Title :
Testing big data (Assuring the quality of large databases)
Author :
Sneed, Harry M. ; Erdoes, Katalin
Author_Institution :
Software Quality Assurance Team, ZTP-Prentner-IT, Vienna, Austria
Abstract :
The volume and variety of modern day databases presents a particular challenge to the system testing community. The question is how to go about testing such large collections of various data types ranging from tables to texts and images. To test those applications which use them, these conglomerations of multiple data object types have to be automatically generated and validated. There is no other way but to automate the test process. This contribution outlines the challenge and presents an automated approach to setting up and testing big data bases. At the end a case study of a large data warehouse is discussed with lessons learned from that industrial test project.
Keywords :
Big Data; data warehouses; program testing; big data testing; large data warehouse; large databases; test process automation; Big data; Data warehouses; Database systems; Generators; Relational databases; Testing; data assertions; data testing tools; data warehouses; images; mixed databases; relational data; text data; validation rules;
Conference_Titel :
Software Testing, Verification and Validation Workshops (ICSTW), 2015 IEEE Eighth International Conference on
Conference_Location :
Graz
DOI :
10.1109/ICSTW.2015.7107424