We apply a model checker to the problem of test generation using a new application of mutation analysis. We define syntactic operators, each of which produces a slight variation on a given model. The operators define a form of mutation analysis at the level of the model checker specification. A model checker generates countersamples which distinguish the variations from the original specification. The countersamples can easily be turned into complete test cases, that is, with inputs and expected results. We define two classes of operators: those that produce test cases from which a correct implementation must differ, and those that produce test cases with which it must agree. There are substantial advantages to combining a model checker with mutation analysis. First, test case generation is automatic; each countersample is a complete test case. Second, in sharp contrast to program-based mutation analysis, equivalent mutant identification is also automatic. We apply our method to an example specification and evaluate the resulting test sets with coverage metrics on a Java implementation.

Using Model Checking to Generate Tests from Specifications | NIST

An agility-oriented and fuzziness-embedded semantic model for collaborative cloud service search, retrieval and recommendation

Context:
Testing is a key concern when developing process-oriented solutions as it supports modeling experts who have 
to deal with increasingly complex models and scenarios such as cross-organizational processes. However, the complexity 
of the research landscape and the diverse set of approaches and goals impedes the analysis and advancement of research 
and the identification of promising research areas, challenges, and research directions. Hence, a comprehensive and systematic 
review that covers state of the art research in the process model testing domain is required.
Objective:
The objective is to analyze process model testing approaches to identify and present, connected research domains and the used terminology. Additionally, research challenges, gaps, and future research directions are identified and discussed.
Method:
A systematic literature review is conducted to identify interesting areas for future research and to provide an 
overview of existing work. Over 6300 potentially matching publications were determined during the search (literature 
databases, selected conferences/journals, and snowballing). Finally, 153 publications from 2002 to 2013 were 
selected, analyzed, and classified.
Results:
It was found that the software engineering domain has influenced process model testing approaches (e.g., regarding 
terminology and concepts), but recent publications are presenting independent approaches. Additionally, historical data 
sources are not exploited to their full potential and current testing related publications frequently contain 
evaluations of relatively weak quality. Overall, the publication landscape is unevenly distributed so that over 31 
publications concentrate on test-case generation but only 4 publications conduct performance test. Hence, the full potential 
of such insufficiently covered testing areas is not exploited.
Conclusion:
This systematic review provides a comprehensive overview of the interdisciplinary topic of process model testing. 
Several open research questions are identified, for example, how to apply testing to cross-organizational or legacy 
processes and how to adequately include users into the testing methods.

A systematic literature review on process model testing: Approaches, challenges, and research directions

Testing of web service orchestrations brings new challenges to developers of Service-Oriented Applications (SOA) due to their dynamic nature and missing control over underlying infrastructure. The current testing approaches and tools cover single testing activities such as test path analysis, test case generation, web service emulation, fault injection, etc. There is still a lack of solutions that provide complete testing of such applications. In order to fill this gap, this paper proposes a framework, called Testing as a Service Software Architecture (TASSA), for testing web service orchestrations, described with Business Process Execution Language for Web Services (WS-BPEL). It automates a complete set of activities for design time testing of functional and non-functional behavior of composed web services. The feasibility of the framework is proved through a case study that demonstrates its features while testing a sample business process.

TASSA: testing framework for web service orchestrations

Evolution pattern will be defined as an Xml Schema document, the generation of pattern aspect is the process of generating xml instance from its related Xml Schema definition document. The process can be iterative until all the evolution requirement carried by the specific evolution feature has been realized by each evolution pattern aspect (Model Driven Architecture).

Evolution Feature Oriented Model Driven Product Line Engineering Approach for Synergistic and Dynamic Service Evolution in Clouds: Pattern Data Structure

With the rapid increase of Web Service applications, the reliability of web service and service composition has drawn particular attention from researchers and industries. Many methods for testing and verifying the reliability have been discussed, however, the existing methods are weak in test automation and therefore difficult in tackling the dynamic features of modern SOA based application. The traditional method of model checking and the technique of test suite generation have a large potential for the reliability verification of web services and service composition. In this paper, an approach to integrating the test suite generation technique with model checking is presented. The approach takes advantage of model checking to verify BPEL script at the logical level, and to generate test suite automatically based on the model description, and finally to select test cases with respect to the counterexamples of model checking output. The approach contributes a set of algorithms and its implementation to support a translation from BPEL to LOTOS, and LTS(Labeled Transition Systems, LTS in short) to TTCN(Test and Testing Control Notation, TTCN in short) behavior Tree. Finally, a case study is presented to demonstrate and verify the proposed approach.

