Software reliability: measurement, prediction, application
Software reliability: measurement, prediction, application
Handbook of software reliability engineering
Handbook of software reliability engineering
Stutter-invariant temporal properties are expressible without the next-time operator
Information Processing Letters
Property specification patterns for finite-state verification
FMSP '98 Proceedings of the second workshop on Formal methods in software practice
Architecture-based approach to reliability assessment of software systems
Performance Evaluation
Reliability prediction for component-based software architectures
Journal of Systems and Software - Special issue on: Software architecture - Engineering quality attributes
Assessing Uncertainty in Reliability of Component-Based Software Systems
ISSRE '03 Proceedings of the 14th International Symposium on Software Reliability Engineering
Quantifying the Variance in Application Reliability
PRDC '04 Proceedings of the 10th IEEE Pacific Rim International Symposium on Dependable Computing (PRDC'04)
Architecture-Based Software Reliability Analysis: Overview and Limitations
IEEE Transactions on Dependable and Secure Computing
Probabilistic Model-Checking Support for FMEA
QEST '07 Proceedings of the Fourth International Conference on Quantitative Evaluation of Systems
A User-Oriented Software Reliability Model
IEEE Transactions on Software Engineering
Principles of Model Checking (Representation and Mind Series)
Principles of Model Checking (Representation and Mind Series)
CoCoME - The Common Component Modeling Example
The Common Component Modeling Example
ProbDiVinE-MC: Multi-core LTL Model Checker for Probabilistic Systems
QEST '08 Proceedings of the 2008 Fifth International Conference on Quantitative Evaluation of Systems
Quality Prediction of Service Compositions through Probabilistic Model Checking
QoSA '08 Proceedings of the 4th International Conference on Quality of Software-Architectures: Models and Architectures
PRISM: probabilistic model checking for performance and reliability analysis
ACM SIGMETRICS Performance Evaluation Review
A classification and comparison of model checking software architecture techniques
Journal of Systems and Software
Importance measures for modular software with uncertain parameters
Software Testing, Verification & Reliability
A Bayesian model for predicting reliability of software systems at the architectural level
QoSA'07 Proceedings of the Quality of software architectures 3rd international conference on Software architectures, components, and applications
Performance evaluation of component-based software systems: A survey
Performance Evaluation
Architecture-based reliability evaluation under uncertainty
Proceedings of the joint ACM SIGSOFT conference -- QoSA and ACM SIGSOFT symposium -- ISARCS on Quality of software architectures -- QoSA and architecting critical systems -- ISARCS
Assessing reliability of modular software
Operations Research Letters
Architecture-Based Reliability Prediction with the Palladio Component Model
IEEE Transactions on Software Engineering
Towards mining informal online data to guide component-reuse decisions
Proceedings of the 16th International ACM Sigsoft symposium on Component-based software engineering
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Engineering of highly reliable systems requires support of sophisticated design methods allowing software architects to competently decide between various design alternatives already early in the development process. Architecture-based reliability prediction provides such capability. The formalisms and analytical methods employed by existing approaches are however often limited to a single reliability measure (the probability of failure on demand) and consideration of behavioural uncertainty (focusing on the uncertainty in model parameters, not the behaviour itself). This paper presents a formal reliability assessment approach for component-based systems based on the probabilistic model checking of various reliability-related properties specified in probabilistic linear temporal logic (PLTL). The systems are formalized as Markov decision processes (MDP), which allows software architects to encode behavioural uncertainties into the models in terms of nondeterministic (scheduler-decided) choices in the MDP.