research-article

A model to detect problems on scrum-based software development projects

Authors:

Mirko Perkusich,

Hyggo Oliveira de Almeida,

Angelo PerkusichAuthors Info & Claims

SAC '13: Proceedings of the 28th Annual ACM Symposium on Applied Computing

Pages 1037 - 1042

https://doi.org/10.1145/2480362.2480560

Published: 18 March 2013 Publication History

Abstract

There is a high rate of software development projects that fails. Whenever problems can be detected ahead of time, software development projects may have better chances of success, and therefore save money and time. In this paper, we present a probabilistic model to help ScrumMasters to apply Scrum in organizations. The model's goal is to provide information to the project's ScrumMaster to help him to be aware of the project's problems and have enough information to guide the team and improve the project's chances of success. We published a survey to collect data for this study and validated the model by applying it to scenarios. The results obtained so far show that the model is promising.

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Cited By

Gaborov MStojanov ZPopov SStojanov JKavalić MKovač DVecštejn I(2024)Development and Validation of a Theoretical Model for Addressing Problems in Agile Meetings: A Systematic Literature Review and a Qualitative StudyApplied Sciences10.3390/app1421968914:21(9689)Online publication date: 23-Oct-2024
https://doi.org/10.3390/app14219689
de Sousa Ade Souza CReis R(2021)A 20‐year mapping of Bayesian belief networks in software project managementIET Software10.1049/sfw2.1204316:1(14-28)Online publication date: 9-Nov-2021
https://doi.org/10.1049/sfw2.12043
Perkusich MChaves e Silva LCosta ARamos FSaraiva RFreire ADilorenzo EDantas ESantos DGorgônio KAlmeida HPerkusich A(2020)Intelligent software engineering in the context of agile software developmentInformation and Software Technology10.1016/j.infsof.2019.106241119:COnline publication date: 1-Mar-2020
https://dl.acm.org/doi/10.1016/j.infsof.2019.106241
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Index Terms

A model to detect problems on scrum-based software development projects
1. Software and its engineering

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cover image ACM Conferences

SAC '13: Proceedings of the 28th Annual ACM Symposium on Applied Computing

March 2013

2124 pages

ISBN:9781450316569

DOI:10.1145/2480362

Conference Chairs:
Sung Y. Shin
South Dakota State University, United States
,
José Carlos Maldonado
ICMC - University of São Paulo, Brazil

Copyright © 2013 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 18 March 2013

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SAC '13: SAC '13

March 18 - 22, 2013

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SAC '13 Paper Acceptance Rate 255 of 1,063 submissions, 24%;

Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

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Cited By

Gaborov MStojanov ZPopov SStojanov JKavalić MKovač DVecštejn I(2024)Development and Validation of a Theoretical Model for Addressing Problems in Agile Meetings: A Systematic Literature Review and a Qualitative StudyApplied Sciences10.3390/app1421968914:21(9689)Online publication date: 23-Oct-2024
https://doi.org/10.3390/app14219689
de Sousa Ade Souza CReis R(2021)A 20‐year mapping of Bayesian belief networks in software project managementIET Software10.1049/sfw2.1204316:1(14-28)Online publication date: 9-Nov-2021
https://doi.org/10.1049/sfw2.12043
Perkusich MChaves e Silva LCosta ARamos FSaraiva RFreire ADilorenzo EDantas ESantos DGorgônio KAlmeida HPerkusich A(2020)Intelligent software engineering in the context of agile software developmentInformation and Software Technology10.1016/j.infsof.2019.106241119:COnline publication date: 1-Mar-2020
https://dl.acm.org/doi/10.1016/j.infsof.2019.106241
Wang Z(2020)Modelling and Simulation of Scrum Team Strategies: A Multi-agent ApproachSoftware Engineering Perspectives in Intelligent Systems10.1007/978-3-030-63322-6_4(32-63)Online publication date: 16-Dec-2020
https://doi.org/10.1007/978-3-030-63322-6_4
Choetkiertikul MDam HTran TPham TGhose AMenzies T(2019)A Deep Learning Model for Estimating Story PointsIEEE Transactions on Software Engineering10.1109/TSE.2018.279247345:7(637-656)Online publication date: 1-Jul-2019
https://doi.org/10.1109/TSE.2018.2792473
Choetkiertikul MDam HTran TGhose AGrundy J(2018)Predicting Delivery Capability in Iterative Software DevelopmentIEEE Transactions on Software Engineering10.1109/TSE.2017.269398944:6(551-573)Online publication date: 1-Jun-2018
https://doi.org/10.1109/TSE.2017.2693989
Dragicevic SCelar STuric M(2017)Bayesian network model for task effort estimation in agile software developmentJournal of Systems and Software10.1016/j.jss.2017.01.027127:C(109-119)Online publication date: 1-May-2017
https://dl.acm.org/doi/10.1016/j.jss.2017.01.027
Perkusich MMedeiros Ae Silva LGorgônio Kde Almeida HPerkusich AWainwright RCorchado JBechini AHong J(2015)A Bayesian network approach to assist on the interpretation of software metricsProceedings of the 30th Annual ACM Symposium on Applied Computing10.1145/2695664.2695749(1498-1503)Online publication date: 13-Apr-2015
https://dl.acm.org/doi/10.1145/2695664.2695749
Freire ASilva RPerkusich MAlmeida HPerkusich A(2015)A Bayesian Network Model to Assess Agile Teams' Teamwork Quality2015 29th Brazilian Symposium on Software Engineering10.1109/SBES.2015.29(191-196)Online publication date: Sep-2015
https://doi.org/10.1109/SBES.2015.29
Perkusich MSoares GAlmeida HPerkusich A(2015)A procedure to detect problems of processes in software development projects using Bayesian networksExpert Systems with Applications: An International Journal10.1016/j.eswa.2014.08.01542:1(437-450)Online publication date: 1-Jan-2015
https://dl.acm.org/doi/10.1016/j.eswa.2014.08.015
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