Abstract
Web service composition is the process of combining and reusing existing web services to create new business processes to satisfy specific user requirements. Reliability plays an important role in ensuring the quality of web service composition. However, owing to the flexibility and complexity of such architecture, sufficient estimation of reliability is difficult. In this paper, the authors propose a method to estimate the reliability of web service compositions based on Bayes reliability assessment by considering it to be a decision-making problem. This improves the testing efficiency and accuracy of such methods. To this end, the authors focus on fully utilizing prior information of web services to increase the accuracy of prior distributions, and construct a Markov model in terms of the reliabilities of the web composition and each web service to integrate the limited test data. The authors further propose a method of minimum risk (MMR) to calculate the initial values of hyperparameters satisfying the constraint of minimal risk of the wrong decision. Experiments demonstrate that the proposed method is capable of efficiently utilizing prior module-level failure information, comparing with the Bayesian Monte Carlo method (BMCM) and expert scoring method (ESM), when the number of failures increased from 0 to 5, reducing the required number of test cases from 19.8% to 28.9% and 6.1% to 14.1% separately, improving the reliability assessment of web service compositions, and reducing the expenses incurred by system-level reliability testing and demonstration.
Highlights
Web services are service-oriented architecture technologies that are executed using standard web protocols to ensure their operation varying platforms
A reliability assessment method was proposed for web service compositions
The authors used transfer probabilities to represent the inter-relationships between the constituent web services, and used a Markov model to transfer the probability matrix and calculate the reliability of web service composition
Summary
Web services are service-oriented architecture technologies that are executed using standard web protocols to ensure their operation varying platforms. Following the completion of growth testing, a reliability demonstration is performed to verify a specific reliability requirement Both broad and deep studies have been conducted on software reliability assessment to expose software defects and improve software reliability at early stages. When the number of test cases is very high or the test data are limited, software input is selected using statistical methods to promote rapid reliability growth of the software to ensure high reliability software demonstration testing [3] In this context, Bayes reliability inference has been extensively applied to reliability estimation, and a wealth of experts and prior knowledge about system/subsystem performances are associated with it [1]. The Bayesian approach has been adopted because it combines subjective judgment or prior experience with data obtained from test samples In other words, it uses a combination of existing experience and new test data to assess reliability metrics. The fundamental advantage of adopting the Bayesian approach is that it augments the quality of data, thereby reducing the uncertainty involved in decision making
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