Web Engineering for Workflow-based Applications: Models, Systems and Methodologies

This dissertation presents novel solutions for the construction of Workflow-based Web applications: The Web Engineering DSL Framework, a stakeholder-oriented Web Engineering methodology based on Domain-Specific Languages; the Workflow DSL for the efficient engineering of Web-based Workflows with strong stakeholder involvement; the Dialog DSL for the usability-oriented development of advanced Web-based dialogs; the Web Engineering Reuse Sphere enabling holistic, stakeholder-oriented reuse

Web Data Extraction, Applications and Techniques: A Survey

Web Data Extraction is an important problem that has been studied by means of different scientific tools and in a broad range of applications. Many approaches to extracting data from the Web have been designed to solve specific problems and operate in ad-hoc domains. Other approaches, instead, heavily reuse techniques and algorithms developed in the field of Information Extraction. This survey aims at providing a structured and comprehensive overview of the literature in the field of Web Data Extraction. We provided a simple classification framework in which existing Web Data Extraction applications are grouped into two main classes, namely applications at the Enterprise level and at the Social Web level. At the Enterprise level, Web Data Extraction techniques emerge as a key tool to perform data analysis in Business and Competitive Intelligence systems as well as for business process re-engineering. At the Social Web level, Web Data Extraction techniques allow to gather a large amount of structured data continuously generated and disseminated by Web 2.0, Social Media and Online Social Network users and this offers unprecedented opportunities to analyze human behavior at a very large scale. We discuss also the potential of cross-fertilization, i.e., on the possibility of re-using Web Data Extraction techniques originally designed to work in a given domain, in other domains.Comment: Knowledge-based System

Comparative analysis of software reusability attributes in web and mobile applications

Software reuse is an important approach to software engineering, where it aims to use previous software components to create new software systems. Reusability minimizes work repetition, development time, cost, efforts, and increases systems reliability. Reusability measurements help developers to provide the right metrics for measuring the reusability attributes and to identify reusable components among the wealth of existing programs. The main problem encountered in software reuse is the proper selection of the right software component for reuse due to similarity between the desired functionality and the function of the retrieved software component. In addition, it is difficult to define the right metrics that capture important quality attributes of a given class. This research aims to identify and measure the attributes that affect the software components reusability in two open source web and mobile applications. It also aims to compare the usage rate of reusability components in these applications to decide their ability to reuse. Four attributes were selected due to their impacts on reusability namely flexibility, portability, variability and understandability. Five metrics were identified to measure these attributes based on specified formulas. The metrics are Coupling Between Object (CBO), Lack Of Cohesion (LCOM), Depth Of Inheritance (DIT), Number Of Children (NOC) and Line Of Code (LOC). The research results indicate that the same attributes and metrics are suitable for measuring the reusability components in both applications. The comparison between the two applications for reuse indicates that the web application is more difficult for reuse than the mobile application

Towards increasing web application development productivity through object-oriented framework

Software development remains complex, expensive and risky.Thus, the need for reusability has become obvious.Through reusability web developers/engineers can save countless hours and millions of dollars in development cost. Object-oriented (OO) framework mechanism provides a new vehicle for reuse and enables web engineers to customize or reuse various aspects in web engineering such as customizing one or more elements of user interface, automatically generate event handlers, data handlers or related data elements based on changes made by them.The OO framework mechanism includes tags and scripts that predefine some generic web application activities and a common programming interface for generating a framework customization environment. This study provides a novel solution to produce high quality web applications within a shortest development timeframe through the means of customization, reusability, extensibility and flexibility.At the end, this study will conduct a comprehensive evaluation on the proposed OO framework. Building on previous works, this study emphasized the reuse of design, code and testing as a tool to uncover strengths and weaknesses of the OO framework for dynamic web engineering