A Model Checking Based Approach to Automatic Test Suite Generation for Testing Web Services and BPEL

Protecting user's privacy is one of the main concerns for the deployment of pervasive computing systems in the real world. In pervasive environments, the user context information is naturally distributed among different spatial or logical domains. Many efforts have been done to match the service privacy policy with the user's privacy preferences. However, since the pervasive environments are characterized by a large number of available services as well as a large amount of context information, the privacy protection mechanism poses two main requirements. Firstly, policies are created on a per task basis. We argue here that specifying the privacy on a per domain basis facilitates specifying the privacy preferences for the user. Secondly, to ease specifying the user' privacy preferences, an intuitive mechanisms to specifying the context information that can be consumed by services are thus needed. In this paper, and in order to bridge the gap of the context information perception by the developers and by the users, we propose to represent the available context information in each domain as a feature model. In this way, the developers are able to configure this feature model to get the context information they need, the users can easily specify the context features they are willing to share. The result is a domain-oriented user-centric privacy protection scheme.

Lightweight Software Product Line Based Privacy Protection Scheme for Pervasive Applications

This paper defines the data label, data portrait, and data portrait causal model, which proves the equivalence between the data portrait causal model and the Bayesian network model. The causal model of constructing data portraits and user behavior prediction algorithm are proposed to verify the effectiveness of the proposed model and algorithm.

Purchasing Behavior Analysis Based on Customer's Data Portrait Model

Cloud Computing introduces a revolutionary paradigm of computing to Service Oriented Architecture (SOA), by provisioning various types of computational resources and applications as on-demand services. While presenting cloud services semantically using Web Ontology Language (OWL) based techniques, we experience a series of difficulties due to the vagueness of the novel cloud computing specifications, concepts, meanings, etc. Fuzzy extension of OWL 2 has been a widely discussed topic. In this paper, we present a different solution by considering three new OWL 2 based fuzzy scenarios: subsumption, restriction and axiom value fuzziness. With proper use of OWL 2 updates, a series of unique and categorized weight datatype domains are developed to present the above fuzziness. Our approach does not introduce new syntax, nor is it relying on OWL 2 annotations. Therefore, there will not be inconsistency or incompatibility incurred. In the experiment of fuzzy cloud service ontology, the approach proves to be effortless and successful, where simple reasoning and queries can be effectively handled by all OWL 2 compatible Description Logic (DL) reasoners.

Towards OWL 2 Natively Supported Fuzzy Cloud Ontology

In pervasive systems, e.g., smart homes and smart vehicles, users will be surrounded by many mobile devices and sensors embedded everywhere in the systems which will cooperate together to provide a context-aware pervasive environment that supports humans in everyday activities, e.g., in business, health care, or education. In this respect, the users will enjoy a new experience in a non-obtrusive way as the existing infrastructures will be more proactive and dynamically adaptable to the current situations, user preferences and environmental context in a less intrusive way (Weiser, 1991). Context-awareness refers to the capability of an application or a service being aware of its physical environment or situation (e.g. context) and to respond proactively and intelligently based on this awareness (Baldauf et al., 2007). We define context-aware service adaptation as the action that modifies the service in a way that causes its behaviour to evolve according to the evolution of business and user requirements, and the context considered relevant to that service. Currently, despite the active research into and the development of services over the last several years, context-aware services are still difficult to build for the following reasons. Firstly, current service development standards such as Business Service Execution Language (BPEL), are not sufficient for describing and handling context information (Sheng et al., 2010). Secondly, service engineers usually implement everything related to context management, including acquiring, dissemination, and usage of context information, in an ad hoc manner. Moreover, the mobility of users and devices across different context domains (areas) induces changes to the application operating context and makes the development and evolution of services more difficult. In particular, we argue here that context information relevant to the current task at hand may come from a number of spatial domains. For instance, a dynamic recalculation of the quickest routes for a trip involves acquiring the latest contextual information such as traffic congestion from remote sources. We can imagine a domain-oriented context management system where the context information available in each domain is managed by a separate context manager. While moving, the user roams across the domains. In addition, each domain may maintain its own sensors and mechanisms for inferring context related to this user. To tackle the above challenge, consequently, collaborative context management across domains is needed. Finally, services should be dependable in the sense that it should meet the user and business requirements and needs, which are highly changeable all the time in pervasive systems. Therefore, service modelling must be flexible enough to deal with these constant changes – both at the business level (e.g. evolving business rules) and at the technical level (e.g. contextual information and platform upgrades). As services get deployed on Xiaodong Liu Edinburgh Napier University, UK

Huiqun Zhao

Papers

A Model Checking Based Approach to Automatic Test Suite Generation for Testing Web Services and BPEL

Lightweight Software Product Line Based Privacy Protection Scheme for Pervasive Applications

Purchasing Behavior Analysis Based on Customer's Data Portrait Model

Towards OWL 2 Natively Supported Fuzzy Cloud Ontology

A Unified Platform for the Dynamic Evolution of Context-Aware Highly Agile Services.