Principles of multivariate analysis: a user's perspective
Principles of multivariate analysis: a user's perspective
Software architecture: perspectives on an emerging discipline
Software architecture: perspectives on an emerging discipline
SAAM: a method for analyzing the properties of software architectures
ICSE '94 Proceedings of the 16th international conference on Software engineering
Designing Process Replication and Activation: A Quantitative Approach
IEEE Transactions on Software Engineering
The 4+1 View Model of Architecture
IEEE Software
A survey on software architecture analysis methods
IEEE Transactions on Software Engineering
Preliminary guidelines for empirical research in software engineering
IEEE Transactions on Software Engineering
Quality Models to Design Software Architectures
TOOLS '01 Proceedings of the Technology of Object-Oriented Languages and Systems
Scenario-Based Software Architecture Reengineering
ICSR '98 Proceedings of the 5th International Conference on Software Reuse
Experimenting different software architectures performance techniques: a case study
WOSP '04 Proceedings of the 4th international workshop on Software and performance
Model-Based Performance Prediction in Software Development: A Survey
IEEE Transactions on Software Engineering
Discovering Statistics Using SPSS
Discovering Statistics Using SPSS
Predictability by construction
OOPSLA '05 Companion to the 20th annual ACM SIGPLAN conference on Object-oriented programming, systems, languages, and applications
Customized Benchmark Generation Using MDA
WICSA '05 Proceedings of the 5th Working IEEE/IFIP Conference on Software Architecture
Identifying "good" architectural design alternatives with multi-objective optimization strategies
Proceedings of the 28th international conference on Software engineering
Essential Software Architecture
Essential Software Architecture
Concurrency and Computation: Practice & Experience
Model-Driven Software Development: Technology, Engineering, Management
Model-Driven Software Development: Technology, Engineering, Management
Enterprise JavaBeans 3.0 (5th Edition)
Enterprise JavaBeans 3.0 (5th Edition)
A holistic architecture assessment method for software product lines
Information and Software Technology
Early quality prediction of component-based systems - A generic framework
Journal of Systems and Software
Model-Driven Generation of Performance Prototypes
SIPEW '08 Proceedings of the SPEC international workshop on Performance Evaluation: Metrics, Models and Benchmarks
Characterizing software architecture changes: A systematic review
Information and Software Technology
Synthetic Metrics for Evaluating Runtime Quality of Software Architectures with Complex Tradeoffs
SEAA '09 Proceedings of the 2009 35th Euromicro Conference on Software Engineering and Advanced Applications
Introduction to overlapping attributes
Dependability metrics
Exploring quality attributes using architectural prototyping
QoSA'05 Proceedings of the First international conference on Quality of Software Architectures and Software Quality, and Proceedings of the Second International conference on Software Quality
Architecting Dependable Systems III
Model checking and code generation for transaction processing software
Concurrency and Computation: Practice & Experience
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Context: Architecture is fundamental for fulfilling requirements related to the non-functional behavior of a software system such as the quality requirement that response time does not degrade to a point where it is noticeable. Approaches like the Architecture Tradeoff Analysis Method (ATAM) combine qualitative analysis heuristics (e.g. scenarios) for one or more quality metrics with quantitative analyses. A quantitative analysis evaluates a single metric such as response time. However, since quality metrics interact with each other, a change in the architecture can affect unpredictably multiple quality metrics. Objective: This paper introduces a quantitative method that determines the impact of a design change on multiple metrics, thus reducing the risks in architecture design. As a proof of concept, the method is applied on a simulation model of transaction processing in client server architecture. Method: Factor analysis is used to unveil latent (i.e. not directly measurable) quality features represented by new variables that reflect architecture-specific correlations between metrics. Separate Analyses of Variance (ANOVA) are then applied to these variables, for interpreting the tradeoffs detected by factor analysis in terms of the quantified metrics. Results: The results for the examined transaction processing architecture show three latent quality features, the corresponding groups of strongly correlated quality metrics and the impact of architecture characteristics on the latent quality features. Conclusion: The proposed method is a systematic way for relating the variability of quality metrics and the implied tradeoffs to specific architecture characteristics.