For students learning to write code, developing strong foundational coding skills and cultivating proper code style early on is crucial for success in subsequent courses and professional work. TA-Bot, an automated assessment tool, incorporates novice-friendly style suggestions wrapped around an industry-standard static analysis tool, code correctness testing, and an innovative rate-limiting system called Time Between Submissions ("TBS''). This system works in conjunction with a gamified incentive mechanism designed to motivate students to start weekly assignments earlier. Our hypothesis posited that this incentive, when combined with the inherent effects of TBS, would not only encourage students to initiate assignments sooner but would also prompt them to address more style-related issues and produce higher quality code.

Debugging and monitoring programs are integral to engineering and deploying software. Dynamic analyses monitor applications through source code or IR injection, machine code or bytecode rewriting, virtual machine APIs, or direct hardware support. While these techniques are viable within their respective domains, common tooling across techniques is rare, leading to fragmentation of skills, duplicated efforts, and inconsistent feature support. We address this problem in the WebAssembly ecosystem with Whamm, an instrumentation framework for Wasm that uses engine-level probing and has a bytecode rewriting fallback to promote portability. Whamm solves three problems: 1) tooling fragmentation, 2) prohibitive instrumentation overhead of general-purpose frameworks, and 3) tedium of tailoring low-level high-performance mechanisms. Whamm provides fully- programmable instrumentation with declarative match rules, static and dynamic predication, automatic state reporting, and user library support, achieving high performance through compiler and engine optimizations. The Whamm engine API allows instrumentation to be provided to a Wasm engine as Wasm code, reusing existing engine optimizations and unlocking new ones, most notably intrinsification, to minimize overhead. A key insight of our work is that explicitly requesting program state in match rules, rather than reflection, enables the engine to efficiently bundle arguments and even inline compiled probe logic. Whamm streamlines the tooling effort, as its bytecode-rewriting target can run instrumented programs everywhere, lowering fragmentation and advancing the state of the art for engine support. We evaluate Whamm with case studies of non-trivial monitors and show it is expressive, powerful, and efficient.