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Ednaldo Dilorenzo

Researcher at Federal University of Campina Grande

Publications -  8
Citations -  120

Ednaldo Dilorenzo is an academic researcher from Federal University of Campina Grande. The author has contributed to research in topics: Agile software development & Empirical process (process control model). The author has an hindex of 4, co-authored 8 publications receiving 49 citations.

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Intelligent software engineering in the context of agile software development: A systematic literature review

TL;DR: Overall, although the topic area is up-and-coming, for many areas of application, it is still in its infancy, so there is a need for more empirical studies, and there are a plethora of new opportunities for researchers.
Proceedings ArticleDOI

A systematic review on the use of Definition of Done on agile software development projects

TL;DR: There is a need for more and better empirical studies documenting and evaluating the use of the DoD in agile software development, and a map of how DoD is currently being used in the industry can be used as a starting point to define or compare with their own DoD definition.
Journal ArticleDOI

Effort Estimation in Agile Software Development: An Updated Review

TL;DR: An updated review of the state of the art based on a Forward Snowballing approach, which identified a strong indication of solutions based on Artificial Intelligence and Machine Learning methods for effort estimation in Agile Software Development (ASD).
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Team Formation in Software Engineering: A Systematic Mapping Study

TL;DR: There is a predominant use of search-based approaches that combine search and optimization techniques with technical attributes in software team formation, however, the adoption of non-technical attributes as complementary information is a tendency.
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Enabling the Reuse of Software Development Assets Through a Taxonomy for User Stories

TL;DR: A taxonomy for adding link semantics between USs, focusing on easing the task of identifying similar ones, which has shown that users considered the taxonomy a useful approach to ease the process of assessing the similarity between user stories.