While the benefits of subtitles for comprehension are widely acknowledged, empirical research has largely neglected the insights offered by user reviews of mobile applications. This study presents a comprehensive analysis of user feedback on subtitle features in the top 230 mobile applications across various categories. We curated a dataset of 48,872 user reviews specifically related to subtitles, manually categorizing them based on user-provided information. To understand sentiment and accessibility concerns, we conducted sentiment analysis and extracted accessibility-related reviews. Our findings offer valuable insights into user challenges and expectations regarding subtitles in mobile applications, providing a foundation for enhancing their design and implementation. These insights include the need for improved customization options, better accessibility features, and more responsive subtitle performance.

Usability is a crucial aspect of software development, yet it is not emphasized enough in computing education. Studies show that poor usability leads to significant financial losses, with businesses in the United States alone incurring 62 billion in annual losses due to subpar user experiences. Despite its importance, usability principles are not sufficiently taught to computing students. This experience report presents HeuristicBuilder, an interactive multimodal educational tool designed to teach Jakob Nielsen's 10 usability heuristics. These principles are essential for designing user-friendly interactive systems, but often pose challenges in practical application. HeuristicBuilder addresses this by combining theoretical learning via reading and quizzes with practical UI design exercises. The tool was evaluated with 224 participants, showing significant improvements in both theoretical understanding and practical application of usability principles. Participants found HeuristicBuilder to be valuable and effective, preferring its interactive approach over traditional methods such as reading books or online courses. In conclusion, HeuristicBuilder proves effective at educating users about usability heuristics through engaging, accessible means. Its positive reception highlights its potential to enhance usability education and user experience design practices. Future enhancements aim to further optimize interactive learning and practical application, advancing skills among interaction designers and usability practitioners.

Digital accessibility ensures that digital products and services are usable by a diverse range of users, regardless of their physical or cognitive abilities. While numerous standards and guidelines have been established to aid developers in creating accessible content, studies reveal a persistent lack of accessibility in many web and mobile applications. This gap is often attributed to barriers such as lack of awareness, insufficient knowledge, absence of specific requirements, time constraints, and lack of executive support. In this context, we aim to address the lack of awareness and knowledge challenges by proposing a hands-on approach that leverages the capabilities of Large Language Models (LLMs) like ChatGPT to enhance students' accessibility awareness, knowledge, and practical skills. We engaged software engineering students in tasks involving website development and accessibility evaluation using checker tools, and we utilized ChatGPT 3.5 to fix identified accessibility issues. Our findings suggest that practical assignments significantly enhance learning outcomes, as interactions with LLMs allow students to develop a deeper understanding of accessibility concepts. This approach not only reinforces theoretical knowledge but also highlights the real-world impact of their work. The results indicate that combining practical assignments with AI-driven support effectively improves students' proficiency in web accessibility.

This experience report contributes to the expanding body of literature advocating for the inclusion of accessibility topics within core computing courses rather than restricting them to specialized electives such as human-computer interaction (HCI). We integrated an accessibility-focused sprint into a 3-credit software engineering course at a large private university in the US. Throughout the course, students progressively developed a software project in groups with a dedicated sprint designed to emphasize the importance of accessibility. This sprint included lectures on accessibility principles and hands-on accessibility testing on their own projects, followed by a sprint to fix the issues found. A survey was conducted at the end of the course to gauge their learning outcomes and perceptions of accessibility. The results demonstrate that integrating accessibility into a software engineering course not only enhances students' technical skills but also boosts their commitment to creating inclusive software. We present the accessibility interventions made, assessment instruments used and our findings in this report. We also offer key insights as takeaways for the computing education community, providing guidance for educators aiming to embed accessibility into their curriculum.