ArchiTech: tool support for NFR-guided architectural decision-making

© 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Researchers from requirements engineering and software architecture had emphasized the importance of NonFunctional Requirements and their influence in the architectural design process. To improve this process we have designed a tool, ArchiTech, which aims to support architects during the design process by suggesting alternative architectural decisions that can improve some types of non-functional requirements in a particular project, and facilitate the reuse of architectural knowledge shared between projects of the same architectural domain (e.g., web-based applications).Peer ReviewedPostprint (author’s final draft

SeLoC-ML: Semantic Low-Code Engineering for Machine Learning Applications in Industrial IoT

Internet of Things (IoT) is transforming the industry by bridging the gap between Information Technology (IT) and Operational Technology (OT). Machines are being integrated with connected sensors and managed by intelligent analytics applications, accelerating digital transformation and business operations. Bringing Machine Learning (ML) to industrial devices is an advancement aiming to promote the convergence of IT and OT. However, developing an ML application in industrial IoT (IIoT) presents various challenges, including hardware heterogeneity, non-standardized representations of ML models, device and ML model compatibility issues, and slow application development. Successful deployment in this area requires a deep understanding of hardware, algorithms, software tools, and applications. Therefore, this paper presents a framework called Semantic Low-Code Engineering for ML Applications (SeLoC-ML), built on a low-code platform to support the rapid development of ML applications in IIoT by leveraging Semantic Web technologies. SeLoC-ML enables non-experts to easily model, discover, reuse, and matchmake ML models and devices at scale. The project code can be automatically generated for deployment on hardware based on the matching results. Developers can benefit from semantic application templates, called recipes, to fast prototype end-user applications. The evaluations confirm an engineering effort reduction by a factor of at least three compared to traditional approaches on an industrial ML classification case study, showing the efficiency and usefulness of SeLoC-ML. We share the code and welcome any contributions.Comment: Accepted by the 21st International Semantic Web Conference (ISWC2022

User interface patterns in recommendation-empowered content intensive multimedia applications

Design Patterns (DPs) are acknowledged as powerful conceptual tools to improve design quality and to reduce time and cost of the development process by effect of the reuse of “good” design solutions. In many fields (e.g., software engineering, web engineering, interface design) patterns are widely used by practitioners and are also investigated from a research perspective. Still, they have been seldom explored in the arena of Recommender Systems (RSs). RSs provide suggestions (“recommendations”) for items that are likely to be appropriate for the user profile, and are increasingly adopted in content-intensive multimedia applications to complement traditional forms of search in large information spaces. This paper explores RSs through the lens of User Interface (UI) Design Patterns. We have performed a systematic analysis of 54 recommendation-empowered content-intensive multimedia applications, in order to: (i) discover the occurrences of existing domain independent UI patterns; (ii) identify frequently adopted UI solutions that are not modelled by existing patterns, and define a set of new UI patterns, some of which are specific of the interfaces for recommendation features while others can be useful also in a broader context. The results of our inspection have been discussed with and evaluated by a team of experts, leading to a consolidated set of 14 new patterns that are reported in the paper. Reusing pattern-based design solutions instead of building new solutions from scratch enables novice and expert designers to build good UIs for Recommendation-empowered content intensive multimedia applications more effectively, and ultimately can improve the UX experience in this class of systems. From a broader perspective, our work can stimulate future research bridging Recommender Systems, Web Engineering and Interface Design by means of Design Patterns, and highlights new research directions also discussed in the paper

Ontology construction from online ontologies

One of the main hurdles towards a wide endorsement of ontologies is the high cost of constructing them. Reuse of existing ontologies offers a much cheaper alternative than building new ones from scratch, yet tools to support such reuse are still in their infancy. However, more ontologies are becoming available on the web, and online libraries for storing and indexing ontologies are increasing in number and demand. Search engines have also started to appear, to facilitate search and retrieval of online ontologies. This paper presents a fresh view on constructing ontologies automatically, by identifying, ranking, and merging fragments of online ontologies