Optimal Sprint Length Determination for Agile-Based Software Development
Source abstract
Abstract
A carefully planned software development process helps in maintaining the quality of the software. In today’s scenario the primitive software development models have been replaced by the Agile based models like SCRUM, KANBAN, LEAN, etc. Although, every framework has its own boon, the reason for widespread acceptance of the agile-based approach is its evolutionary nature that permits change in the path of software development. The development process occurs in iterative and incremental cycles called sprints. In SCRUM, which is one of the most widely used agile-based software development modeling framework; the sprint length is fixed throughout the process wherein; it is usually taken to be 1–4 weeks. But in practical application, the sprint length should be altered intuitively as per the requirement. To overcome this limitation, in this paper, a methodical work has been presented that determines the optimal sprint length based on two varied and yet connected attributes; the cost incurred and the work intensity required. The approach defines the number of tasks performed in each sprint along with the corresponding cost incurred in performing those tasks. Multi-attribute utility theory (MAUT), a multi-criterion decision making approach, has been utilized to find the required trade-off between two attributes under consideration. The proposed modeling framework has been validated using real life data set. With the use of the model, the optimal sprint for each sprint could be evaluated which was much shorter than the original length. Thus, the results obtained validate the proposal of a dynamic sprint length that can be determined before the start of each sprint. The structure would help in cost as well as time savings for a firm.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Software Reliability and Analysis Research · Software Engineering Research · Software Engineering Techniques and Practices
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (35)
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1. K. Beck, M. Beedle, A. Van Bennekum, A. Cockburn, W. Cunningham et al., “Manifesto for agile software development,” 2001. [Online]. Available: https://agilemanifesto.org/.
2. VersionOne Inc., “The 14th annual state of agile report,” Technical Report, VersionOne Inc., 2020. [Online]. Available: https://stateofagile.com/.
3. Sutherland · The Definitive Guide to Scrum: The Rules of the Game · 2013 · 268
4. Abrahamsson · Agile Software Development Methods: Review and Analysis · 2002 · 478 · 107
5. Using scrum in global software development: A systematic literature review
6. Journey towards agility: The agile wheel explored10.1108/09544780010318398 ↗
7. Identifying some critical changes required in adopting Agile practices in traditional software development projects10.1108/02656711011035147 ↗
8. Agile software development practices: Evolution, principles, and criticisms10.1108/02656711211272863 ↗
9. Doyle · Agile Processes in Software Engineering and Extreme Programming. XP 2014. Lecture Notes in Business Information Processing · 2014 · 179
10. Optimising Agile development practices for the maintenance operation: Nine heuristics10.1007/s10664-014-9335-7 ↗
11. Teamwork quality and project success in software development: A survey of agile development teams10.1016/j.jss.2016.09.028 ↗
12. Significant factors of the successful lean six-sigma implementation10.33889/IJMEMS.2017.2.2-009 ↗
13. OSCRUM: A modified scrum for open-source software development
14. The application of a new secure software development life cycle (S-SDLC) with Agile methodologies10.3390/electronics8111218 ↗
15. SKI: A new agile framework that supports, develops, continuous delivery, and lean hypothesis testing10.24251/HICSS.2020.761 ↗
16. Multi-sprint planning and smooth replanning10.1016/j.jss.2013.04.028 ↗
17. Software metrics in Agile software: An empirical study
18. Software quality analysis for Agile development
19. Software reliability growth modeling for agile software development10.1515/amcs-2017-0054 ↗
20. Mishra · Quality, IT and Business Operations · 2018 · 25110.1007/978-981-10-5577-5_20 ↗
21. Visual Paradigm,, “Why fixed length of sprints in Scrum,” 2020. [Online]. Available: https://www.visual-paradigm.com/scrum/why-fixed-length-of-sprints-in-scrum/.
22. What do practitioners vary in using scrum?
23. M. Cohn, “Time pressure improves productivity & quality up to a point,” 2020. [Online]. Available: https://www.mountaingoatsoftware.com/blog/time-pressure-improves-productivity-qualityup-to-a-point.
24. Parkinson · Parkinson’s Law, and Other Studies in Administration · 1957 · 24
25. High-level software requirements and iteration changes: A predictive model10.1007/s10664-018-9656-z ↗
26. Kapur · Software Reliability Assessment with OR Applications · 201110.1007/978-0-85729-204-9 ↗
27. Fishburn · Utility Theory for Decision Making · 197010.21236/AD0708563 ↗
28. A multi-criteria decision model to determine inspection intervals of condition monitoring based on delay time analysis10.1016/j.ress.2008.10.001 ↗
29. Reliability analysis and optimal version-updating for open-source software10.1016/j.infsof.2011.04.005 ↗
30. Modeling the impact of remanufacturing process in determining demand-cost tradeoff using MAUT
31. Reliability analysis and optimal release time for a software using multi-attribute utility theory
32. A multi-attribute approach for release time and reliability trend analysis of a software
33. Application of multi-attribute utility theory in multiple releases of software
34. Modeling and characterizing software vulnerabilities10.33889/IJMEMS.2017.2.4-022 ↗
35. SAS/ETS User’s Guide Version 9.1 · 2004