Service-oriented system engineering

Service-Oriented System Engineering (SOSE) is one of the emerging research areas that involves a number of research challenges in engineering service-oriented systems, the architecture and computing paradigm as well as the development and management of service-oriented systems. Service-Oriented Computing (SOC) exploits services as the fundamental elements for developing computer-based systems. It has been applied to various areas and promotes fundamental changes to system architecture, especially changing the way software systems are being analyzed, architected, designed, implemented, tested, evaluated, delivered, consumed, maintained and evolved. The innovations of SOC also offer many interesting avenues of research for scientific and industrial communities. In this paper, we present the concepts of the SOSE from the related work. The motivation, opportunities and challenges of the SOSE is highlighted thereafter. In addition to this, a brief overview of accepted papers in our Special Issue on SOSE is presented. Finally we highlight and summarize this paper.N/

Ontology learning for semantic web services

Semantic Web Services promise automatic service discovery and composition, relying heavily on domain ontology as a core component. With large Web Service repository, manual ontology development is proving a bottleneck (with associated expense and likely errors) to the realisation of a semantic Web of services. Providing the appropriate tools that assist in and automate ontology development is essential for a dynamic service vision to be realised. As a statement of research-in-progress, this paper proposes combining different ontology learning paradigms in Web Services domain, highlighting the need for further research that accommodates the variation in Web Service descriptive and operational sources. A research agenda is proposed that recognises this variation in artefacts as they are selected, pre-processed and analyzed by ontology learning techniques

Cloud based testing of business applications and web services

This paper deals with testing of applications based on the principles of cloud computing. It is aimed to describe options of testing business software in clouds (cloud testing). It identifies the needs for cloud testing tools including multi-layer testing; service level agreement (SLA) based testing, large scale simulation, and on-demand test environment. In a cloud-based model, ICT services are distributed and accessed over networks such as intranet or internet, which offer large data centers deliver on demand, resources as a service, eliminating the need for investments in specific hardware, software, or on data center infrastructure. Businesses can apply those new technologies in the contest of intellectual capital management to lower the cost and increase competitiveness and also earnings. Based on comparison of the testing tools and techniques, the paper further investigates future trend of cloud based testing tools research and development. It is also important to say that this comparison and classification of testing tools describes a new area and it has not yet been done

A data-driven game theoretic strategy for developers in software crowdsourcing: a case study

Crowdsourcing has the advantages of being cost-effective and saving time, which is a typical embodiment of collective wisdom and community workers’ collaborative development. However, this development paradigm of software crowdsourcing has not been used widely. A very important reason is that requesters have limited knowledge about crowd workers’ professional skills and qualities. Another reason is that the crowd workers in the competition cannot get the appropriate reward, which affects their motivation. To solve this problem, this paper proposes a method of maximizing reward based on the crowdsourcing ability of workers, they can choose tasks according to their own abilities to obtain appropriate bonuses. Our method includes two steps: Firstly, it puts forward a method to evaluate the crowd workers’ ability, then it analyzes the intensity of competition for tasks at Topcoder.com—an open community crowdsourcing platform—on the basis of the workers’ crowdsourcing ability; secondly, it follows dynamic programming ideas and builds game models under complete information in different cases, offering a strategy of reward maximization for workers by solving a mixed-strategy Nash equilibrium. This paper employs crowdsourcing data from Topcoder.com to carry out experiments. The experimental results show that the distribution of workers’ crowdsourcing ability is uneven, and to some extent it can show the activity degree of crowdsourcing tasks. Meanwhile, according to the strategy of reward maximization, a crowd worker can get the theoretically maximum reward

Big Data Analytics for QoS Prediction Through Probabilistic Model Checking

As competitiveness increases, being able to guaranting QoS of delivered services is key for business success. It is thus of paramount importance the ability to continuously monitor the workflow providing a service and to timely recognize breaches in the agreed QoS level. The ideal condition would be the possibility to anticipate, thus predict, a breach and operate to avoid it, or at least to mitigate its effects. In this paper we propose a model checking based approach to predict QoS of a formally described process. The continous model checking is enabled by the usage of a parametrized model of the monitored system, where the actual value of parameters is continuously evaluated and updated by means of big data tools. The paper also describes a prototype implementation of the approach and shows its usage in a case study.Comment: EDCC-2014, BIG4CIP-2014, Big Data Analytics, QoS Prediction, Model Checking, SLA compliance monitorin

Microservices Validation: Methodology and Implementation

Due to the wide spread of cloud computing, arises actual question about architecture, design and implementation of cloud applications. The microservice model describes the design and development of loosely coupled cloud applications when computing resources are provided on the basis of automated IaaS and PaaS cloud platforms. Such applications consist of hundreds and thousands of service instances, so automated validation and testing of cloud applications developed on the basis of microservice model is a pressing issue. There are constantly developing new methods of testing both individual microservices and cloud applications at a whole. This article presents our vision of a framework for the validation of the microservice cloud applications, providing an integrated approach for the implementation of various testing methods of such applications, from basic unit tests to continuous stability testing