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Productivity In A Waterfall Versus Agile Development Team

Author

Listed:
  • Albert-Cristian CRÄ‚CIUN

  • Ioana-Alexandra MATEI

  • Silviu-Gabriel FLORIAN

  • Cătălin TUDOSE

    (POLITEHNICA National University for Science and Technology of Bucharest and Luxoft Romania, Romania)

  • Costin-Anton BOIANGIU

    (POLITEHNICA National University for Science and Technology of Bucharest, Romania)

Abstract

This research delves into a comparative analysis of productivity in Waterfall and Agile development teams. It challenges the traditional metrics of productivity, like lines of code and hours worked, revealing their limitations in the complex realm of software development. The study emphasizes the need to consider both qualitative aspects - such as code quality and team collaboration - and quantitative measures. It explores how Waterfall and Agile methodologies influence team dynamics, efficiency, and project success, providing insights through industry examples and modern tools. The comparison presents a comprehensive view of evolving productivity metrics in software development. This article comprehensively explores the various reasons why Agile methodology is widely considered to significantly enhance productivity compared to the Waterfall approach. Though both methodologies contribute to increased productivity, Agile distinguishes itself through its inherent characteristics that prove advantageous not only for achieving project success but also for the well-being of developers.

Suggested Citation

  • Albert-Cristian CRÄ‚CIUN & Ioana-Alexandra MATEI & Silviu-Gabriel FLORIAN & Cătălin TUDOSE & Costin-Anton BOIANGIU, 2024. "Productivity In A Waterfall Versus Agile Development Team," Journal of Information Systems & Operations Management, Romanian-American University, vol. 18(2), pages 51-67, December.
    • Handle: RePEc:rau:jisomg:v:18:y:2024:i:2:p:51-67
    DOI: 10.5281/zenodo.21827637
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    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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