Web Services form the basis of the web based eCommerce eScience applications so it is vital that robust services are developed. Traditional validation and verification techniques are centred around the concept of removing all faults to guarantee correct operation whereas Dependability gives an assessment of how dependably a system can deliver the required functionality by assessing attributes, and by eliminating threats via means attempts to improve dependability. Fault injection is a well-proven dependability assessment method. Although much work has been done in the area of fault injection and distributed systems in general, there appears to have been little research carried out on applying this to middleware systems and Web Services in particular. There are additional problems associated with applying existing fault injection technologies to Web Services running in a virtual machine environment since most are either invasive or work at a machine level. The Fault Injection Technology (FIT) method has been devised to address these problems for middleware systems. The Web Service-Fault Injection Technology (WS-FIT) implementation applies the FIT method, based on network level fault injection, to Web Services to create a non-invasive dependability assessment method. It allows targeted perturbation of Web Service RFC parameters as well as more traditional network level fault injection operations. The WS-FIT tool includes taxonomies that define a system under test, fault models to apply and failure modes to be detected, and uses these taxonomies to generate fault injection campaigns. WS-FIT has been applied to a number of case studies and has successfully demonstrated its effectiveness. It has also been successfully applied to a third-party system to evaluate dependability means. It performed this dependability assessment as well as allowing debugging of the means to be undertaken uncovering unknown faults.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:436627 |
| Date | January 2006 |
| Creators | Looker, Nik |
| Publisher | Durham University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://etheses.dur.ac.uk/2888/ |
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