Team projects are an essential part of any software engineering program, and are known to help students in learning the primary course materials while imparting valuable teamwork skills. At the same time, teamwork can also present challenges, to both students and their instructors. Well-known problems include teams not following recommended practices (e.g., producing deliverables out of order or at the last minute) and problematic team dynamics interfering with progress (e.g., social loafing or last-minute heroes). This paper presents TeamCAST, a tool we designed to address both kinsd of problems. The key idea underneath TeamCAST is that, by tapping into the intermediate work that students produce as part of their projects, it becomes possible to gain insight into both team progress and contributions. TeamCAST is designed to provide an easy-to-use platform for students to submit such intermediate work and for instructors to monitor the ongoing projects in an intuitive dashboard. This experience report introduces the primary design decisions underlying TeamCAST and presents the results of an exploratory pilot use in a 179 student software design class.

Despite the availability of numerous automatic accessibility testing solutions, web accessibility issues persist on many websites. Moreover, there is a lack of systematic evaluations of the efficacy of current accessibility testing tools. To address this gap, we present the first mutation analysis framework, called Ma11y, designed to assess web accessibility testing tools. Ma11y includes 25 mutation operators that intentionally violate various accessibility principles and an automated oracle to determine whether a mutant is detected by a testing tool. Evaluation on real-world websites demonstrates the practical applicability of the mutation operators and the framework’s capacity to assess tool performance. Our results demonstrate that the current tools cannot identify nearly 50% of the accessibility bugs injected by our framework, thus underscoring the need for the development of more effective accessibility testing tools. Finally, the framework’s accuracy and performance attest to its potential for seamless and automated application in practical settings.