English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Open

This paper aims to utilize the fuzzy logic concepts to improve the effort estimation in Scrum framework and in turn add a significant enhancement to Scrum. Scrum framework is one of the most popular agile methods in which the team accomplishes their work by breaking down the work into a series of sprints. In Scrum, there are many factors that have a significant influence on the effort estimation of each task in a Sprint. These factors are: Development Team Experience, Task Complexity, Task Size, and Estimation Accuracy. These factors are usually presented using linguistic quantifiers. Therefore, this paper utilizes the fuzzy logic concepts to build a fuzzy based model that can improve the effort estimation in Scrum framework. The proposed model includes three components: fuzzifier, inference engine, and defuzzifier. In addition, the proposed model takes into consideration the feedback that is resulted from comparing the estimated effort and the actual effort. The researcher designed the proposed model using MATLAB. The proposed model is applied on three Sprints of a real software development project to present how the proposed model works and to show how it becomes more accurate over time and gives a better effort estimation. In addition, the Scrum Master and the development team can use the proposed model to monitor the improvement in effort estimation accuracy over the project life.

A Fuzzy based Model for Effort Estimation in Scrum Projects