JWE Abstracts 

Vol.13 No.3&4 July 1, 2014

Component-Based, Client-Oriented Web Engineering:
 Issues, Advancements and Opportunities

Editorial (pp181-182)
Florian Daniel, Peter Dolog, and Qing Li
Component-based Web Engineering using Shared Components and Connectors
Stefania Leone, Alexandre de Spindler, Moira C. Norrie, and Dennis McLeod
Today, web development platforms often follow a modular architecture that enables platform extension. Popular web development frameworks such as Ruby on Rails and Symfony, as well as content management systems (CMS) such as WordPress and Drupal offer extension mechanisms that allow the platform core to be extended with additional functionality. However, such extensions are typically isolated units defining their own data structures, application logic and user interfaces, and are difficult to combine. We address the fact that applications need to be configured more freely through the composition of such extensions. We present an approach and model for component-based web engineering based on the concept of components and connectors between them, supporting composition at the level of the schema and data, the application logic and the user interface. We have realised our approach in two popular web development settings. First, we demonstrate how our approach can be integrated into web development frameworks, thus bringing component-based web engineering to the developer. Second, we present, based on the example of WordPress, how advanced end-users can be supported in component-based web engineering by integrating our approach into CMS. The applicability of our approach in both settings demonstrates its generality.

DireWolf Framework for Widget-based Distributed User Interfaces (pp203-222)
Dejan Kovachev, Dominik Renzel, Petru Nicolaescu, Istvan Koren, and Ralf Klamma
Web applications have overcome traditional desktop applications especially in collaborative settings. However, the bulk of Web applications still follow the ``single user on a single device'' computing model. Therefore, we created the DireWolf framework for rich Web applications with distributed user interfaces (DUIs) over a federation of heterogeneous commodity devices supporting modern Web browsers such as laptops, smart phones and tablet computers. The DUIs are based on widget technology coupled with cross-platform inter-widget communication (IWC) and seamless session mobility. Inter-widget communication technologies connect the widgets and enable real-time collaborative applications as well as runtime migration in our framework. We show that the DireWolf framework facilitates the use case of DUI-enabled semantic video annotation. For a single user it provides more flexible control over different parts of an application by enabling the simultaneous use of smart phones, tablets and computers. We conducted a technical evaluation and two user studies to validate the DireWolf approach. The work presented opens the way for creating distributed Web applications which can access device specific functionalities such as multi-touch, text input, etc. in a federated and usable manner. In this paper, we also sketch our ongoing work to integrate the WebRTC API into DireWolf, where we see opportunities for potential adoption of DUI Web applications by the majority of Web users.

Efficient Development of Progressively Enhanced Web Applications by  Sharing Presentation and Business Logic Between Server and Client (pp223-242)
Markus Ast, Stefan Wild, and Martin Gaedke
A Web application's codebase is typically divided into a server side and a client side with essential functionalities being implemented twice, such as validation or rendering. While developers can choose from a rich set of programming languages to implement a Web application's server side, they are bound to JavaScript for the client side. Recent developments like Node.js allow using JavaScript in a simple and efficient way also on the server side, but lack offering a common codebase for the entire Web application. In this article, we present the SWAC approach that aims at reducing development efforts and minimizing coding errors in order to make creating Web applications more efficiently. Based on our approach, we created the SWAC framework. It enables establishing a unified Web application codebase that provides both dynamic functionality and progressive enhancement by taking characteristic differences between server and client into account.

Model-Based Rich Internet Applications Crawling: "Menu" and "Probability" Models (pp243-262)
Suryakant Choudhary, Emre Dincturk, Seyed Mirtaheri, Ggregor v. Bochmann, Guy-Vincent Jourdan, and Iosif Viorel Onut
Strategies for ``crawling'' Web sites efficiently have been described more than a decade ago. Since then, Web applications have come a long way both in terms of adoption to provide information and services and in terms of technologies to develop them. With the emergence of richer and more advanced technologies such as AJAX, ``Rich Internet Applications'' (RIAs) have become more interactive, more responsive and generally more user friendly. Unfortunately, we have also lost our ability to crawl them. Building models of applications automatically is important not only for indexing content, but also to do automated testing, automated security assessments, automated accessibility assessment and in general to use software engineering tools. We must regain our ability to efficiently construct models for these RIAs. In this paper, we present two methods, based on ``Model-Based Crawling'' (MBC) first introduced in \cite{ICWE2011}: the ``menu'' model and the ``probability'' model. These two methods are shown to be more effective at extracting models than previously published methods, and are much simpler to implement than previous models for MBC. A distributed implementation of the probability model is also discussed. We compare these methods and others against a set of experimental and ``real" RIAs, showing that in our experiments, these methods find the set of client states faster than other approaches, and often finish the crawl faster as well.

