Assisted Reuse of Pattern-Based Composition Knowledge for Mashup Development

First generation of the World Wide Web (WWW) enabled users to have instantaneous access to a large diversity of knowledge. Second generation of the WWW (Web 2.0) brought a fundamental change in the way people interact with and through the World Wide Web. Web 2.0 has made the World Wide Web a platform not only for communication and sharing information but also for software development (e.g., web service composition). Web mashup or mashup development is a Web2.0 development approach in which users are expected to create applications by combining multiple data sources, application logic and UI components from the web to cater for their situational application needs. However, in reality creating an even simple mashup application is a complex task that can only be managed by skilled developers. Examples of ready mashup models are one of the main sources of help for users who don't know how to design a mashup, provided that suitable examples can be found (examples that have an analogy with the modeling situation faced by the user). But also tutorials, expert colleagues or friends, and, of course, Google are typical means to find help. However, searching for help does not always lead to a success, and retrieved information is only seldom immediately usable as it is, since the retrieved pieces of information are not contextual, i.e., immediately applicable to the given modeling problem. Motivated by the development challenges faced by a naive user of existing mashup tools, in this thesis we propose toaid such users by enabling assisted reuse of pattern-based composition knowledge. In this thesis we show how it is possible to effectively assist these users in their development task with contextual, interactive recommendations of composition knowledge in the form of mashup model patterns. We study a set of recommendation algorithms with different levels of performance and describe a flexible pattern weaving approach for the one-click reuse of patterns. We prove the generality of our algorithms and approach by implementing two prototype tools for two different mashup platforms. Finally, we validate the usefulness of our assisted development approach by performing thorough empirical tests and two user studies with our prototype tools

Assisted mashup development: On the discovery and recommendation of mashup composition knowledge

Over the past few years, mashup development has been made more accessible with tools such as Yahoo! Pipes that help in making the development task simpler through simplifying technologies. However, mashup development is still a difficult task that requires knowledge about the functionality of web APIs, parameter settings, data mappings, among other development efforts. In this work, we aim at assisting users in the mashup process by recommending development knowledge that comes in the form of reusable composition knowledge. This composition knowledge is harvested from a repository of existing mashup models by mining a set of composition patterns, which are then used for interactively providing composition recommendations while developing the mashup. When the user accepts a recommendation, it is automatically woven into the partial mashup model by applying modeling actions as if they were performed by the user. In order to demonstrate our approach we have implemented Baya, a Firefox plugin for Yahoo! Pipes that shows that it is indeed possible to harvest useful composition patterns from existing mashups, and that we are able to provide complex recommendations that can be automatically woven inside Yahoo! Pipes' web-based mashup editor

Recommendation and weaving of reusable mashup model patterns for assisted development

With this article, we give an answer to one of the open problems of mashup development that users may face when operating a model-driven mashup tool, namely the lack of modeling expertise. Although commonly considered simple applications, mashups can also be complex software artifacts depending on the number and types of Web resources (the components) they integrate. Mashup tools have undoubtedly simplified mashup development, yet the problem is still generally nontrivial and requires intimate knowledge of the components provided by the mashup tool, its underlying mashup paradigm, and of how to apply such to the integration of the components. This knowledge is generally neither intuitive nor standardized across different mashup tools and the consequent lack of modeling expertise affects both skilled programmers and end-user programmers alike. In this article, we show how to effectively assist the users of mashup tools with contextual, interactive recommendations of composition knowledge in the form of reusable mashup model patterns. We design and study three different recommendation algorithms and describe a pattern weaving approach for the one-click reuse of composition knowledge. We report on the implementation of three pattern recommender plugins for different mashup tools and demonstrate via user studies that recommending and weaving contextual mashup model patterns significantly reduces development times in all three cases

Conceptual development of custom, domain-specific mashup platforms

Despite the common claim by mashup platforms that they enable end-users to develop their own software, in practice end-users still don't develop their own mashups, as the highly technical or inexistent user bases of today's mashup platforms testify. The key shortcoming of current platforms is their general-purpose nature, that privileges expressive power over intuitiveness. In our prior work, we have demonstrated that a domainspecific mashup approach, which privileges intuitiveness over expressive power, has much more potential to enable end-user development (EUD). The problem is that developing mashup platforms - domain-specific or not - is complex and time consuming. In addition, domain-specific mashup platforms by their very nature target only a small user basis, that is, the experts of the target domain, which makes their development not sustainable if it is not adequately supported and automated. With this article, we aim to make the development of custom, domain-specific mashup platforms costeffective. We describe a mashup tool development kit (MDK) that is able to automatically generate a mashup platform (comprising custom mashup and component description languages and design-time and runtime environments) from a conceptual design and to provision it as a service. We equip the kit with a dedicated development methodology and demonstrate the applicability and viability of the approach with the help of two case studies. © 2014 ACM

