Improving the Quality Validation of Semi-Structured Data Process Using Hadoop

Abstract

The age of big data testing is now coming. But the traditional software testing may not be able to handle such large quantities of unstructured data. Testing aims to assess product quality by identifying persisting artifacts. The software development industry experiences constant pressure to innovate novel software which works quite competently while ensuring reliability. The testing involves quality perfection, fidelity, cost reduction, etc., and hence demands the need to augment most application expanses. In this aspect software Industries implementing testing techniques like Manual and Automation testing tools. Software test cases are to find myths by using verification of plans like the question that arises now is, how to develop a high performance platform to efficiently test the big data and how to analyze an appropriate algorithm to find the useful things from big data To deeply discuss this issue, this paper begins with a brief introduction to big data testing, followed by the discussions of Hadoop testing. Some important open issues and further research directions will also be presented for the next step of big data testing.