Abstract
Software testing is an integral part of software development lifecycle. Lack of testing can often lead to disastrous consequences including lost of data, fortunes, and even lives. Despite its importance, current software testing practice lacks automation, and is still primarily based on highly manual processes from the generation of test cases up to the actual execution of the test. Although the emergence of helpful automated testing tools in the market is blooming, their adoptions are lacking as they do not adequately provide the right level abstraction and automation required by test engineers. JTst is a Java based automated unit testing tool that addresses some of the aforementioned issues. The main novel features are the fact that JTst automates the test preparation activities, facilitates the test data generation through recombination, and allows concurrent execution of test data, in order to encourage higher product quality at lower testing costs.
Highlights
In line with market demands and the need for technological innovations, designing and implementing a useful engineering product is ever growing in complexity
Covering as much as 40 to 50 percent of the development costs and resources[1], current software testing practice is still primarily based on highly manual processes from the generation of test cases up to the actual execution of the test
In order to address some of the aforementioned issues, this paper describes an automated software testing tool, called JTst, based on the use of Java technology
Summary
In line with market demands and the need for technological innovations, designing and implementing a useful engineering product is ever growing in complexity. In order to address some of the aforementioned issues, this paper describes an automated software testing tool, called JTst, based on the use of Java technology. The first responsibility is to iteratively parse the test cases (defined in JTst fault files), and automatically generates and executes the appropriate Java code driver. In the case of one parameter as sensitivity variable, provided that all the base data values are unique, recombination can regenerate new test cases based on: The number of generated test cases = n2 where n = number of defined test cases. In the case of all parameters as sensitivity variable, provided that all base data values are unique, recombination can regenerate new test cases based on: The number of generated test cases = (p*n2) – where n = number of defined test cases p = number of input parameters = the number of repetitive values = n*(p-1). A key issue here is the fact that the faults can always be reproducible with the same sets of inputs
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