mlsanityData to 7 Oct 2026

Agile Software Development Methods: Review and Analysis

arXiv 1709.08439 ↗First posted 25 Sep 2017cs.SEcited by 18

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Abstract (arXiv)

Agile - denoting "the quality of being agile, readiness for motion, nimbleness, activity, dexterity in motion" - software development methods are attempting to offer an answer to the eager business community asking for lighter weight along with faster and nimbler software development processes. This is especially the case with the rapidly growing and volatile Internet software industry as well as for the emerging mobile application environment. The new agile methods have evoked substantial amount of literature and debates. However, academic research on the subject is still scarce, as most of existing publications are written by practitioners or consultants. The aim of this publication is to begin filling this gap by systematically reviewing the existing literature on agile software development methodologies. This publication has three purposes. First, it proposes a definition and a classification of agile software development approaches. Second, it analyses ten software development methods that can be characterized as being "agile" against the defined criterion. Third, it compares these methods and highlights their similarities and differences. Based on this analysis, future research needs are identified and discussed.

Key facts. Cited by 18 papers in the map (data through 7 Oct 2026). First posted on arXiv 25 Sep 2017.

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Citing papers per year: 2021: 1; 2022: 2; 2023: 4; 2024: 6; 2025: 5.

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  1. 2024LLM-Based Multi-Agent Systems for Software Engineering: Literature Review, Vision and the Road Aheadcited by 155
  2. 2023Experiential Co-Learning of Software-Developing Agentscited by 57
  3. 2023Enhancing Large Language Models in Coding Through Multi-Perspective Self-Consistencycited by 46
  4. 2023LILO: Learning Interpretable Libraries by Compressing and Documenting Codecited by 46
  5. 2025CodeFlowBench: A Multi-turn, Iterative Benchmark for Complex Code Generationcited by 16
  6. 2024AXIS: Efficient Human-Agent-Computer Interaction with API-First LLM-Based Agentscited by 11
  7. 2024Experimenting with Multi-Agent Software Development: Towards a Unified Platformcited by 6
  8. 2024Open-Source AI-based SE Tools: Opportunities and Challenges of Collaborative Software Learningcited by 4
  9. 2025Cognitive Agents Powered by Large Language Models for Agile Software Project Managementcited by 4
  10. 2024Exploring Data-Efficient Adaptation of Large Language Models for Code Generationcited by 3
  11. 2025AI-Driven Self-Evolving Software: A Promising Path Toward Software Automationcited by 3
  12. 2025What Makes LLM Agent Simulations Useful for Policy Practice? An Iterative Design Study in Emergency Preparednesscited by 2
6 more
  1. 2021Technology Readiness Levels for Machine Learning Systemscited by 0
  2. 2022Internet-of-Things Architectures for Secure Cyber-Physical Spaces: the VISOR Experience Reportcited by 0
  3. 2022Evident: a Development Methodology and a Knowledge Base Topology for Data Mining, Machine Learning and General Knowledge Managementcited by 0
  4. 2023HIVA: Holographic Intellectual Voice Assistantcited by 0
  5. 2024Generative Language Models Potential for Requirement Engineering Applications: Insights into Current Strengths and Limitationscited by 0
  6. 2025Mirror, Mirror on the Wall -- Which is the Best Model of Them All?cited by 0