Improving Interactive System Performance Using TIPME

Abstract

On the vast majority of today’s computers, the dominant form of computation is GUI-based user interaction. In such an environment, the user’s perception is the final arbiter of performance. Human-factors research shows that a user’s perception of performance is affected by unexpectedly long delays. However, most performance-tuning techniques currently rely on throughput-sensitive benchmarks. While these techniques improve the average performance of the system, they do little to detect or eliminate response-time variabilities—in particular, unexpectedly long delays. We introduce a measurement methodology that improves user-perceived performance by helping us to identify and eliminate the causes of the unexpected long response times that users find unacceptable. We describe TIPME (The Interactive Performance Monitoring Environment), a collection of measurement tools that implements this methodology, and we present two case studies that demonstrate its effectiveness. Each of the performance problems we identify drastically affects variability in response time in a mature system, demonstrating that current tuning techniques do not address this class of performance problems.