TL;DR
By identifying the barriers and strengths of agile deployment, the paper deepens understanding of this highly relevant but relatively under-researched phenomenon and contributes to the literature on agile deployment and software process improvement.
Context: The Agile methodology has been prevalent in the software industry for more than two decades, marking a shift from plan-driven to market-driven approaches and introducing various challenges. While the literature identifies numerous challenges in Agile development, little attention has been given to their ranking and prioritization, which are critical for effective project management and decision making. This study fills this gap by combining empirical evidence from the literature and practitioners. Objectives: This study aims to identify and hierarchically prioritize the most recent challenges faced by Agile practitioners during product development. To achieve this, a Systematic Literature Review (SLR) was conducted using 115 published studies between 2010 and 2025 followed by empirical data collection from 30 Agile experts through semi-structured interviews conducted with practitioners from Agile companies and an online survey. This study applies Cumulative Voting (100-Dollar Test) and Multi-Criteria Decision Making (MCDM) techniques to rank and prioritize these challenges. Results: The SLR identifies several recurring Agile challenges; however, limited research has focused on their ranking and prioritization. The present study reveals new challenges, such as user interface complexities, lack of pre-development and pre-operational cost information, and lack of cost scalability at the module and feature levels. The current study identifies Inadequate Architecture (22%), Lack of Standardized Framework (18%), Communication and Coordination (16%), Poor Requirement Verification (13%), and Minimum Documentation (8%) as the most significant challenges. Conclusions: This study provides valuable insight for Agile practitioners and organizations, enabling more informed project planning, resource allocation, and strategic decision making. By focusing on the most critical challenges, teams can enhance software quality, streamline processes, and improve overall productivity in Agile environments.
Agile methodology, which offers collaborative, adaptable, and iterative alternatives to conventional plan-driven procedures, has become a revolutionary paradigm in project management since it was codified in the Agile Manifesto. Agile was first used in software development, but it has now spread across many different industries, demonstrating its increasing applicability in dealing with complexity, ambiguity, and quick environmental change. Given this expansion, a comprehensive synthesis of the existing body of knowledge is necessary to understand the trajectory of Agile’s development, its practical applications, and its theoretical foundations. The literature demonstrates enduring issues, such as organizational resistance, misalignment with current governance structures, and the shortcomings of traditional performance measuring tools, despite widespread implementation. As a result, hybrid models that combine Agile and conventional methods have drawn more academic and real-world interest. This paper aims to present a literature review of Agile methodologies from 2001 to 2025, systematically examining their evolution, cross-sectoral diffusion, and key adaptations. It further identifies critical gaps in the literature and outlines future research directions, particularly in relation to sustainability, emerging market contexts, and the advancement of hybrid frameworks. Through this analysis, the study aims to provide a coherent and integrated understanding of Agile’s role in managing complexity and enhancing value delivery in contemporary organizational environments.
Modern software development requires flexible, efficient, and collaborative methodologies to cope with rapidly changing requirements and complex systems. This article explores three widely adopted programming and software development methodologies: Agile, Scrum, and DevOps. Agile focuses on iterative development, customer collaboration, and continuous improvement. Scrum, as an Agile framework, provides structured roles, events, and artifacts to enhance team productivity and project transparency. DevOps extends Agile principles by integrating development and operations, enabling continuous integration, continuous delivery, and faster deployment cycles. Through practical analysis and real-world examples, this study highlights how these methodologies complement each other in practice, improve software quality, reduce time-to-market, and enhance collaboration among stakeholders. The article concludes by discussing best practices and challenges in adopting Agile, Scrum, and DevOps in modern software engineering environments.
Measuring productivity in software development teams is a key process for evaluating their performance in agile environments, which are characterized by value creation, continuous adaptation, and incremental improvement. However, in the field of software engineering, although there are approaches focused on individual metrics, there remains a gap in the development of multifactorial models that integrate the various dimensions influencing team productivity. In response to this issue, this study proposes a multifactorial conceptual model designed to support the process of measuring productivity in agile teams. The development of the model was based on the measurement protocol proposed by Fenton and Bieman and included two main stages: design and validation. During the design phase, productivity factors were identified, and entities, properties, and empirical relationships were defined; these were represented using a Unified Modeling Language (UML) class diagram. The model was validated through expert judgment and an exploratory empirical application in higher education settings. The results demonstrate a high level of acceptance by experts, as well as the model’s viability for application in real-world scenarios, enabling the operationalization of the productivity construct in Scrum teams. In conclusion, the proposed model constitutes a significant advance in measuring productivity in agile teams by integrating multiple dimensions of performance, offering a structured, validated, and applicable framework that overcomes the limitations of traditional approaches and contributes to both the academic realm and professional practice.
This study assessed the effectiveness of Agile Scrum practices in enhancing team collaboration in construction projects in Port Harcourt, Nigeria. The research was motivated by persistent challenges in the construction industry such as poor communication, weak coordination, delays, and cost overruns, which are often linked to ineffective team collaboration. A survey research design was adopted, and data were collected from 171 construction professionals drawn from selected construction firms in Port Harcourt using a structured questionnaire. The study examined the extent of adoption of Scrum practices, the factors hindering their implementation, their effectiveness in improving team coordination, and strategies for enhancing their use in construction projects. Data were analyzed using frequency tables and percentages. Findings revealed that Agile Scrum practices such as sprint planning, daily stand-up meetings, sprint reviews, and iterative feedback are moderately adopted in construction projects and significantly improve team communication, coordination, and task alignment. It was concluded that Agile Scrum practices enhance team collaboration when properly implemented within a supportive organizational environment. The study recommends continuous training, provision of technological tools, flexible organizational structures, and strong management commitment to improve Scrum adoption and team collaboration in construction projects in Port Harcourt.
GPT-Lab
· gpt-lab.eu
Sep 17, 2026
AI is making software generation faster, but speed does not remove the need for expertise. As more work is delegated to AI, tacit knowledge may become one of the most important human advantages in software engineering. The post Beyond Prompt Engineering: The Role of Tacit Knowledge in Software Engineering appeared first on GPT-Lab.
We’re launching agentic video understanding across our latest Gemini models for improved accuracy and lower costs and token usage.
In his latest book, Professor Eugene Fitzgerald examines the forces that turn breakthroughs into value — and why innovation resists simple formulas.
A path, a fence, a knot. MindTopo sets a new benchmark for testing how AI understands topological relationships and highlights new opportunities to strengthen spatial reasoning and planning. The post MindTopo reveals VLMs’ spatial reasoning abilities appeared first on Microsoft Research.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
