Model-Based Performance Prediction in Software Development: A Survey
IEEE Transactions on Software Engineering
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
QEST '05 Proceedings of the Second International Conference on the Quantitative Evaluation of Systems
Quantitative verification: models techniques and tools
Proceedings of the the 6th joint meeting of the European software engineering conference and the ACM SIGSOFT symposium on The foundations of software engineering
Performance Model Estimation and Tracking Using Optimal Filters
IEEE Transactions on Software Engineering
Efficient online monitoring of web-service SLAs
Proceedings of the 16th ACM SIGSOFT International Symposium on Foundations of software engineering
Using quantitative analysis to implement autonomic IT systems
ICSE '09 Proceedings of the 31st International Conference on Software Engineering
Model evolution by run-time parameter adaptation
ICSE '09 Proceedings of the 31st International Conference on Software Engineering
Online Monitoring of Software System Reliability
EDCC '10 Proceedings of the 2010 European Dependable Computing Conference
Dynamic QoS Management and Optimization in Service-Based Systems
IEEE Transactions on Software Engineering
FOCS'10 Proceedings of the 16th Monterey conference on Foundations of computer software: modeling, development, and verification of adaptive systems
Ymer: a statistical model checker
CAV'05 Proceedings of the 17th international conference on Computer Aided Verification
PRISM: a tool for automatic verification of probabilistic systems
TACAS'06 Proceedings of the 12th international conference on Tools and Algorithms for the Construction and Analysis of Systems
FOCS'10 Proceedings of the 16th Monterey conference on Foundations of computer software: modeling, development, and verification of adaptive systems
When the requirements for adaptation and high integrity meet
Proceedings of the 8th workshop on Assurances for self-adaptive systems
Self-adaptive software needs quantitative verification at runtime
Communications of the ACM
Specification and quantitative analysis of probabilistic cloud deployment patterns
HVC'11 Proceedings of the 7th international Haifa Verification conference on Hardware and Software: verification and testing
Integration architecture synthesis for taming uncertainty in the digital space
Proceedings of the 17th Monterey conference on Large-Scale Complex IT Systems: development, operation and management
Compositional reverification of probabilistic safety properties for large-scale complex IT systems
Proceedings of the 17th Monterey conference on Large-Scale Complex IT Systems: development, operation and management
Adaptive model learning for continual verification of non-functional properties
Proceedings of the 5th ACM/SPEC international conference on Performance engineering
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Markovian models are widely used to analyse quality-of-service properties of both system designs and deployed systems. Thanks to the emergence of probabilistic model checkers, this analysis can be performed with high accuracy. However, its usefulness is heavily dependent on how well the model captures the actual behaviour of the analysed system. Our work addresses this problem for a class of Markovian models termed discrete-time Markov chains (DTMCs). We propose a new Bayesian technique for learning the state transition probabilities of DTMCs based on observations of the modelled system. Unlike existing approaches, our technique weighs observations based on their age, to account for the fact that older observations are less relevant than more recent ones. A case study from the area of bioinformatics workflows demonstrates the effectiveness of the technique in scenarios where the model parameters change over time.