Abstract

Web service composition is a method of developing a new web service from an existing one based on business goals. Web services selected for composition should provide accurate operational results and reliable applications. However, most alternative service providers have not yet fulfilled users' needs in terms of services and processes. Service providers, in fact, have focused on enhancing nonfunctional attributes, such as efficiencies of time, cost, and availability, which still face limitations. Furthermore, it remains advantageous to compose services and suitably plan them around business plans. Thus, this study introduces hybrid testing using a combination of the functional and nonfunctional testing approaches. The former was used to design a test case through the equivalence class partitioning technique, and the latter was used to select suitable services for the test results. We find defects and appropriate solutions for combining services based on business requirements. The mutation-based harmony search (MBHS) algorithm is proposed to select web services and to compose with minimum defects. The results of this study reveal that MBHS can support a combination of various services more efficiently and dramatically than other metaheuristic methodologies. Additionally, it helps find appropriate solutions to compose services based on business plans.

Highlights

  • Test Case ProcessIs is the process of evaluating defects found by the test case

  • Adjusting Defect in Tasks with QoS. is process enhances the calculated service via functional testing, with an equal number of task defects (Table 5). is process is calculated by nonfunctional testing as QoS, which is divided into two parts of the calculation performance for each web service

  • Where QoSavailability represents the value of conditioned comparison and x is quality value of data required for comparison

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Summary

Test Case Process

Is is the process of evaluating defects found by the test case. E calculation results can be divided into three sections, as follows. E RDT of a test case is calculated using the number of defects detected and number of test cases taken to find defects for each test case of web service, i. For each defect severity value, defects have different impacts. E severity value is calculated per the following equation: t For each defect severity value, defects have different impacts. e analysis of defects from the test case should be classified according to the severity level, as shown in Table 3. e severity value is calculated per the following equation: t

Related works
Objective
Service Selection for Composition by Mutation-Based
Performance Analysis and Comparison
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