Abstract

A systematic literature review is presented that surveyed the topic of cloud testing over the period 2012--2017. Cloud testing can refer either to testing cloud-based systems (testing of the cloud) or to leveraging the cloud for testing purposes (testing in the cloud): both approaches (and their combination into testing of the cloud in the cloud) have drawn research interest. An extensive paper search was conducted by both automated query of popular digital libraries and snowballing, which resulted in the final selection of 147 primary studies. Along the survey, a framework has been incrementally derived that classifies cloud testing research among six main areas and their topics. The article includes a detailed analysis of the selected primary studies to identify trends and gaps, as well as an extensive report of the state-of-the-art as it emerges by answering the identified Research Questions. We find that cloud testing is an active research field, although not all topics have received enough attention and conclude by presenting the most relevant open research challenges for each area of the classification framework.

WebRTC is the umbrella term for several emergent technologies aimed to exchange real-time media in the Web. Like other media-related services, the perceived quality of WebRTC communication can be measured using Quality of Experience (QoE) indicators. QoE assessment methods can be classified as subjective (users’ evaluation scores) or objective (models computed as a function of different parameters). In this paper, we focus on VMAF (Video Multi-method Assessment Fusion), which is an emergent full-reference objective video quality assessment model developed by Netflix. VMAF is typically used to assess video streaming services. This paper evaluates the use of VMAF in a different type of application: WebRTC. To that aim, we present a practical use case built on the top of well-known open source technologies, such as JUnit, Selenium, Docker, and FFmpeg. In addition to VMAF, we also calculate other objective QoE video metrics such as Visual Information Fidelity in the pixel domain (VIFp), Structural Similarity (SSIM), or Peak Signal-to-Noise Ratio (PSNR) applied to a WebRTC communication in different network conditions in terms of packet loss. Finally, we compare these objective results with a subjective evaluation using a Mean Opinion Score (MOS) scale to the same WebRTC streams. As a result, we found a strong correlation of the subjective video quality perceived in WebRTC video calls with the objective results computed with VMAF and VIFp in comparison with SSIM and PSNR and their variants.

This paper introduces the concept of bilingual subtitles, a kind of captioning in which a pair of subtitles (in the mother tongue, L1, and second language, L2) is shown at the same time on the screen. The aim of dual subtitles is to help the final user in different learning processes, due to the fact that several capacities (listening, reading, and matching) are exercised at the same time by the learner while watching dual‐captioned media. The contribution of this paper is threefold. First, it presents DualSub, an open source desktop tool aimed to create bilingual subtitles. Second, a descriptive study was designed and executed to evaluate the extent to which bilingual subtitles are perceived by final users in the incidental vocabulary knowledge of a second language. Third, an experimental case study in which dual subtitles were used in the engineering education arena was carried out. The results of these surveys confirm that bilingual subtitles are perceived as useful in the different dimensions of the incidental vocabulary learning process (form, meaning, use) and are also helpful when applied to the educational domain (deliberate learning). © 2017 Wiley Periodicals, Inc. Comput Appl Eng Educ 25:468–479, 2017; View this article online at http://www.wileyonlinelibrary.com/journal/cae; DOI

WebRTC comprises a set of technologies and standards that provide real-time communication with web browsers, simplifying the embedding of voice and video communication in web applications and mobile devices. The perceived quality of WebRTC communication can be measured using Quality of Experience (QoE) indicators. QoE is defined as the degree of delight or annoyance of the user with an application or service. This paper is focused on the QoE assessment of WebRTC-based applications and its contribution is threefold. First, an analysis of how WebRTC topologies affect the quality perceived by users is provided. Second, a group of Key Performance Indicators for estimating the QoE of WebRTC users is proposed. Finally, a systematic survey of the literature on QoE assessment in the WebRTC arena is presented.