Conceptual design of sound, custom composition languages

Service composition, web mashups, and business process modeling are based on the composition and reuse of existing functionalities, user interfaces, or tasks. Composition tools typically come with their own, purposely built composition languages, based on composition techniques like data flow or control flow, and only with minor distinguishing features-besides the different syntax. Yet, all these composition languages are developed from scratch, without reference specifications (e.g., XML schemas), and by reasoning in terms of low-level language constructs. That is, there is neither reuse nor design support in the development of custom composition languages. We propose a conceptual design technique for the construction of custom composition languages that is based on a generic composition reference model and that fosters reuse. The approach is based on the abstraction of common composition techniques into high-level language features, a set of reference specifications for each feature, and the assembling of features into custom languages by guaranteeing their soundness. We specifically focus on mashup languages

Quality-aware mashup composition: issues, techniques and tools

Web mashups are a new generation of applications based on the composition of ready-to-use, heterogeneous components. In different contexts, ranging from the consumer Web to Enterprise systems, the potential of this new technology is to make users evolve from passive receivers of applications to actors actively involved in the creation of their artifacts, thus accommodating the inherent variability of the users’ needs. Current advances in mashup technologies are good candidates to satisfy this requirement. However, some issues are still largely unexplored. In particular, quality issues specific for this class of applications, and the way they can guide the users in the identification of adequate components and composition patterns, are neglected. This paper discusses quality dimensions that can capture the intrinsic quality of mashup components, as well as the components’ capacity to maximize the quality and the userperceived value of the overall composition. It also proposes an assisted composition process in which quality becomes the driver for recommending to the users how to complete mashups, based on the integration of quality assessment and recommendation techniques within a tool for mashup development

Enhancement of the usability of SOA services for novice users

Recently, the automation of service integration has provided a significant advantage in delivering services to novice users. This art of integrating various services is known as Service Composition and its main purpose is to simplify the development process for web applications and facilitates reuse of services. It is one of the paradigms that enables services to end-users (i.e.service provisioning) through the outsourcing of web contents and it requires users to share and reuse services in more collaborative ways. Most service composers are effective at enabling integration of web contents, but they do not enable universal access across different groups of users. This is because, the currently existing content aggregators require complex interactions in order to create web applications (e.g., Web Service Business Process Execution Language (WS-BPEL)) as a result not all users are able to use such web tools. This trend demands changes in the web tools that end-users use to gain and share information, hence this research uses Mashups as a service composition technique to allow novice users to integrate publicly available Service Oriented Architecture (SOA) services, where there is a minimal active web application development. Mashups being the platforms that integrate disparate web Application Programming Interfaces (APIs) to create user defined web applications; presents a great opportunity for service provisioning. However, their usability for novice users remains invalidated since Mashup tools are not easy to use they require basic programming skills which makes the process of designing and creating Mashups difficult. This is because Mashup tools access heterogeneous web contents using public web APIs and the process of integrating them become complex since web APIs are tailored by different vendors. Moreover, the design of Mashup editors is unnecessary complex; as a result, users do not know where to start when creating Mashups. This research address the gap between Mashup tools and usability by the designing and implementing a semantically enriched Mashup tool to discover, annotate and compose APIs to improve the utilization of SOA services by novice users. The researchers conducted an analysis of the already existing Mashup tools to identify challenges and weaknesses experienced by novice Mashup users. The findings from the requirement analysis formulated the system usability requirements that informed the design and implementation of the proposed Mashup tool. The proposed architecture addressed three layers: composition, annotation and discovery. The researchers developed a simple Mashup tool referred to as soa-Services Provisioner (SerPro) that allowed novice users to create web application flexibly. Its usability and effectiveness was validated. The proposed Mashup tool enhanced the usability of SOA services, since data analysis and results showed that it was usable to novice users by scoring a System Usability Scale (SUS) score of 72.08. Furthermore, this research discusses the research limitations and future work for further improvements

End-User-Oriented Telco Mashups: The OMELETTE Approach

With the success of Web 2.0 we are witnessing a growing number of services and APIs exposed by Telecom, IT and content providers. Targeting the Web community and, in particular, Web application developers, service providers expose capabilities of their infrastructures and applications in order to open new markets and to reach new customer groups. However, due to the complexity of the underlying technologies, the last step, i.e., the consumption and integration of the offered services, is a non-trivial and time-consuming task that is still a prerogative of expert developers. Although many approaches to lower the entry barriers for end users exist, little success has been achieved so far. In this paper, we introduce the OMELETTE project and show how it addresses end-user-oriented telco mashup development. We present the goals of the project, describe its contributions, summarize current results, and describe current and future work