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Other literature type . 2024
License: CC BY
Data sources: Datacite
ZENODO
Other literature type . 2024
License: CC BY
Data sources: Datacite
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Guidelines for the Efficient Use of the Bogus Library in C# for Fake Data Generation

Authors: Filho, Nagib;

Guidelines for the Efficient Use of the Bogus Library in C# for Fake Data Generation

Abstract

The Bogus library is widely used for generating fake data in software development projects, especially in testing environments. This article presents a set of guidelines and best practices for the efficient use of Bogus in C#. The goal is to assist developers in creating realistic and varied data, ensuring that software tests are robust and representative. The article also explores some advanced features of the library.

Keywords

fake data generation, creation of fictitious objects, test data, faker library, bogus library, mocking, bogus, best practices, random data, c#

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green
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