Assessing and Detecting Components Suffering from Sub-optimal Performance for a Web-based CRM System

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Performance is one of the crucial factors related to the success and the sustainability of software systems.**Failure to provide satisfactory performance would result in customers' abandonment and loss of revenue. For**example, Amazon reported that one second delay in loading their webpages could result in $1.6 billion loss in**their sales revenue annually. However, it is very challenging to find areas to improve and optimize system**performance due to limitations of existing tools. Instead of directly pin-pointing the sub-optimal components,**existing performance profiling tools can only provide resource or timing information for each individual**component. As components consume processing time and resources while executing the actual tasks, they**might not be the areas suffering from sub-optimal performance. More sophisticated and in-depth analysis is**required to detect potential areas for performance improvement.**Sparky is a web-based software program responsible for CRM (Customer Relation Management) and quoting**for high speed ink-jet printer jobs for Copywell. Existing process is complex and time consuming. Improve the**efficiency and scalability of Sparky would greatly increase the amount of tasks that can be handled, and hence**results in an increase in the Copywell's income. We process a three-step process to evaluate and improve the**architecture of Sparky. First, we will characterize the workload of Sparky by surveying the domain experts and**mining the existing historical usage data. Second, we will assess Sparky's performance by executing**performance tests and building performance models. Third, various approaches (architectural-level analysis,**design/code-level analysis, and performance anti-pattern detection) will be applied to detect sub-optimal**performance components based on the resulting models.