Software Quality achieved through Coverage Metrics in Database Testing

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MS. A. Askarunisa
MS. P. Prameela
DR. N. Ramaraj


Code coverage is often defined as a measure of the degree to which the source code of a program has been tested. Various metrics for measuring code coverage exist.The number of defects is an important measure of software quality which is widely used in industry. Software test coverage tools can easily and accurately measure the extent to which the software has been exercised .Both testing time and test coverage can be used as measures to model the defect finding process. However test coverage is a more direct measure of test effectiveness and can be expected to correlate better with the number of defects found.In majority of software applications,Database systems play an important role. In literature there is good amount of work done in testing database applications [3, 5, and 6]. The levels of quality, maintainability, testability,and stability of software can be improved by performing measures of the testing process and calculating its metrics. In most of the applications coverage metrics plays a major role in predicting the quality of the software.The accuracy of database testing is improved by calculating the coverage percentage of the frequently used SELECT statements.This paper proposes two algorithms for measuring coverage of the SQL queries. An analysis of the two algorithms also performed as to which metric is better so that it would help the test manager to take effective decisions.Our work in this paper details on importance of coverage metrics required to achieve quality of a database application and presents the various coverage metrics that are used for achieving the testing efficiency of a database application. We have considered six different database applications and calculated the various coverage metrics thereby achieving quality and efficiency in testing.

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How to Cite
Askarunisa, M. A., Prameela, M. P., & Ramaraj, D. N. (2010). Software Quality achieved through Coverage Metrics in Database Testing. INFOCOMP Journal of Computer Science, 9(1), 33-42. Retrieved from