Agile Processes in Software Engineering and Extreme Programming, 9th International Conference, XP 2008, Limerick, Ireland, June 10-14, 2008. Proceedings
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
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 identifies Inadequate Architecture, Lack of Standardized Framework, Communication and Coordination, Poor Requirement Verification, and Minimum Documentation as the most significant challenges in Agile development.
Kamran Khan Tatari, Shahid Latif, Salim ur Rehman et al.· Information· 0 citations
Agile Software Development (ASD) has turned out to be the foundation of the present-day software development practices with the provision of iterative processes, such as Scrum or Kanban, that emulate focus on flexibility, cooperation, and continuous deployment. Nonetheless, it is always a cumulative issue to deliver on...
Neha Choudhary, Mahaveer Kumar Sain· International journal of com...· 0 citations
Generative artificial intelligence (GAI) is becoming more incorporated into software engineering functions like code creation, debugging, requirement analysis, testing, and sharing knowledge. This research looks at how GAI affects software teams in terms of productivity and quality of the output in Agile environments....
Abdalmenam Khalif Masaud Abuswah, Abdarrahman Khalif Ali Abousowa, Ziad Omar Salem Wareg· Al-Farooq Journal of Science...· 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.
Microsoft Research Blog· microsoft.comJul 30, 2026
Computer-use AI agents struggle with multi-step workflows like email and customer support. Echoverse trains agents in realistic environments rather than simply providing more training tasks, helping them improve as the tasks, tests, and environments evolve. The post Echoverse: Deep, evolving environments for computer-use agents appeared first on Microsoft Research.
Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar appeared first on Microsoft Research.
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