With over 95% of the top one million websites not being fully accessible, teaching digital accessibility to computing students is crucial. In this study, conducted over three spring semesters within a Software Engineering project course, we introduced dedicated sprints focused on accessibility. During these sprints, students were taught about various types of disabilities, accessibility principles, web content accessibility guidelines (WCAG), and various automated and manual techniques to test for accessibility. Students utilized automated tools to identify accessibility issues in their web projects and subsequently dedicated another sprint to address and resolve these issues. We systematically documented common accessibility mistakes students make, highlighting the WCAG 'success criteria' that require careful instructional focus. Additionally, we identify which accessibility issues are frequently and easily resolved by students and which challenges persist despite their efforts. This comprehensive analysis provides valuable insights, enabling the computing education community to effectively integrate and emphasize accessibility instruction in their curricula, ultimately fostering more inclusive and accessible web development practices.

Accessibility is an important quality factor of mobile applications. Many studies have shown that, despite the availability of many resources to guide the development of accessible software, most apps and web applications contain many accessibility issues. Some researchers surveyed professionals and organizations to understand the lack of accessibility during software development, but few studies have investigated how developers and organizations respond to accessibility bug reports. Therefore, this paper analyzes accessibility bug reports posted in the Chromium repository to understand how developers and organizations handle them. More specifically, we want to determine the frequency of accessibility bug reports over time, the time-to-fix compared to traditional bug reports (e.g., functional bugs), and the types of accessibility barriers reported. Results show that the frequency of accessibility reports has increased over the years, and accessibility bugs take longer to be fixed, as they tend to be given low priority.

Accessibility reviews collected from app stores may contain valuable information for improving apps accessibility. Recent studies have presented insightful information on accessibility reviews, but they were based on small datasets and focused on general accessibility concerns. In this paper, we analyzed accessibility reviews that report issues affecting users with visual disabilities or conditions. Such reviews were identified based on selection criteria applied over 179,519,598 reviews of popular apps on the Google Play Store. Our results show that only 0,003% of user reviews mention visual disabilities or conditions; accessibility reviews are associated with 36 visual disabilities or eye conditions; many users do not give precise feedback and refer to their disability using generic terms; accessibility reviews can be grouped into general topics of concerns related to different types of disabilities; and positive reviews are generally associated with high scores and negative feedback with lower scores.

Accessibility is a quality sub-characteristic intended to make software products accessible to a broad range of users, regardless of their physical, motor, intellectual or cognitive skills. Mobile accessibility has been on the spotlight recently due to the increasing shift towards mobile platforms. Thus, many advances have been made in this field when it comes to the development of assistive technologies, conception of well-documented accessibility guidelines and supporting tools. However, a general lack of accessibility in mobile applications has been observed in several studies. Researchers have conducted investigations to understand the same phenomenon in web development from the perspective of those involved in the development process, but studies concerning accessibility in the context of mobile applications are still scarce. This paper presents a survey conducted with 872 people involved in mobile application development in the Brazilian industry to gather information on their awareness, adoption, motivations and barriers to ensure digital accessibility. Results show that most participants have moderate accessibility awareness, but low levels of knowledge or adoption in practice. In addition, accessibility is usually not considered in their projects due to lack of requirements, time, training and focus on users with disabilities.

Smart toys raises new concerns for parents and researchers. Children are more likely to share sensitive data and are unaware or rarely care about online risks. Parents play a relevant role in protecting the children, and parental control tools are necessary to take control and properly manage their child's data, according to their preferences. However, current tools neither meet parental needs nor are compliant with a standard for toy makers. We present a study of requirements for the development of a parental control tool for smart toys.

Software testing involves probing into the behavior of software systems to uncover faults. Most testing activities are complex and costly, so a practical strategy that has been adopted to circumvent these issues is to automate software testing. There has been a growing interest in applying machine learning (ML) to automate various software engineering activities, including testing-related ones. In this paper, we set out to review the state-of-the art of how ML has been explored to automate and streamline software testing and provide an overview of the research at the intersection of these two fields by conducting a systematic mapping study. We selected 48 primary studies. These selected studies were then categorized according to study type, testing activity, and ML algorithm employed to automate the testing activity. The results highlight the most widely used ML algorithms and identify several avenues for future research. We found that ML algorithms have been used mainly for test-case generation, refinement, and evaluation. Also, ML has been used to evaluate test oracle construction and to predict the cost of testing-related activities. The results of this paper outline the ML algorithms that are most commonly used to automate software-testing activities, helping researchers to understand the current state of research concerning ML applied to software testing. We also found that there is a need for better empirical studies examining how ML algorithms have been used to automate software-testing activities.

