Fuguo Wei

Deriving Artefact-Centric Interfaces for Overloaded Web Services

We present a novel framework and algorithms for the analysis of Web service interfaces to improve the efficiency of application integration in wide-spanning business networks. Our approach addresses the notorious issue of large and overloaded operational signatures, which are becoming increasingly prevalent on the Internet and being opened up for third-party service aggregation. Extending upon existing techniques used to refactor service interfaces based on derived artefacts of applications, namely business entities, we propose heuristics for deriving relations between business entities, and in turn, deriving permissible orders in which operations are invoked. As a result, service operations are refactored on business entity CRUD which then leads to behavioural protocols generated, thus supportive of fine-grained and flexible service discovery, composition and interaction. A prototypical implementation and analysis of web services, including those of commercial logistic systems (Fedex), are used to validate the algorithms and open up further insights into service interface synthesis.

Discovering Behavioural Interfaces for Overloaded Web Services

The growth of APIs and Web services on the Internet, especially through larger enterprise systems increasingly being leveraged for Cloud and software-as-a-service opportunities, poses challenges to improving the efficiency of integration with these services. Interfaces of enterprise systems are typically larger, more complex and overloaded, with single operation having multiple data entities and parameter sets, supporting varying requests, and reflecting versioning across different system releases, compared to fine-grained operations of contemporary interfaces. We propose a technique to support the refactoring of service interfaces by deriving business entities and their relationships. In this paper, we focus on the behavioural aspects of service interfaces, aiming to discover the sequential dependencies of operations (otherwise known as protocol extraction) based on the entities and relationships derived. Specifically, we propose heuristics according to these relationships, and in turn, deriving permissible orders in which operations are invoked. As a result of this, service operations can be refactored on business entity CRUD lines, with explicit behavioural protocols as part of an interface definition. This supports flexible service discovery, composition and integration. A prototypical implementation and analysis of existing Web services, including those of commercial logistic systems (Fedex), are used to validate the algorithms proposed through the paper.

A likelihood-free Bayesian derivation method for service variants

Abstract Application programming interfaces (API), allowing systems to be accessed by the services they expose, have proliferated on the Internet and gained strategic interest in the IT industry. However, integration opportunities for larger, enterprise systems are hampered by complex and overloaded operations of their interfaces, having hundreds of parameters and multiple levels of nesting, corresponding to multiple business entities. Static (code) analysis techniques have been proposed to analyse service interfaces of enterprise systems. They support the derivation of business entities and relationships from the parameters of interface operations, allowing the restructure of operations, based on individual entities. In this paper, we extend the repertoire of static interface analysis to derive service variants, whereby subsets of operation parameters correspond to multiple nested business entity subtypes of variants. Specifically, we apply a Monte Carlo sampling method, based on likelihood-free Bayesian sampling, to traverse large parameter spaces, based on higher probabilistic tree search, to efficiently find subsets of parameters related to prospective subtypes. The results demonstrate a method with significant success rates in massive search spaces, as applied to the FedEx Shipment interface whose operations have in excess of 1000 parameters.

Efficient Service Variant Analysis with Markov Updates in Monte Carlo Tree Search (Short Paper).

Static analysis techniques can be used to analyse and simplify interfaces of enterprise systems, such as those from SAP, Oracle and FedEx, which becoming more prominent on the internet and vying for new systems integration and extension opportunities. Web services of enterprise systems are notoriously complex, having hundreds of parameters per operation, multiple levels of nesting, leading to ambiguities about valid invocations of operations. To derive valid invocations, which in turn assists service users with invoking services correctly, this paper focuses on a challenging aspect of static interface analysis, namely, the identification of service variants in operations, in which the parameters are subtypes of business entities involved in a service. To efficiently search for which combinations of parameters are for a valid invocation, we have proposed a Monte Carlo method, based on likelihood-free Bayesian sampling, to identify higher probability parameters spaces, from which to test prospective invocations. A significant performance boost was found by extending Monte Carlo sampling with Markov look-up, with validation using a simulated FedEx service interface, whose structural complexity exceeds many web services of enterprise systems available on the internet.

Service Interface Synthesis in Business Networks

We propose a framework to allow the analysis of service interfaces, useful for interoperability in heterogeneous settings such as business networks. The framework supports analysis of large and overloaded operational signatures to derive focal artefacts, namely the underlying business objects of services. A more simplified and comprehensive service interface layer is created based on these, and rendered into semantically normalised interfaces, given an ontology accrued through the framework from service analysis history. This opens up the prospect of supporting capability comparisons across services, and run-time request backtracking and adjustment, as consumers discover new features of a service’s operations through corresponding features of similar services. This paper provides a first exposition of the service interface synthesis framework, describing algorithms for business object derivation and service behavioural interface generation. A prototypical implementation and analysis of web services drawn from commercial logistic systems are used to validate the algorithms and identify open challenges and future research directions.