Quantitative system performance: computer system analysis using queueing network models
Quantitative system performance: computer system analysis using queueing network models
Asymptotic analysis of multiclass closed queueing networks: multiple bottlenecks
Performance Evaluation
Capacity planning for Web performance: metrics, models, and methods
Capacity planning for Web performance: metrics, models, and methods
Mean-Value Analysis of Closed Multichain Queuing Networks
Journal of the ACM (JACM)
Performance bound hierarchies for queueing networks
ACM Transactions on Computer Systems (TOCS)
Designing Process Replication and Activation: A Quantitative Approach
IEEE Transactions on Software Engineering
Simple analytic modeling of software contention
ACM SIGMETRICS Performance Evaluation Review
Scaling for E Business: Technologies, Models, Performance, and Capacity Planning
Scaling for E Business: Technologies, Models, Performance, and Capacity Planning
IEEE Transactions on Software Engineering
Performance Engineering of Component-Based Distributed Software Systems
Performance Engineering, State of the Art and Current Trends
Balanced job bound analysis of queueing networks
SIGMETRICS '81 Proceedings of the 1981 ACM SIGMETRICS conference on Measurement and modeling of computer systems
Feedback Control with Queueing-Theoretic Prediction for Relative Delay Guarantees in Web Servers
RTAS '03 Proceedings of the The 9th IEEE Real-Time and Embedded Technology and Applications Symposium
Feedback Control of Computing Systems
Feedback Control of Computing Systems
A method for evaluating the impact of software configuration parameters on e-commerce sites
Proceedings of the 5th international workshop on Software and performance
Hierarchical model-based autonomic control of software systems
DEAS '05 Proceedings of the 2005 workshop on Design and evolution of autonomic application software
Tracking time-varying parameters in software systems with extended Kalman filters
CASCON '05 Proceedings of the 2005 conference of the Centre for Advanced Studies on Collaborative research
The Use of Optimal Filters to Track Parameters of Performance Models
QEST '05 Proceedings of the Second International Conference on the Quantitative Evaluation of Systems
Guerrilla Capacity Planning: A Tactical Approach to Planning for Highly Scalable Applications and Services
A performance analysis method for autonomic computing systems
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
QoS management in service-oriented architectures
Performance Evaluation
A framework for measurement based performance modeling
WOSP '08 Proceedings of the 7th international workshop on Software and performance
Improved performance models of web-based software systems
INES'09 Proceedings of the IEEE 13th international conference on Intelligent Engineering Systems
Performance aware open-world software in a 3-layer architecture
Proceedings of the first joint WOSP/SIPEW international conference on Performance engineering
Modeling the effect of application server settings on the performance of J2EE web applications
TEAA'06 Proceedings of the 2nd international conference on Trends in enterprise application architecture
Tracking adaptive performance models using dynamic clustering of user classes
Proceedings of the 2nd ACM/SPEC International Conference on Performance engineering
Managing a SaaS application in the cloud using PaaS policy sets and a strategy-tree
Proceedings of the 7th International Conference on Network and Services Management
Iterative test suites refinement for elastic computing systems
Proceedings of the 2013 9th Joint Meeting on Foundations of Software Engineering
Mitigating DoS Attacks Using Performance Model-Driven Adaptive Algorithms
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
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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 autonomic, 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-layer 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.