Context: Selenium is a widely used tool for end-to-end (E2E) web testing. However, it is often criticized for brittleness, slowness, and flakiness. In parallel, newer frameworks and Artificial Intelligence (AI) are reshaping the test automation landscape. Objectives: This study aims to investigate current practices, challenges, and emerging trends in Selenium-based test automation. Methods: We designed and executed a large-scale online survey targeting software professionals who use Selenium. The questionnaire covered technical practices, tooling, AI usage, perceived challenges, and competing tools. Results: A total of 88 complete responses were analyzed using descriptive statistics and thematic coding. The results show that Selenium remains the dominant tool for regression and functional testing, primarily using the Page Object Model (POM) pattern. The most reported challenges are related to assertability, asynchrony, and brittleness. AI tools like ChatGPT are gaining traction for test generation. Playwright is the most prominent alternative. Conclusion: While Selenium is recognized as a cornerstone in many automation workflows, its limited native test-specific features present a significant drawback. The findings indicate an increasing demand for testing-focused improvements within the Selenium ecosystem, as well as for enhanced integration with AI-driven development tools.

Context: While test automation offers numerous benefits, it also introduces significant challenges. Two challenges that developers and testers face on a daily basis, particularly when using Selenium WebDriver to test web applications, are driver management (involving tasks such as version identification, download, installation, and maintenance) and management of test lifecycle phases (using specific test libraries, as for example JUnit, and inserting annotations into the code). These manual tasks make test suite development particularly tedious, error-prone, and expensive. Recently, to ease the burden on developers and testers, some Java libraries have been proposed, called WebDriverManager and Selenium-Jupiter, capable of automatically carrying out the driver management process for Selenium WebDriver and simplifying the development of test suites. These libraries appear to be very promising but until now no one has experimentally evaluated their effectiveness. Objective: To investigate the effectiveness of WebDriverManager and Selenium-Jupiter in reducing driver management times and boilerplate code. Method: We designed and conducted a family of experiments (three for WebDriverManager and two for Selenium-Jupiter) with 104 master student participants from the University of Genoa, Italy (across academic years 2021/2022 and 2022/2023) and nine professional participants. Results: Results indicate that the adoption of Selenium WebDriver with WebDriverManager significantly reduces setup time for multi-browser test suites from 33% to 50% (depending on the tester experience). Additionally, Selenium-Jupiter reduces test suite development time significantly (20% on average). Although it also decreases total code length, the reduction is relatively small compared to overall code length. Conclusion: WebDriverManager and Selenium-Jupiter can be seen as valuable solutions for enhancing testers’ productivity by shortening the time needed to develop test suites and minimizing the amount of code to write.

Automated testing is vital for ensuring the reliability of web applications. This paper presents a preliminary study on leveraging artificial intelligence (AI) models, specifically ChatGPT and Github Copilot, to generate test scripts for web end-to-end testing. Through experimentation, we evaluated the feasibility and effectiveness of AI language models in generating test scripts based on natural language descriptions of user interactions with web applications.

Modern web applications are complex and used for tasks of primary importance, so their quality must be guaranteed at the highest levels. For this reason, testing techniques (e.g., end-to-end) are required to validate the overall behavior of web applications. One of the most popular tools for testing web applications is Selenium WebDriver. Selenium WebDriver automates the browser to mimic real user actions on the web.While Selenium has made testing easier for many Teams worldwide, it still has its share of challenges. To better understand the challenges and the corresponding solutions adopted we decided to undertake a personal opinion survey from the industry (in total with 78 highly skilled participants) with a focus on the Selenium ecosystem.The results allow understanding which challenges are consid-ered more relevant by professionals in their daily practice and which are the techniques, approaches, and tools they adopt to face them. Therefore, this study is useful to (1) practitioners interested in understanding how to solve the problems they face every day and (2) researchers interested in proposing innovative solutions to problems having a solid industrial impact.

In software engineering, observability is the ability to determine the current state of a software system based on its external outputs or signals such as metrics, logs, or traces. Web engineers rely on the web browser console as the primary tool to monitor the client-side of web applications during end-to-end tests. However, this is a manual and time-consuming task due to the different browsers available. This paper presents BrowserWatcher, an open-source browser extension providing cross-browser capabilities to observe web applications and automatically gather browser console logs in different browsers (e.g., Chrome, Firefox, or Edge). We have leveraged this extension to conduct an empirical study analyzing the browser console of the top-50 public websites manually and automatically. The results show that BrowserWatcher gathers all the well-known log categories such as console or error traces. It also reveals that each web browser additionally includes other types of logs, which differ among browsers, thus providing distinct pieces of information for the same website.

