Zwinne szacowanie pracochłonności w projektach programistycznych – studium przypadków

Łabędzki, Maciej; Promiński, Patryk; Rybicki, Adam; Wolski, Marcin

doi:10.29015/cerem.359

Cited by 4 publications

(4 citation statements)

References 13 publications

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“…Even though Labedzki et al [40], when examining the performance of Planning Poker in multiple projects with diverse characteristics, found that "Planning Poker is a technique which yields good results in any undertaking, increasing the estimation precision and raising the level of understanding user stories which await their realization", as far as generalization is concerned, our results are limited to projects with a relatively small number of user stories and smaller development teams. The question is whether these three methods would yield similar results with larger development teams with significantly larger set of user stories in the project.…”

Section: Limitationsmentioning

confidence: 78%

“…However, the most used are those that use expert-based subjective assessment [87]. Planning Poker has been used in the software industry and teaching environment [40,31,19,44]. It can provide reliable estimates compared to single expert estimation [5].…”

Section: Project Settingmentioning

confidence: 99%

“…It can provide reliable estimates compared to single expert estimation [5]. Labedzki et al [40] presented a study based on three different reference agile projects with a mature team, different team sizes, project lengths and user stories that differed in size and how they were defined. They concluded that Planning Poker yielded good results in any of the three settings, improved estimation precision and enabled a better understanding of user stories.…”

Section: Project Settingmentioning

confidence: 99%

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Agile Effort Estimation: Comparing the Accuracy and Efficiency of Planning Poker, Bucket System, and Affinity Estimation Methods

Poženel,

Fürst,

Vavpotič

et al. 2023

Int. J. Soft. Eng. Knowl. Eng.

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Published studies on agile effort estimation predominantly focus on comparisons of the accuracy of different estimation methods, while efficiency comparisons, i.e. how much time the estimation methods consume was not in the forefront. However, for practical use in software development, the time required can be a very important cost factor for enterprises, especially when the accuracy of different agile effort estimations is similar. In this study, we thus try to advance the current standard accuracy comparison between methods by introducing efficiency, i.e. time it takes to use a method as an additional dimension of comparison. We conduct this comparison between three agile effort estimation methods that were not yet compared in the literature, namely, Planning Poker, Bucket System and Affinity Estimation. For the comparison, we used eight student teams with 29 students who had to use all the effort estimation methods during the course where they had to finish a programming project in 3 weeks. The results indicate that after the students get used to using the different methods the accuracy between them is not statistically significantly different, however, the efficiency is. On average, Bucket System and Affinity Estimation methods take half as much time as Planning Poker.

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Section: Limitationsmentioning

confidence: 78%

Section: Project Settingmentioning

confidence: 99%

Section: Project Settingmentioning

confidence: 99%

See 1 more Smart Citation

Agile Effort Estimation: Comparing the Accuracy and Efficiency of Planning Poker, Bucket System, and Affinity Estimation Methods

Poženel,

Fürst,

Vavpotič

et al. 2023

Int. J. Soft. Eng. Knowl. Eng.

View full text Add to dashboard Cite

show abstract

“…En las últimas dos décadas, varias encuestas de investigación se han centrado en el esfuerzo del proyecto de software y la estimación del cronograma. Esto es importante, ya que una visión imparcial es esencial para ayudar a la industria a hacer estimaciones más precisas [30].…”

Section: Estado Del Arteunclassified

Estimation of effort in agile software development: Study of the current state in Bogotá

Bustamante

2020

ITECKNE

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Context: Over the years, numerous studies have been developed related to estimating effort in agile software development, which allow us to understand the advances that have been made and the need for their use in companies. Objective: To know the perspective of entrepreneurs from different organizations in Bogotá that work in the sector or are related to the development of agile software and those who have had projects related to the subject. Method: For the elaboration of the article, a bibliographic research is carried out. Results: The data obtained are from 314 respondents in the city of Bogotá, the main findings are: 1) For companies it is extremely important with (34%) the adoption of an effort estimation methodology. 2) The most used estimation technique is the use case point with (43.31%). 3) The most used effort predictor is the Code Line (38.85%) and followed by this STORY POINT with (33.76%). 4) The agile methodology adopted in companies is SCRUM with (43.95%). 5) As the most determining factor to estimate the effort, the team experience with (53.50%) is considered. 6) In the percentage of error between estimate of projected effort and real effort (26.75%) of the respondents determine that this 5% -25% is underestimated. 7) Finally, as a difficulty in your company to estimate the effort of projects through agile software development, the respondents recognize (26.11%) that the resources are the greatest. Conclusions: The estimation of effort is relatively variable, for many companies this depends on the needs of each one, on the other hand, the use of agile methodology and estimation techniques varies in its use depending on the cross between them and how they are used. complement each other.

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Much more than a prediction: Expert-based software effort estimation as a behavioral act

et al. 2023

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Zwinne szacowanie pracochłonności w projektach programistycznych – studium przypadków

Cited by 4 publications

References 13 publications

Agile Effort Estimation: Comparing the Accuracy and Efficiency of Planning Poker, Bucket System, and Affinity Estimation Methods

Agile Effort Estimation: Comparing the Accuracy and Efficiency of Planning Poker, Bucket System, and Affinity Estimation Methods

Estimation of effort in agile software development: Study of the current state in Bogotá

Much more than a prediction: Expert-based software effort estimation as a behavioral act

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