Jun 2008· International Conference on Agile Software Development· pp. 232-233· 13 citations· 9 references
Computer Science
TL;DR
There is a vital need for devising a research agenda for identifying and dealing with architecture-centric challenges in agile software development to make it possible to guide the future research on integrating Architecture-centric methods in agile approaches and give advice to the software industry on dealing with Architecture related challenges.
It was identified that the industry tends to follow a hybrid Agile-DevOps practice with more emphasis on automation, continuous integration and collaboration to achieve quick and competitive software environments.
Raman Kumar· Journal of Global Research i...· 0 citations
A literature review of Agile methodologies from 2001 to 2025 is presented, systematically examining their evolution, cross-sectoral diffusion, and key adaptations, and identifies critical gaps in the literature and outlines future research directions.
Majid Al-Nabae, Norshahrizan Nordin, Abdulwadod S. A. Hassan et al.· Global Social Science and Hu...· 0 citations
It is possible that the waterfall method may be chaotic due to prescribed rather than effective structures, and structure and planning are essential to agile processes and take different forms from the waterfall model.
This study highlights how these methodologies complement each other in practice, improve software quality, reduce time-to-market, and enhance collaboration among stakeholders in modern software engineering environments.
Nkiwa Monkila Jonathan, Monkila Nkiwa Barthelemy, Padinganyi Tshiombela Faustin et al.· International journal of re...· 0 citations
The proposed multifactorial conceptual 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 acade...
Marcela Guerrero-Calvache, Giovanni Hernández, María Clara Gómez-Álvarez· Computers· 0 citations
This study investigates Agile practitioners’ perceptions of collaborating with GenAI in software development activities and findings advance the understanding of human-AI collaboration in Agile settings and can guide both future research and the practical adoption of GenAI in Agile environments.
Daniel Planötscher, Xiaofeng Wang, Mahum Adil et al.· 0 citations
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
Computer scientist, entrepreneur, and philanthropist will collaborate with the MIT Schwarzman College of Computing to advance AI and scientific discovery.