Asymptotic analysis of multiclass closed queueing networks: multiple bottlenecks
Performance Evaluation
Mean-Value Analysis of Closed Multichain Queuing Networks
Journal of the ACM (JACM)
Designing Process Replication and Activation: A Quantitative Approach
IEEE Transactions on Software Engineering
Simple analytic modeling of software contention
ACM SIGMETRICS Performance Evaluation Review
IEEE Transactions on Software Engineering
A performance analysis method for autonomic computing systems
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
Tracking adaptive performance models using dynamic clustering of user classes
Proceedings of the 2nd ACM/SPEC International Conference on Performance engineering
ICWE'12 Proceedings of the 12th international conference on Current Trends in Web Engineering
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In this paper, we present a method for performance testing of transactional systems. The methods models the system under test, finds the software and hardware bottlenecks and generate the workloads that saturate them. The framework is adaptive, the model and workloads are determined during the performance test execution by measuring the system performance, fitting a performance model and by analytically computing the number and mix of users that will saturate the bottlenecks. We model the software system using a two layers queuing model and use analytical techniques to find the workload mixes that change the bottlenecks in the system. Those workload mixes become stress vectors and initial starting points for the stress test cases. The rest of test cases are generated based on a feedback loop that drives the software system towards the worst case behaviour.