The AETG System: An Approach to Testing Based on Combinatorial Design
IEEE Transactions on Software Engineering
Representing Variability in Software Product Lines: A Case Study
SPLC 2 Proceedings of the Second International Conference on Software Product Lines
QoS-Aware Middleware for Web Services Composition
IEEE Transactions on Software Engineering
Software Fault Interactions and Implications for Software Testing
IEEE Transactions on Software Engineering
On Comprehensive Contractual Descriptions of Web Services
EEE '05 Proceedings of the 2005 IEEE International Conference on e-Technology, e-Commerce and e-Service (EEE'05) on e-Technology, e-Commerce and e-Service
An approach for QoS-aware service composition based on genetic algorithms
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Software Abstractions: Logic, Language, and Analysis
Software Abstractions: Logic, Language, and Analysis
Generic semantics of feature diagrams
Computer Networks: The International Journal of Computer and Telecommunications Networking
Search-based testing of service level agreements
Proceedings of the 9th annual conference on Genetic and evolutionary computation
A probabilistic approach to modeling and estimating the QoS of web-services-based workflows
Information Sciences: an International Journal
IEEE Transactions on Software Engineering
Knowledge representation concepts for automated SLA management
Decision Support Systems
Probabilistic QoS and Soft Contracts for Transaction-Based Web Services Orchestrations
IEEE Transactions on Services Computing
PESOS '09 Proceedings of the 2009 ICSE Workshop on Principles of Engineering Service Oriented Systems
Automated and Scalable T-wise Test Case Generation Strategies for Software Product Lines
ICST '10 Proceedings of the 2010 Third International Conference on Software Testing, Verification and Validation
Variability Modeling and QoS Analysis of Web Services Orchestrations
ICWS '10 Proceedings of the 2010 IEEE International Conference on Web Services
Using test cases as contract to ensure service compliance across releases
ICSOC'05 Proceedings of the Third international conference on Service-Oriented Computing
| Hi-index | 0.00 |
Online services encapsulate enterprises, people, software systems and often operate in poorly understood environments. Using such services in tandem to predictably orchestrate a complex task is one of the principal challenges of service-oriented computing. A composite service orchestration soliciting multiple atomic services is plagued by a number of sources of variation. For instance, availability of an atomic service and its response time are two important sources of variation. Moreover, the number of possible variations in a composite service increases exponentially with increase in the number of atomic services. Testing such a composite service presents a crucial challenge as its often very expensive to exhaustively examine the variation space. Can we effectively test the dynamic behavior of a composite service using only a subset of these variations? This is the question that intrigues us. In this paper, we first model composite service variability as a feature diagram (FD) that captures all valid configurations of its orchestration. Second, we apply pairwise testing to sample the set of all possible configurations to obtain a concise subset. Finally, we test the composite service for selected pairwise configurations for a variety of QoS metrics such as response time, data quality, and availability. Using two case studies, Car crash crisis management and eHealth management, we demonstrate that pairwise generation effectively samples the full range of QoS variations in a dynamic orchestration. The pairwise sampling technique eliminates over 99% redundancy in configurations, while still calling all atomic services at least once. We rigorously evaluate pairwise testing for the criteria such as: a) ability to sample the extreme QoS metrics of the service b) stable behavior of the extracted configurations c) compact set of configurations that can help evaluate QoS tradeoffs and d) comparison with random sampling.