Other Research Articles:

An Improved Ant Colony Algorithm for Effective Mining of Frequent Items (pp263-276)
Suriya Sundaramoorthy and S.P. Shantharajah
Data Mining involves discovery of required potentially qualified content from a heavy collection of heterogeneous data sources. Two decades passed, still it remains the interested area for researchers. It has become a flexible platform for mining engineers to analyse and visualize the hidden relationships among the data sources. Association rules have a strong place in representing those relationships by framing suitable rules. It has two powerful parameters namely support and confidence which helps to carry out framing of such rules. Frequent itemset mining is also termed to be frequent pattern mining. When the combination of items increases rapidly, we term it to be a pattern. The ultimate goal is to design rules over such frequent patterns in an effective manner i.e in terms of time complexity and space complexity. The count of evolutionary algorithms to achieve this goal is increasing day by day. Bio Inspired algorithms holds a strong place in machine learning, mining, evolutionary computing and so on. Ant Colony Algorithm is one such algorithm which is designed based on behaviour of biological inspired ants. This algorithm is adopted for its characteristic of parallel search and dynamic memory allocation. It works comparatively faster than basic Apriori algorithm, AIS, FP Growth algorithm. The two major parameters of this algorithm are pheromone updating rule and transition probability. The basic ant colony algorithm is improved by modifying the pheromone updating rule in such way to reduce multiple scan over data storage and reduced count of candidate sets. The proposed approach was tested using MATLAB along with WEKA toolkit. The experimental results prove that the stigmeric communication of improved ant colony algorithm helps in mining the frequent items faster and effectively than the above stated existing algorithms.

Improving Search and Exploration in Tag Spaces Using Automated Tag Clustering(pp277-301)
Joni Radelaar, Aart-Jan Boor, Damir Vandic, Jan-Willem van Dam, and Flavius Fasincar
In recent years we have experienced an increase in the usage of tags to describe resources. However, the free nature of tagging presents some challenges regarding the search and exploration of tag spaces. In order to deal with these challenges we propose the Semantic Tag Clustering Search (STCS) framework. The framework first groups syntactic variations using several measures based on the Levenshtein distance and the cosine similarity based on tag co-occurrences. We find that a measure that combines the newly introduced variable cost Levenshtein similarity measure with the cosine similarity significantly outperforms the other methods we evaluated in terms of precision. After grouping syntactic variations, the framework clusters semantically related tags using the cosine similarity based on tag co-occurrences. We compare the STCS framework to a state-of-the-art clustering technique and find that the STCS framework performs significantly better in terms of precision. For the evaluation we used a large data set gathered from Flickr, which contains all the pictures uploaded in the year 2009.

A Conceptual Cohesion Metric for Service Oriented Systems (pp302-332)
Ali Kazemi, Ali Rostampour, Hassan Haghighi, and Sahel Abbasi
Service conceptual cohesion has an incredible impact on the reusability and maintainability of service-oriented software systems. Conceptual cohesion indicates the degree of focus of services on a single business functionality. Current metrics for measuring service cohesion reflect the structural aspect of cohesion and therefore cannot be utilized to measure conceptual cohesion of services. Latent Semantic Indexing (LSI), on the other hand, is an information retrieval technique widely used to measure the degree of similarity between a set of text based documents. In our previous work, a metric, namely SCD (Service Cohesion Degree), has been proposed that measures conceptual cohesion of services based on the LSI technique. SCD provides a quantitative evaluation to measure how much a service concentrates on a single business functionality. In addition, SCD is applied in the service identification step, i.e., when services are not yet available, and the designer plans for developing services with high cohesion. This paper has two contributions in comparison to our previous work. At first, it resolves two anomalies occurring in our previous method when calculating conceptual relationship between service operations. Secondly, as the main contribution of the paper, it presents details of a theoretical validation and an empirical evaluation of SCD. By using a small-scale controlled study, the empirical evaluation demonstrates that SCD could measure conceptual cohesion of services acceptably.

Webpage Clustering – Taking the Zero Step: a Case Study of an Iranian Website (pp333-360)
Abbas Keramati and Ruholla Jafari-Marandi
The expansion of websites and their too many pages not only have pushed their visitors to frustration but also have made the websites ever more difficult to be managed and controlled by their owners. In the past few years data mining (clustering) has been of great help so as to assist website’s owner to address the complexities related to owners’ extracting their visitor’s preferences and their coming to know their websites properly. In this line of literature, this paper contains several parts and features. First, with regard to the fact that SOM has been the popular algorithm in dealing with page clustering, a comparison between SOM and K-means (another popular clustering algorithm) were performed to show the superiority of SOM in dealing with the task of webpage clustering. Second, due to the clustering tasks’ complication not being able to be tested (unlike Classification), this study aims at proposing a mind-set by which one before taking any other actions has to go through some steps in order to choose the best set of data. Thirdly, looking at the literature, one can see the question about the suitability of types of data (content, structure and usage) and the task they are being used for has never been raised. Using an Iranian website’s data, a field study and SOM algorithm, we presented that the popular belief about the type of data and the task they are appropriate for should be open to doubt. It was also depicted that different sets of data in two chosen tasks – webpage profiling and extracting visitors’ preference - can influence the results tremendously. Last but not least, apart from observing the influence of different sets of data, both data mining tasks have been performed to the end and the results are presented in the paper. Additionally, using the second clustering task’s results (the extraction of visitors’ preferences) a novel recommendation system is presented. The recommendation system in question was installed in the website for more than a month and its influence on the whole website is observed and analysed.

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