applications from infrastructure to social media. Such system must cope with varying load and evolving usage reflecting societies' interaction and dependency on automated computing systems whilst satisfying Quality of Service (QoS) guarantees. Enabling these systems are a cohort of conceptual technologies, synthesized to meet demand of evolving computing applications. In order to understand current and future challenges of such system, there is a need to identify key technologies enabling future applications. In this study, we aim to explore how three emerging paradigms (Blockchain, IoT and Artificial Intelligence) will influence future cloud computing systems. Further, we identify several technologies driving these paradigms and invite international experts to discuss the current status and future directions of cloud computing. Finally, we proposed a conceptual model for cloud futurology to explore the influence of emerging paradigms and technologies on evolution of cloud computing. (C) 2019 Elsevier B.V. All rights reserved.Review Citation - WoS: 67Citation - Scopus: 81Software Test Maturity Assessment and Test Process Improvement: a Multivocal Literature Review(Elsevier, 2017) Garousi, Vahid; Felderer, Michael; Hacaloglu, TunaContext: Software testing practices and processes in many companies are far from being mature and are usually conducted in ad-hoc fashions. Such immature practices lead to various negative outcomes, e.g., ineffectiveness of testing practices in detecting all the defects, and cost and schedule overruns of testing activities. To conduct test maturity assessment (TMA) and test process improvement (TPI) in a systematic manner, various TMA/TPI models and approaches have been proposed. Objective: It is important to identify the state-of-the-art and the-practice in this area to consolidate the list of all various test maturity models proposed by practitioners and researchers, the drivers of TMA/TPI, the associated challenges and the benefits and results of TMA/TPI. Our article aims to benefit the readers (both practitioners and researchers) by providing the most comprehensive survey of the area, to this date, in assessing and improving the maturity of test processes. Method: To achieve the above objective, we have performed a Multivocal Literature Review (MLR) study to find out what we know about TMA/TPI. A MLR is a form of a Systematic Literature Review (SLR) which includes the grey literature (e.g., blog posts and white papers) in addition to the published (formal) literature (e.g., journal and conference papers). We searched the academic literature using the Google Scholar and the grey literature using the regular Google search engine. Results: Our MLR and its results are based on 181 sources, 51 (29%) of which were grey literature and 130 (71%) were formally published sources. By summarizing what we know about TMA/TPI, our review identified 58 different test maturity models and a large number of sources with varying degrees of empirical evidence on this topic. We also conducted qualitative analysis (coding) to synthesize the drivers, challenges and benefits of TMA/TPI from the primary sources. Conclusion: We show that current maturity models and techniques in TMA/TPI provides reasonable advice for industry and the research community. We suggest directions for follow-up work, e.g., using the findings of this MLR in industry-academia collaborative projects and empirical evaluation of models and techniques in the area of TMA/TPI as reported in this article. (C) 2017 Elsevier B.V. All rights reserved.Review Citation - WoS: 4Citation - Scopus: 4Smart Hydrogels in Lab-On (loc) Applications(Elsevier, 2024) Tevlek, Atakan; Cretin, Esin Akbay; Çetin, Esin AkbayLaboratory on-chip (LOC) technology facilitates numerous developments across diverse disciplines, such as medicine, tissue engineering, materials science, biomedical engineering, and biotechnology. Moreover, the potential applications appear boundless when LOC is integrated with intelligent hydrogels. In the literature, however, there are few accounts of the vast array of developments and applications that this combination has spawned. These new systems, which integrate smart hydrogels and LOC and thus significantly advance cuttingedge technology, have been thoroughly examined in this review. The functions of smart hydrogels in LOC applications were described and subsequently the developed intelligent hydrogels were classified as multiresponsive, thermo-responsive, pH-responsive, and stimuli-responsive (light, magnetic, and electric). Following this, details regarding tunable properties for LOC functions were provided, followed by a discussion of the fabrication processes and integration of these intelligent hydrogels into LOC systems, including their benefits and drawbacks. Following that, current literature examples of LOC systems utilizing these intelligent hydrogels for biosensing, 3D culture, tissue engineering, controlled release, personalized medicine, drug delivery, analyte enrichment, and organ-on-a-chip applications were presented. Following the presentation of state-of-the-art information regarding smart hydrogel characterization techniques, present challenges and