An Extended Domain-Based Model of Software Reliability
IEEE Transactions on Software Engineering
A Markov Chain Model for Statistical Software Testing
IEEE Transactions on Software Engineering
Sun performance and tuning (2nd ed.): Java and the Internet
Sun performance and tuning (2nd ed.): Java and the Internet
Operational Profiles in Software-Reliability Engineering
IEEE Software
The Automatic Generation of Load Test Suites and the Assessment of the Resulting Software
IEEE Transactions on Software Engineering
Performability evaluation: where it is and what lies ahead
IPDS '95 Proceedings of the International Computer Performance and Dependability Symposium on Computer Performance and Dependability Symposium
ACS'07 Proceedings of the 7th Conference on 7th WSEAS International Conference on Applied Computer Science - Volume 7
An Industrial Case Study of Customizing Operational Profiles Using Log Compression
Proceedings of the 30th international conference on Software engineering
PIRR: a methodology for distributed network management in mobile networks
WSEAS Transactions on Information Science and Applications
ICOSSSE'08 Proceedings of the 7th WSEAS international conference on System science and simulation in engineering
Efficiently extracting operational profiles from execution logs using suffix arrays
ISSRE'09 Proceedings of the 20th IEEE international conference on software reliability engineering
Methods and opportunities for rejuvenation in aging distributed software systems
Journal of Systems and Software
Software agents as a versatile simulation tool to model complex systems
WSEAS Transactions on Information Science and Applications
Using design metrics for predicting system flexibility
FASE'06 Proceedings of the 9th international conference on Fundamental Approaches to Software Engineering
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A new software metric, designed to predict the likelihood that the system will fail to meet its performance goals when the workload is scaled, is introduced. Known as the PNL (Performance Nonscalability Likelihood) metric, it is applied to a study of a large industrial system, and used to predict at what workloads bottlenecks are likely to appear when the presented workload is significantly increased. This allows for intelligent planning in order to minimize disruption of acceptable performance for customers. The case study also outlines our performance testing approach and presents the major steps required to identify current production usage and to assess the software performance under current and future workloads.