Iman Saleh

Formal Specification and Verification of Data-Centric Service Composition

Service-oriented architecture (SOA) promotes a paradigm where ad-hoc applications are built by dynamically linking service-based software capabilities. Service providers follow specification standards to advertise their services’ capabilities and to enable loosely coupled integration between their services and other businesses over the Web. A major challenge in this domain is interpreting the data that must be marshaled between consumer and producer systems. We propose a framework to support formal modeling and contracts for data-centric Web services. We demonstrate how this framework can be used to verify correctness properties for composition of services.

Crowdsourcing, Mixed Elastic Systems and Human-Enhanced Computing–A Survey

State-of-the-art practices have recognized the utility of leveraging human intervention as a crucial aspect of modern computing systems. The emerging crowdsourcing paradigm is based on harnessing human intelligence, effort and rational behaviors to augment computation and analysis. In addition to the crowdsourcing paradigm, new techniques have emerged that incorporate machine and human computational resources together forming a hybrid intelligence when addressing complex problems and tasks. This combined technique is particularly impactful if human and machine contributions can scale automatically in response to their respective efficiency and effectiveness when addressing subsets of a bigger problem – an approach that we have named mixed elastic systems. In this survey, we highlight state-of-the-art projects that investigate crowdsourcing, hybrid intelligence systems and mixed elastic systems. We also present a taxonomy and classification of the broader domain of human-enhanced computing systems as it assimilates crowdsourcing, hybrid intelligence, and mixed elastic systems.

Formal Specification and Verification of Transactional Service Composition

Research in transactions planning has recognized the evolvement of Web Services as an industry standard to implement transactional business processes. We proposed a data modeling and contracting framework for Web services and in this paper we are exploring how our framework can help formally verify data integrity properties in an ad-hoc transaction.

Specification and Verification of Data-Centric Web Services

Data-centric Web services are services whose behavior is determined by their interactions with a repository of stored data. The lack of data specification in current Web service standards potentially leads to erroneous use of these services by their consumers. In this work, we propose using formal data contracts to decrease ambiguity about a service behavior, to fully verify a composition of services, and to guarantee data integrity within a composition of services.

Specification and Verification of Transactional Web Service Composition

Web transactions are formed by integrating Web services in an ad-hoc manner. Distributed transaction protocols may be used to ensure that data integrity is maintained. However, these protocols require coordinated transaction management. Moreover, individual services must be transaction-aware in order to support necessary compensation operations whenever a transaction fails. These assumptions are unrealistic and impractical in the case of Web services that are generic by design and promote a loosely-coupled service integration practices.

Evaluation Using a Deep Web Case Study

We carry an experiment to test the effectiveness of our data model in reducing ambiguity about a Web service behavior. The experiment uses a Web crawling scenario. Our evaluation is based on the observation that the more queries the crawler has to try to retrieve the same set of data records, the more ambiguous the service behavior.

Design-by-Contract for Web Services

Unlike software components operating within an enterprise, the Web services model establishes a loosely coupled relationship between a service producer and a service consumer. Service consumers have little control over services that they employ within their applications. A service is hosted on its provider’s server and is invoked remotely by a consumer over the Web. In such settings, it is important to establish a contract between the service provider and the service consumer. The contract establishes a set of obligations and expectations. These obligations can be functional, specifying the service operations in terms of its pre/postconditions. They can also be non-functional pertaining to legal, security, availability and performance aspects.

Appendix A: The Amazon Item Search Implementation in JML

This appendix contains the Java Modeling Language (JML) version of ItemSeach data model and data contract presented in the book. JML annotations are appended to java code as comments proceeded by the at-sign (@). JML uses a requires clause to specify the client’s obligation (pre-conditions) and an ensures clause to specify the implementer’s obligation (post-conditions). The \result variable denotes the output of a method. A complete reference of the JML syntax can be found in [62].

Appendix B: A Prolog Reasoner

The following code is for a reasoner in Prolog that implements the Amazon ItemSearch service assertions and the Web crawling logic described in Chap. 8. The reasoner produces the total number of possible queries the Web crawler has to try against the Web service given the service specifications. A sample output is provided.

Static Detection of Implementation Errors in Data-Centric Web Services

The experiment described in this chapter is performed to test our hypothesis that our formal model and contracting framework enables detection of programming errors at design time in data-centric Web services. Again, we use mutation testing techniques in order to measure the effectiveness of the data contract attached to services.