prospective prospects were discussed.Review Citation - WoS: 152Citation - Scopus: 194Challenges and Best Practices in Industry-Academia Collaborations in Software Engineering: a Systematic Literature Review(Elsevier, 2016) Garousi, Vahid; Petersen, Kai; Ozkan, BarisContext: The global software industry and the software engineering (SE) academia are two large communities. However, unfortunately, the level of joint industry-academia collaborations in SE is still relatively very low, compared to the amount of activity in each of the two communities. It seems that the two 'camps' show only limited interest/motivation to collaborate with one other. Many researchers and practitioners have written about the challenges, success patterns (what to do, i.e., how to collaborate) and anti-patterns (what not do do) for industry-academia collaborations. Objective: To identify (a) the challenges to avoid risks to the collaboration by being aware of the challenges, (b) the best practices to provide an inventory of practices (patterns) allowing for an informed choice of practices to use when planning and conducting collaborative projects. Method: A systematic review has been conducted. Synthesis has been done using grounded-theory based coding procedures. Results: Through thematic analysis we identified 10 challenge themes and 17 best practice themes. A key outcome was the inventory of best practices, the most common ones recommended in different contexts were to hold regular workshops and seminars with industry, assure continuous learning from industry and academic sides, ensure management engagement, the need for a champion, basing research on real world problems, showing explicit benefits to the industry partner, be agile during the collaboration, and the co-location of the researcher on the industry side. Conclusion: Given the importance of industry-academia collaboration to conduct research of high practical relevance we provide a synthesis of challenges and best practices, which can be used by researchers and practitioners to make informed decisions on how to structure their collaborations. (C) 2016 Elsevier B.V. All rights reserved.Review Citation - WoS: 86Citation - Scopus: 93A Review on the Development of the Electrochemical Hydrogen Compressors(Elsevier, 2021) Durmus, Gizem Nur Bulanik; Colpan, C. Ozgur; Devrim, YilserHydrogen should be stored at high pressure and high purity, especially when utilized in fuel cells. Conventionally, mechanical compressors are used for pressurization of hydrogen; however, this technology has disadvantages such as noise and vibration during operation due to their moving parts. Electrochemical hydrogen compressors (ECHC) have emerged as an alternative solution, as these devices can purify and compress hydrogen electrochemically in a single device. This review provides a comprehensive overview of key components and management strategies of the ECHC systems. This review will also provide an overview of different hydrogen compression technologies and provides a comprehensive overview of the latest developments and current issues and future of ECHCs. For this purpose, firstly, the advantages and disadvantages of ECHC compared to mechanical compressors are explained. Then, recent studies on hydrogen purification methods are given. The working principle of ECHC, material development studies and mathematical modeling of ECHCs are also discussed.Review Citation - WoS: 73Citation - Scopus: 112Devops and Software Quality: a Systematic Mapping(Elsevier, 2020) Mishra, Alok; Otaiwi, ZiadoonQuality pressure is one of the factors affecting processes for software development in its various stages. DevOps is one of the proposed solutions to such pressure. The primary focus of DevOps is to increase the deployment speed, frequency and quality. DevOps is a mixture of different developments and operations to its multitudinous ramifications in software development industries, DevOps have attracted the interest of many researchers. There are considerable literature surveys on this critical innovation in software development, yet, little attention has been given to DevOps impact on software quality. This research is aimed at analyzing the implications of DevOps features on software quality. DevOps can also be referred to a change in organization cultures aimed at removal of gaps between the development and operations of an organization. The adoption of DevOps in an organization provides many benefits including quality but also brings challenges to an organization. This study presents systematic mapping of the impact of DevOps on software quality. The results of this study provide a better understanding of DevOps on software quality for both professionals and researchers working in this area. The study shows research was mainly focused in automation, culture, continuous delivery, fast feedback of DevOps. There is need of further research in many areas of DevOps (for instance: measurement, development of metrics of different stages to assess its performance, culture, practices toward ensuring quality assurance, and quality factors such as usability, efficiency, software maintainability and portability). (C) 2020 The Author(s). Published by Elsevier Inc.
