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Indexed in the SCIE (2018 Impact Factor 0.854), and in Scopus

Journal of Web Engineering

Editors-in-Chief:
Martin Gaedke, Chemnitz University of Technology, Germany
Geert-Jan Houben, Delft University of Technology, The Netherlands


ISSN: 1540-9589 (Print Version),

ISSN: 1544-5976 (Online Version)
Vol: 17   Issue: Combined Issue 6 & 7

Published In:   November 2018

Publication Frequency: 8 issues per year


Search Available Volume and Issue for Journal of Web Engineering


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Enhancing the Web With Advanced Engineering

doi: https://doi.org/10.13052/jwe1540-9589.17671
Juan Carlos Preciado1, Juan Hernández1, Tommi Mikkonen2 and Ralf Klamma3

1QUERCUS Software Engineering Group School of Technology, University of Extremadura, Spain
2University of Helsinki, Finland
3RWTH Aachen University, Germany

Abstract: [+]    |    Download File [ 45KB ]    |   Read Article Online

Abstract: In the last fifteen years, services deployed via the Web have become a part of our everyday lives. Supporting Web technologies have also evolved very quickly to respond to the new services and features demanded by mobile and always connected users. Currently, the demand for services on the Web is still growing at a very fast pace as well as new techniques, methods and cutting-edge technologies that make the Web an increasingly complex environment.

In this scenario, the application of systematic, disciplined and quantifiable approaches to development, operation, and maintenance of Web-based applications continues to have a full validity like never before. So, at this point, is where the Web Engineering discipline comes into the scene. Web Engineering deals with the process of developing, deploying and maintaining Web applications. The main issues of Web Engineering encompass how to successfully manage the diversity and complexity of Web development, and to avoid potential failures that may have serious implications.

The Liquid WebWorker API for Horizontal Offloading of Stateless Computations

doi: https://doi.org/10.13052/jwe1540-9589.17672
Andrea Gallidabino and Cesare Pautasso

Software Institute, Faculty of Informatics, Universit`a della Svizzera italiana, Lugano, Switzerland

Abstract: [+]    |    Download File [ 3489KB ]    |   Read Article Online

Abstract: As most users access the Web from multiple devices with different characteristics, ranging from powerful desktops or laptops to tablets, mobile phones or watches and cars, liquid Web applications seamlessly flow across multiple Web-enabled devices and adapt their distributed user interface to the set of devices simultaneously accessing the application. In this paper we focus on the business logic layer of rich Web applications and explore the opportunity to reduce the execution time of CPU-intensive tasks or limit their energy consumption by offloading them among nearby devices running the same liquid Web application. We extend the standard HTML5 WebWorker API with the concept of liquid WebWorkers, so that developers can transparently offload parallel execution of stateless tasks by managing the necessary device selection and direct peer-to-peer data transfer. By introducing the liquid WebWorkerAPI into our Liquid.js framework, we present how to create a pool of devices sharing their CPU processing capabilities according to different policies.

Keywords: WebWorkers, Edge Computing, Liquid Software, Horizontal Offloading.

Fine-grained Web Content Classification via Entity-level Analytics: The Case of Semantic Fingerprinting

doi: https://doi.org/10.13052/jwe1540-9589.17673
Govind, Céline Alec and Marc Spaniol

Université de Caen Normandie, Department of Computer Science Campus Côte de Nacre, F-14032 Caen, France

Abstract: [+]    |    Download File [ 8441KB ]    |   Read Article Online

Abstract: Approaching three decades ofWeb contents being created, the amount of heterogeneous data of diverse provenance becomes seemingly overwhelming and its organization is a “continuous battle” against time. In parallel, business, sociological, political, and media analysts require a structured access to these contents in order to conduct their studies. To this end, concise and – at the same time – efficient engineering methods are required to classify Web contents accordingly. However, the whole task is not as simple as classifying something as A or B, but to assign the most suitable (sub-)category for each Web content based on a fine-grained classification scheme. In practice, the underlying type hierarchies are commonly excerpts of large scale ontologies containing several hundreds or even thousands of (sub-)types decomposed into a few top-level types. Having such a fine-grained type hierarchy, the engineering task of Web content classification becomes out-most challenging. Our main objective in this work is to investigate whether entity-level analytics can be utilized to characterize aWeb content and align it onto a fine-grained hierarchy. We hypothesize that “You know a document by the named entities it contains”. To this end, we present a novel concept, called “Semantic Fingerprinting” that allows Web content classification solely based on the information derived from the named entities contained in a Web document. It encodes the semantic nature of a Web content into a concise vector, namely the semantic fingerprint. Thus, we expect that semantic fingerprints, when utilized in combination with machine learning, will enable a fine-grained classification of Web contents. In order to empirically validate the effectiveness of semantic fingerprinting, we perform a case study on the classification of Wikipedia documents. Even further, we thoroughly examine the results obtained by analyzing the performance of Semantic Fingerprinting with respect to the characteristics of the data set used for the experiments. In addition, we also investigate performance aspects of the engineered approach by discussing the run-time in comparison with its competitor baselines. We observe that the semantic fingerprinting approach outperforms the state-of-the-art baselines as it raises Web contents to the entity-level and captures their core essence. Moreover, our approach achieves a superior run time performance on the test data in comparison to competitors.

