The integration of external software in project development is challenging and risky, notably because the execution quality of the software and the trustworthiness of the software provider may be unknown at integration time. This is a timely problem and of increasing importance with the advent of the SaaS model of service delivery. Therefore, in choosing the SaaS service to utilize, project managers must identify and evaluate the level of risk associated with each candidate. Trust is commonly assessed through reputation systems; however, existing systems rely on ratings provided by consumers. This raises numerous issues involving the subjectivity and unfairness of the service ratings. This paper describes a framework for reputation-aware software service selection and rating. A selection algorithm is devised for service recommendation, providing SaaS consumers with the best possible choices based on quality, cost, and trust. An automated rating model, based on the expectancy-disconfirmation theory from market science, is also defined to overcome feedback subjectivity issues. The proposed rating and selection models are validated through simulations, demonstrating that the system can effectively capture service behavior and recommend the best possible choices. (SaaS - software as a service)

The future is a combination of software and Internet services interacting with one another. Software makes services better and services make software better. And by bringing together the best of both worlds, we maximize choice, flexibility and capabilities for our customers.

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