There are many applications that help orchestrate face-to-face, online, or hybrid classes through the cloud. Examples are polling apps like Wooclap or Mentimeter, digital boards like Jamboard or Miro, or diagramming tools like diagrams.net, Coggle, or Kialo. However, one can go one step further and integrate some of these tools in order to use the most appropriate tool for each teaching moment and have information flow across tools preserving consistency without having to do this manually. In this paper, we present a specific experience and extrapolate it to highlight the power of programming the teaching interaction.

Selenium WebDriver is a library that allows controlling web browsers (e.g., Chrome, Firefox, etc.) programmatically.It provides a cross-browser programming interface in several languages used primarily to implement end-to-end tests for web applications.JUnit is a popular unit testing framework for Java.Its latest version (i.e., JUnit 5) provides a programming and extension model called Jupiter.This paper presents Selenium-Jupiter, an open-source JUnit 5 extension for Selenium WebDriver.Selenium-Jupiter aims to ease the development of Selenium WebDriver tests thanks to an automated driver management process implemented in conjunction with the Jupiter parameter resolution mechanism.Moreover, Selenium-Jupiter provides seamless integration with Docker, allowing the use of different web browsers in Docker containers out of the box.This feature enables cross-browser testing, load testing, and troubleshooting (e.g., configurable session recordings).This paper presents an example case in which Selenium-Jupiter is used to evaluate the performance of video conferencing systems based on WebRTC.This example case shows that Selenium-Jupiter can build and maintain the required infrastructure for complex tests effortlessly.

The coronavirus pandemic has accelerated the digital transformation of society, and in particular of university teaching. Professors who were reluctant or unwilling to take advantage of what digital technologies offered suddenly were forced to teach with technologies. In this paper, we describe teaching during the two main phases during the pandemic at Universidad Carlos III de Madrid (UC3M): the first phase during the complete lockdown and the second where students were allowed on campus with limitations. We also explain how the investment done during these two phases influences teaching in the future and how digital cloud-based technologies promote active learning at the university.

WebRTC is the umbrella term for a number of emerging technologies that extends the web browsing model\nto exchange real-time media (Voice over IP, VoIP) with other browsers. The mechanisms to provide quality\nassurance for WebRTC are key to release this kind of applications to production environments.\nNevertheless, testing WebRTC based application, consistently automated fashion is a challenging problem.\nThe aim of this piece of research is to provide a comprehensive summary of the current trends in the domain\nof WebRTC testing. For the sake of completeness, we have carried out this survey by aggregating the results\nfrom three different sources of information: i) Scientific and academia research papers; ii) WebRTC testing\ntools (both commercial and open source); iii) "Grey literature”, that is, materials produced by organizations\noutside of the traditional commercial or academic publishing and distribution channels.

In this paper, we introduce NUBOMEDIA, an open source elastic cloud Platform as a Service (PaaS) specifically designed for real-time interactive multimedia and WebRTC services. NUBOMEDIA exposes its capabilities through simple Application Programming Interfaces (APIs), making possible to deploy and execute developers' applications. To that aim, NUBOMEDIA combines the simplicity and ease of development of API services with the flexibility of PaaS infrastructures. Once an application is implemented, developers just need to deploy it on top of NUBOMEDIA providing elasticity as a service and reliable communication.

In this paper we introduce Kurento Media Server: an open source WebRTC Media Server providing a toolbox of capabilities which include group communications, recording, routing, transcoding and mixing. Kurento supports a large number of media protocols such as WebRTC, plain RTP, RTSP or HTTP and bunch of codecs including VP8, VP9, H.264, H.263, OPUS, Speex, PCM or AMR. Kurento Media Server is based on a modular architecture, which makes it possible for developers to extend and customize its native capabilities with advanced media processing features such as computer vision, augmented reality or speech analysis. Kurento is ideal for WWW developers who find natural programming with its Java and JavaScript APIs following the traditional three tiered WWW development model.