Effort Estimation using Bayesian Networks for Agile Development

Ratke, Cláudio; Hoffmann, Helcio Hermes; Gaspar, Tercio; Floriani, Pedro Edmundo

doi:10.1109/cais.2019.8769455

Cited by 6 publications

(2 citation statements)

References 9 publications

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“…The model was intended for the use of inexperienced teams to help them estimate the required effort more easily. Another BN model was used to predict the user story's effort [28]. That model was based on narrative texts.…”

Section: Related Workmentioning

confidence: 99%

Advanced Bayesian Network for Task Effort Estimation in Agile Software Development

Turic,

Celar,

Dragicevic

et al. 2023

Applied Sciences

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Effort estimation is always quite a challenge, especially for agile software development projects. This paper describes the process of building a Bayesian network model for effort prediction in agile development. Very few studies have addressed the application of Bayesian networks to assess agile development efforts. Some research has not been validated in practice, and some has been validated on one or two projects. This paper aims to bring the implementation and use of Bayesian networks for effort prediction closer to the practitioners. This process consists of two phases. The Bayesian network model for task effort estimation is constructed and validated in the first phase on real agile projects. A relatively small model showed satisfactory estimation accuracy, but only five output intervals were used. The model was proven to be useful in daily work, but the project manager wanted to obtain more output intervals, although increasing the number of output intervals reduces the prediction accuracy. In the second phase, the focus is on increasing the number of output intervals while maintaining satisfactory accuracy. The advanced model for task effort estimation is developed and tested on real projects of two software firms.

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Section: Related Workmentioning

confidence: 99%

Advanced Bayesian Network for Task Effort Estimation in Agile Software Development

Turic,

Celar,

Dragicevic

et al. 2023

Applied Sciences

View full text Add to dashboard Cite

show abstract

“…In addition, some researches put forward new methods to solve these problems. In [10] [11], machine learning was used for estimation. What's more, the authors in [10] compared machine learning, expert opinions and mathematical algorithm models, finally concluding that machine learning is more accurate in Agile estimation; By analyzing the text of user story description, Sudarmaningtyas and Mohamed [10] got 83% accuracy of story point estimation.…”

Section: Introductionmentioning

confidence: 99%

Real-time Estimation Approach to Scrum Projects Effort: Task Point and Individual Reliability (S)

Guo,

Shi

et al. 2023

International Conferences on Software Engineering and Knowledge Engineering

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In software project management, it is a useful method to control the progress of the project through effort estimation. How to estimate the effort in real time in the Agile software development has always been a difficulty faced by Agile teams. Aiming at the current mainstream Agile Software Development techniques, Scrum framework, this paper puts forward the calculation approach for reliability of Scrum team members and the Sprint development time estimation approach based on individual reliability, i.e., the total working time estimation of the next Sprint is realized by estimating and adjusting the working time of the team individuals. 51 development teams with 5-9 people have put this method into practice for experimental verification, and the results show that the highest estimation accuracy of this approach can reach 84.1%.

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Data-driven effort estimation techniques of agile user stories: a systematic literature review

Alsaadi

Saeedi

2022

Artif Intell Rev

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Effort Estimation using Bayesian Networks for Agile Development

Cited by 6 publications

References 9 publications

Advanced Bayesian Network for Task Effort Estimation in Agile Software Development

Advanced Bayesian Network for Task Effort Estimation in Agile Software Development

Real-time Estimation Approach to Scrum Projects Effort: Task Point and Individual Reliability (S)

Data-driven effort estimation techniques of agile user stories: a systematic literature review

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