Design And Implementation Of Test Case Selection Based On Color Petri Net In Cloud

In recent years, with the complicated software system, software testing becomes an important part in software development, and in the general case, the process of software testing mainly divided into three steps, i.e., the generation of test cases, choice of test cases and test execution.usually a large collection of test cases of the tested system automatically generated, test cases under this collection contains various functions, in the process of actual execution, all of the test cases are executed is not possible. Normally, we test a certain function of the tested system, so choosing test cases based on the purpose of selection is very necessary, this process can not only improve the test efficiency, but also be targeted on the certain function of the tested system.This dissertation focuses on solving the problem of choosing test cases based on CPN model, the method which is based on purpose is used in this process. In the process of test cases selection, there are a whole lot of repeated calculation and operation, this characteristic just can make it combined with the parallel advantage of cloud computing.In summary, this dissertation aims at the test selection problem, using MapReduce programming on Hadoop platform, a test case selection tool is designed to improve the efficiency and service capabilities of test selection.This dissertation mainly completed the following work:the test purposes of the tested software is determined, and its purpose is set up based on CPN; The algorithm of the test case selection based on the purpose model is designed and implemented; Finally, a test case selection tool is implemented on the cloud platform.Its advantages are:the MapReduce method in cloud computing is applied to solve the problem of low efficiency, time and cost are saved; The low degree of automation in the traditional process of test cases choice is improved based on CPN model.