On the Development of Feature-Based Sprint in AGILE

  • Sarika SharmaEmail author
  • Deepak Kumar
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 904)


AGILE methodology is widely used throughout the information technology industry for software development. In AGILE methodology, the delivery cycle is broken down into sprints or iterations. Many iteration-based AGILE teams use a time-boxed 1-hour discussion midway through a 2-week iteration (the team selects an iteration duration that provides them frequent enough feedback) (Cohn in AGILE Estimating and Planning, 2005 [1]). A sprint or iteration is expected to deliver a piece of functionality within a fixed period of time. The length of AGILE sprint is measured in number of days. Hence, it can be concluded that the unit of sprint is time, measured in numbers of days. But since AGILE is feature-driven, the unit of sprint should not be limited to time. There is a need to explore other measures that can be used to define or determine the length of the AGILE sprint. The purpose of this paper is to find out any other unit to define or derive the length of sprint. The paper also explores the various ways in which the AGILE developer(s), AGILE tester(s), and AGILE end user(s) can be benefited by changing the unit of sprint length from time to something else. This paper particularly talks about the possibility of using the “feature” as unit of sprint and lists down the advantages and disadvantages of using “feature” over “time” as unit of sprint. The term “sprint” or “iteration” is used as synonyms throughout the discussion.


Software engineering Software development AGILE Sprint Iteration Length of sprint Sprint planning Iteration Planning Fixed length sprint 


  1. 1.
    Cohn, M.: AGILE Estimating And Planning Is The Definitive, Practical Guide To Estimating And Planning AGILE Projects, AGILE Alliance Cofounder Mike Cohn Discusses The Philosophy Of AGILE Estimating [2] (2005)Google Scholar
  2. 2.
    AGILE Alliance “AGILE Practice Guide” [1] (2017)Google Scholar
  3. 3.
    Gangji, A., Hartman, B.: Agile SCRUM for Denver Web Development. Neon Rain Interactive. Retrieved September 25 (2015)Google Scholar
  4. 4.
    Dhir, S., Deepak, K., Singh, V.B.: An estimation technique in agile archetype using story points and function point analysis. Int. J. Process. Manag. Benchmarking 7(4), 518–539 (2017). Inderscience. ISSN online: 1741-816X, ISSN print: 1460-6739Google Scholar
  5. 5.
    Cole, R., Scotcher, E.: Brilliant AGILE Project Management [3] (2016)Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Amity UniversityNoidaIndia

Personalised recommendations