It is important to make mobile apps accessible, so as not to exclude users with common disabilities such as blindness, low vision, or color blindness. Even when developers are aware of these accessibility needs, the lack of tool support makes the development and assessment of accessible apps challenging. Some accessibility properties can be checked statically, but user interface widgets are often created dynamically and are not amenable to static checking. Some accessibility checking frameworks analyze accessibility properties at runtime, but have to rely on existing thorough test suites. In this paper, we introduce the idea of using automated test generation to explore the accessibility of mobile apps. We present the MATE tool (Mobile Accessibility Testing), which automatically explores apps while applying different checks for accessibility issues related to visual impairment. For each issue, MATE generates a detailed report that supports the developer in fixing the issue. Experiments on a sample of 73 apps demonstrate that MATE detects more basic accessibility problems than static analysis, and many additional types of accessibility problems that cannot be detected statically at all. Comparison with existing accessibility testing frameworks demonstrates that the independence of an existing test suite leads to the identification of many more accessibility problems. Even when enabling Android's assistive features like contrast enhancement, MATE can still find many accessibility issues.

Evolutionary algorithms have been shown to be effective at generating unit test suites optimised for code coverage. While many specific aspects of these algorithms have been evaluated in detail (e.g., test length and different kinds of techniques aimed at improving performance, like seeding), the influence of the choice of evolutionary algorithm has to date seen less attention in the literature. Since it is theoretically impossible to design an algorithm that is the best on all possible problems, a common approach in software engineering problems is to first try the most common algorithm, a genetic algorithm, and only afterwards try to refine it or compare it with other algorithms to see if any of them is more suited for the addressed problem. The objective of this paper is to perform this analysis, in order to shed light on the influence of the search algorithm applied for unit test generation. We empirically evaluate thirteen different evolutionary algorithms and two random approaches on a selection of non-trivial open source classes. All algorithms are implemented in the EvoSuite test generation tool, which includes recent optimisations such as the use of an archive during the search and optimisation for multiple coverage criteria. Our study shows that the use of a test archive makes evolutionary algorithms clearly better than random testing, and it confirms that the DynaMOSA many-objective search algorithm is the most effective algorithm for unit test generation. Our results show that the choice of algorithm can have a substantial influence on the performance of whole test suite optimisation. Although we can make a recommendation on which algorithm to use in practice, no algorithm is clearly superior in all cases, suggesting future work on improved search algorithms for unit test generation.

Context: while the mobile computing market has expanded and become critical, the amount and complexity of mobile apps have also increased. To assure reliability, these apps require software engineering methods, mainly verification, validation, and testing. However, mobile app testing is a challenging activity due to the diversity and limitations found in mobile devices. Thus, it would be interesting to characterize mobile apps in hopes of assisting in the definition of more efficient and effective testing approaches. Objective: this paper aims to identify and quantify the specific characteristics of mobile apps so that testers can draw from this knowledge and tailor software testing activities to mobile apps. We investigate the presence of automated tests, adopted frameworks, external connectivity, graphical user interface (GUI) elements, sensors, and different system configurations. Method: we developed a tool to support the automatic extraction of characteristics from Android apps. We conducted an empirical study with a sample of 663 open source mobile apps. Results: we found that one third of the projects perform automated testing. The frameworks used in these projects can be divided into three groups: unit testing, GUI testing, and mocking. There is a medium correlation between project size and test presence. Specific features of mobile apps (connectivity, GUI, sensors, and multiple configurations) are present in the projects, however, they are fully covered by tests. Conclusion: automated tests are still not developed in a systematic way. Interestingly, measures of app popularity (number of downloads and rating) do not seem to be correlated with the presence of tests. However, the results show a correlation of the project size and more critical domains with the existence of automated tests. Although challenges such as connectivity, sensors, and multiple configurations are present in the examined apps, only one tool has been identified to support the testing of these challenges.

