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Article detail · 2021

Big Data Testing Framework for Recommendation Systems in e-Science and e-Commerce Domains

Journal

2021 IEEE International Conference on Big Data (Big Data)
OpenAlex Citations 21 Top 10% Percentile 96.4% FWCI 4.86
Year
2021
Type
conference-paper

Data source split

  • YÖKSİS venue 2021 IEEE International Conference on Big Data (Big Data)
  • OpenAlex OpenAlex enrichment (abstract, citations, topics)

Abstract

OpenAlex · English

Software testing is an important process to evaluate whether the developed software applications meet the required specifications. There is an emerging need for testing frameworks for big data software projects to ensure the quality of the big data applications and satisfy the user requirements. In this study, we propose a software testing framework that can be utilized in big data projects both in e-science and e-commerce. In particular, we design the proposed framework to test big data-based recommendation applications. To show the usability of the proposed framework, we provide a reference prototype implementation and use the prototype to test a big data recommendation application. We apply the prototype implementation to test both functional and non-functional methods of the recommendation application. The results indicate that the proposed testing framework is usable and efficient for testing the recommendation systems that use big data processing techniques.

Topics

Citations

OpenAlex cited_by_count. Not a WoS or Scopus citation count; those sources have no separate column here.

21 citations

OpenAlex cited_by_count (cache / database)

Authors

No author information.