Muhammad Hamza

Context: Serverless computing, also referred to as Function‐as‐a‐Service (FaaS), has revolutionized application development by abstracting the management of underlying infrastructure. Accordingly, the software industry frequently adopts open‐source serverless frameworks such as OpenFaaS and Apache OpenWhisk for greater portability and flexibility. However, this adaptability often introduces a range of development and operational issues during application development. Objective: To this end, this study aims to develop an empirically grounded understanding of the issues encountered when developing applications with open‐source serverless frameworks, their underlying causes, and the relationships between them. Method: We conducted an empirical investigation of 3550 closed issue reports from 12 open‐source serverless frameworks. Results: Our analysis led to the development of a comprehensive taxonomy of 261 issue types and 158 underlying cause types that developers encounter when developing applications with these frameworks. The findings revealed that Development Workflow, Release Workflow and Containerization, and System Configuration and Interoperability are the leading categories of issues, whereas Improper Development and Execution Practices, Missing Components and Critical Features, and Mismanagement of Versioning and Variables are the most prevalent underlying causes of these issues. We further develop an issue–cause mapping that links observed issues to their underlying causes and identify which issues are most strongly shaped by the serverless execution model. Conclusion: Finally, we discuss implications for researchers and practitioners, propose actionable tooling directions derived from the issue–cause mapping, and outline future research directions based on the findings of this study.

The integration of circular economy principles and digital technologies into green hydrogen supply chain (GHSC) operations is essential for achieving sustainable, efficient, and resilient energy systems. However, limited research has investigated their combined role in improving circular GHSC performance. This study proposes a hybrid multi-criteria decision-making (MCDM) framework to evaluate the influence of digital technologies on circular GHSC operations. Initially, 23 potential factors were identified through a comprehensive literature review and expert consultation and grouped into four key parameters. The Fuzzy Delphi Technique (FDT) was employed to refine the factors, resulting in 17 significant factors. Subsequently, the Fuzzy Full Consistency Method (FUCOM) was applied to determine their relative importance. The robustness of the proposed framework was validated through sensitivity and comparative analyses. The results indicate that Technological Integration (P2) is the most influential parameter, followed by Economic and Ecosystem Integration (P4). Among the identified factors, Digital Infrastructure (H7), Cost Competitiveness (H15), Risk Management (H14), and Transparency and Security (H6) are the most critical for enhancing circular GHSC performance. Furthermore, three conceptual frameworks are proposed to support digital integration, circularity, and operational optimization, providing practical guidance for researchers, policymakers, and industry stakeholders to accelerate the transition toward sustainable green hydrogen economy.

The integration of circularity principles and digitalisation to enhance green hydrogen supply chain (GHSC) operations is essential for supporting and assessing sustainability. To date, no study has examined the integration of these concepts within the green hydrogen supply chain. Therefore, this study adopts a hybrid multi-criteria decision-making approach to assess the impact of digital technologies on circular GHSC operations. Initially, 23 factors were identified and categorised into four parameters. The Fuzzy Delphi Technique (FDT) refined these factors by eliminating six, after which the fuzzy Full Consistency Method (FUCOM) method determined factor weights. Finally, sensitivity and comparative analyses validated the robustness of the proposed approach. The findings show that Technological Integration (P2) ranked highest, followed by Economic and Ecosystem Integration (P4). Among the factors, Digital Infrastructure (H7) emerged as the most critical, followed by Cost Competitiveness (H15), Risk Management (H14), and Transparency and Security (H6). Sensitivity analysis confirmed the stability of Digital Infrastructure and Cost Competitiveness, while comparative analysis demonstrated consistent rankings across F-DEMATEL, F-BWM, and F-AHP methods. The study proposes three framework models. First, a circularity-based blockchain green hydrogen supply chain model is developed. Second, an integrated green hydrogen supply chain framework incorporating digital technologies is presented. Third, a digital technology–based circular GHSC potential factors framework is established to support operational optimization and enhance supply chain performance. Overall, the study highlights the role of digital technologies in the circular green hydrogen economy and provides practical insights for researchers, practitioners, and policymakers to enable a secure and efficient green hydrogen future.

Serverless computing has revolutionized cloud computing by abstracting the management of underlying infrastructure. This paradigm shift allows developers to concentrate on developing and optimizing application logic rather than managing the complexities of servers. Platforms such as AWS Lambda and OpenWhisk are gaining widespread adoption by enabling organizations to execute code in response to events. However, selecting the right serverless platform becomes challenging for organizations with the increasing number of serverless platforms and their diverse features. Moreover, decision-makers often lack specialized expertise in each platform, compelling them to continuously adapt to the rapidly evolving information and frequent updates. Therefore, this study presents a decision model for the serverless platforms selection problem that systematically captures knowledge and key features required for selecting serverless platforms. The model was evaluated through five real-world case studies at different software development companies. It suggests and prioritizes more than one serverless platform based on the participants' requirements. Participants reported that the model offered valuable insights, significantly simplifying the selection process while reducing the time and costs associated with decision-making. Additionally, the model enables organizations to efficiently evaluate and select serverless platforms that align with their technical requirements and strategic objectives. It also provides a foundation of reusable insights for researchers addressing future challenges in serverless computing.

Enterprises are increasingly adopting serverless computing to enhance scalability, reduce costs, and improve efficiency. However, this shift introduces new responsibilities and necessitates a distinct set of skills for practitioners. This study aims to identify and organize the industry requirements for serverless practitioners by conducting a qualitative analysis of 141 job advertisements from seven countries. We developed comprehensive taxonomies of roles, responsibilities, and skills, categorizing 19 responsibilities into four themes: software development, infrastructure and operations, professional development and leadership, and software business. Additionally, we identified 28 hard skills mapped into seven themes and 32 soft skills mapped into eight themes, with the six most demanded soft skills being communication proficiency, continuous learning and adaptability, collaborative teamwork, problem-solving and analytical skills, leadership excellence, and project management. Our findings contribute to understanding the organizational structures and training requirements for effective serverless computing adoption.