The low adoption of standards defined by the federal government may be preventing Brazilian e-government to reach more mature levels. In this context, the aim of this paper is to present an investigation we conducted in the Brazilian education sector to check whether federal universities comply with e-government standards when developing their web portals and which are their main strategies and challenges in this environment. Results show that most federal universities' main web portals do not follow important standards because the IT teams cannot cope with the combination of staff shortage, high demand, tight deadlines, and the lack of specific development methods. Such findings point to many possible improvements on the Brazilian Digital Government scenario that may also be useful to governments of developing countries.

Mobile computing has become ubiquitous, thus the amount and complexity of mobile applications have challenged software engineering practices. To overcome the challenges brought by mobile applications, the adoption of repeatable, systematic and mainly automated tests have been researched. In this paper, we look into open source projects in hopes of identifying how automated tests are applied to mobile applications developed for the Android platform. We analyzed the automated tests to identify the frameworks adopted, the relation between the production and the testing code, and how the following challenges have been dealt with: connectivity, rich GUIs, limited resources, sensors, and multiple configurations.

In software testing, a program is executed in hopes of revealing faults. Over the years, specific testing criteria have been proposed to help testers to devise test cases that cover the most relevant faulty scenarios. Symbolic execution has been used as an effective way of automatically generating test data that meet those criteria. Although this technique has been used for over three decades, several challenges remain and there is a lack of research on how often they appear in real-world applications. In this paper, we analyzed two samples of open source Java projects in order to understand the characteristics that may hinder the generation of unit test data using symbolic execution. The first sample, named SF100, is a third party corpus of classes obtained from 100 projects hosted by SourceForge. The second sample, called R47, is a set of 47 well-known and mature projects we selected from different repositories. Both samples are compared with respect to four dimensions that influence symbolic execution: path explosion, constraint complexity, dependency, and exception-dependent paths. The results provide valuable insight into how researchers and practitioners can tailor symbolic execution techniques and tools to better suit the needs of different Java applications.

Testing exception scenarios is a challenging task in the context of test data generation based on symbolic execution.In such a context, test data is generated based on constraints explicitly declared in the code.However, constraints required to activate specific exceptions may not be directly declared in the code.In such a case, implicit constraints have to be inferred from exception handling mechanisms.Given that exceptions can be raised in several situations, finding constraints to generate test data to exercise all possible faulty scenarios can significantly increase the number of paths and constraints, which can cause or aggravate path explosion issues.This paper reports on an investigation that we carried out to gauge the cost (i.e., number of path constraints) of four data generation approaches aimed at covering exception dependent paths.

Testing plays a key role in assessing the quality of a software product. During testing, a program is run in hopes of finding faults. As exhaustive testing is seldom possible, specific testing criteria have been proposed to help testers to devise test cases that cover the most relevant faulty scenarios. Manually creating test cases that satisfy these criteria is time consuming, error prone, and unwieldy. Symbolic execution has been used as an effective way of automatically generating test data that meets those criteria. Although this technique has been used for over three decades, several challenges remain, such as path explosion, precision of floating-point data, constraints with complex expressions, and dependency of external libraries. In this paper, we explore a sample of 100 open source Java projects in order to analyze characteristics that are relevant to generate test data using symbolic execution. The results provide valuable insight into how researchers and practitioners can tailor symbolic execution techniques and tools to better suit the needs of different Java applications.

Web services are an emerging Service-Oriented Architecture technology to integrate applications using open standards based on XML. Software Engineering tools integration is a promising area since companies adopt different software processes and need different tools on each activity. Software engineers could take advantage of software engineering tools available as web services and create their own workflow for integrating the required tools. In this paper, we propose the development of testing tools designed as web services and discuss the pros and cons of this idea. We developed a web service for structural testing of Java programs called JaBUTiService, which is based on the stand-alone tool JaBUTi. We also present an usage example of this service with the support of a desktop front-end and pre prepared scripts. A set of 62 classes of the library Apache-Commons-BeanUtils was used for this test and the results are discussed.