Testing and Quality Assurance for Component-Based Software
Testing and Quality Assurance for Component-Based Software
Research in testing COTS components - built-in testing approaches
AICCSA '05 Proceedings of the ACS/IEEE 2005 International Conference on Computer Systems and Applications
CoCoME - The Common Component Modeling Example
The Common Component Modeling Example
Palladio --- Prediction of Performance Properties
The Common Component Modeling Example
The Palladio component model for model-driven performance prediction
Journal of Systems and Software
The Art of Application Performance Testing: Help for Programmers and Quality Assurance
The Art of Application Performance Testing: Help for Programmers and Quality Assurance
Usage profile and platform independent automated validation of service behavior specifications
Proceedings of the 2nd International Workshop on the Quality of Service-Oriented Software Systems
Software Testing Foundations: A Study Guide for the Certified Tester Exam
Software Testing Foundations: A Study Guide for the Certified Tester Exam
A qos driven development process model for component-based software systems
CBSE'06 Proceedings of the 9th international conference on Component-Based Software Engineering
Decision support via automated metric comparison for the palladio-based performance blame analysis
Proceedings of the 4th ACM/SPEC International Conference on Performance Engineering
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Performance is an important quality attribute for business information systems. When a tester has spotted a performance error, the error is passed to the software developers to fix it. However, in component-based software development the tester has to do blame analysis first, i. e. the tester has to decide, which party is responsible to fix the error. If the error is a design or deployment issue, it can be assigned to the software architect or the system deployer. If the error is specific to a component, it needs to be assigned to the corresponding component developer. An accurate blame analysis is important, because wrong assignments of errors will cause a loss of time and money. Our approach aims at doing blame analysis for performance errors by comparing performance metrics obtained in performance testing and performance prediction. We use performance prediction values as expected values for individual components. For performance prediction we use the Palladio approach. By this means, our approach evaluates each component's performance in a certain test case. If the component performs poorly, its component developer needs to fix the component or the architect replaces the component with a faster one. If no component performs poorly, we can deduce that there is a design or deployment issue and the architecture needs to be changed. In this paper, we present an exemplary blame analysis based on a web shop system. The example shows the feasibility of our approach.