Keywords: Fine-grained Web Content Classification, Entity-level Web Analytics, AdvancedWeb Engineering,Web Semantics, Semantic Fingerprinting.

Evaluating the Effect of Developers’ Personality and Productivity on their Intention to Use Model-Driven Web Engineering Techniques: An Exploratory Observational Study

doi: https://doi.org/10.13052/jwe1540-9589.1764
Magister Glenda Toala Sánchez1, Cristina Cachero2, and Santiago Meliá2

1Universidad Central de Ecuador, Quito, Ecuador
2Universidad de Alicante, Alicante, Spain

Abstract: [+]    |    Download File [ 1545KB ]    |   Read Article Online

Abstract: Context: During the last decades, MDWE approaches have claimed important advantages in terms of short and long term productivity gains. However, the extent of such objective gains is still not clear. Moreover, despite such gains, they suffer from a low level of adoption. Being a complex socio-technical activity, not only productivity but also individual developer’s characteristics such as personality are potential explanatory factors of such situation.
Objective: To study the relationship between (a) intention to use MDWE approaches and (b) individual personality and productivity factors.
Method: We have proposed a conceptual model that has guided the design of an observational study with 77 subjects from the University of Alicante. After following an MDWE course, the subjects were measured in terms of their psychological profile, their productivity and their intention to use an MDWE approach in the future.
Results: The study shows that higher levels of neuroticism relate with lower intention to use MDWE: subjects rating high in this dimension regard MDWE as significantly more difficult to use, and they show lower interest in using MDWE in future developments. Also, it shows how highly effective MDWE developers express a higher intention to use the approach.
Conclusions: According to our data, in order to reach a wider audience, MDWE approaches need to improve their ease of use, and limit the amount of potential developer’s stressors. Also, our data suggest that the MDWE community should focus on improving the effectiveness of the developers, since it is the increased effectiveness rather than the efficiency what is significantly related with the intention to use MDWE in the future.

Keywords: MDWE, Personality, Productivity, Intention to Use, Technology Acceptance Model, EPQ-R, UMAM-Q.

OakStreaming: A Peer-to-Peer Video Streaming Library

doi: https://doi.org/10.13052/jwe1540-9589.17675
István Koren and Ralf Klamma

Advanced Community Information Systems (ACIS) Group, RWTH Aachen University, Ahornstr. 55, 52074 Aachen, Germany

Abstract: [+]    |    Download File [ 3758KB ]    |   Read Article Online

Abstract: Multimedia platforms dealing with movie streaming and video-based short messages have increased the global Internet video traffic substantially in the last couple of years. Over the same period, multimedia on the Web has been standardized in terms of codecs and browserbased JavaScript APIs. However, today the technological challenges concerning the distribution of large video files are mainly tackled by scaling up capacities in cloud data centers, or relying on content delivery networks. Both approaches favor financially strong, large companies, while independent video providers with highly demanded videos are disadvantaged. Peer-to-peer streaming provides an alternative by shifting the data streams to the clients. In this article, we conceptualize different methods to move video delivery from centralized cloud infrastructures to end user devices.We discuss their strengths & weaknesses and present design considerations. To exemplify a particular approach, we showcase the implementation and evaluation of OakStreaming, our system that streams videos peer-to-peer via WebTorrent in HTML5. Particularly, we offer Web video providers a library that has various parameters, for instance to limit the bandwidth available for peer-topeer uploads. The resulting library is available as open source software on GitHub.

Keywords: Web Engineering, Video Streaming, Peer-to-Peer, WebRTC,WebTorrent.

Auto-Extraction and Integration of Metrics for Web User Interfaces

doi: https://doi.org/10.13052/jwe1540-9589.17676
Maxim Bakaev1, Sebastian Heil2, Vladimir Khvorostov1 and Martin Gaedke2

1Novosibirsk State Technical University, Novosibirsk, Russia
2Technische Universität Chemnitz, Chemnitz, Germany

Abstract: [+]    |    Download File [ 5367KB ]    |   Read Article Online

Abstract: Metric-based assessment of web user interface (WUI) quality attributes is shifting from code (HTML/CSS) analysis to mining webpages’visual representations based on image recognition techniques. In our paper, we describe a visual analysis tool which takes a WUI screenshot and produces structured and machine-readable representation (JSON) of the interface elements’ spatial allocation. The implementation is based on OpenCV (image recognition functions), dlib (trained detector for the elements’ classification), and Tesseract (label and content text recognition). The JSON representation is used to automatically calculate several metrics related to visual complexity, which is known to have major effect on user experience with UIs. We further describe a WUI measurement platform that allows integration of the currently dispersed sets of metrics from different providers and demonstrate the platform’s use with several remote services. We perform statistical analysis of the collected metrics in relation to complexity-related subjective evaluations obtained from 63 human subjects of various nationalities. Finally, we build predictive models for visual complexity and show that their accuracy can be improved by integrating the metrics from different sets. Regressions with the single index of visual complexity metric that we proposed had R2=0.460, while the best joint model with 4 metrics had R2=0.647.

Keywords: Automated metrics, HCI Vision, web design mining, visual complexity.

River Publishers: Journal of Web Engineering