Assessing Software Service Quality and Trustworthiness at Selection Time

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 th...

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Bibliographic Details
Published in:IEEE transactions on software engineering 2010-07, Vol.36 (4), p.559-574
Main Authors: Limam, N, Boutaba, R
Format: Article
Language:English
Subjects:
Algorithms
Analysis
Automation
Business
Computer industry
Computer programs
Computer simulation
Consumers
Costs
Decision making
Digital Object Identifier
Feedback
Markets
Mathematical models
Monitoring
Project management
Quality of service
Ratings
Ratings & rankings
Reputations
review and rating
Risk
Risk management
service utility
SLA monitoring
Software
Software as a service (SaaS)
Software engineering
Software maintenance
Software performance
Software quality
software selection
Software services
Studies
Subjectivity
Trust
trust and reputation
Trustworthiness
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Summary: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.
ISSN:0098-5589
1939-3520
DOI:10.1109/TSE.2010.2