Argus: Interactively Debugging Rust trait Errors

Traits are a source of bewildering error messages in the Rust community and people have spent money and time trying to improve the resulting diagnostics. We took a different approach. We analyzed a community suite of difficult-to-debug trait errors and formed hypotheses about why they were difficult for engineers to debug. Then, we built an interactive debugger that developers can use in the IDE to debug trait errors. Find more details about our process, the tool, and our paper in our Cognitive Engineering Lab blog post.

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LTL Tutor

We have been engaged in a multi-year project to improve education in Linear Temporal Logic (LTL) [Blog Post 1, Blog Post 2]. In particular, we have arrived at a detailed understanding of typical misconceptions that learners and even experts have. Our useful outcome from our studies is a set of instruments (think “quizzes”) that instructors can deploy in their classes to understand how well their students understand the logic and what weaknesses they have.

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Misconceptions In Finite-Trace and Infinite-Trace Linear Temporal Logic

Over the past three years and with a multi-national group of collaborators, we have been digging deeper into misconceptions in LTL (Linear Temporal Logic) and studying misconceptions in LTLf, a promising variant of LTL restricted to finite traces. Why LTL and LTLf? Because beyond their traditional uses in verification and now robot synthesis, they support even more applications, from image processing to web-page testing to process-rule mining. Why study misconceptions? Because ultimately, human users need to fully understand what a formula says before they can safely apply synthesis tools and the like.

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Iterative Student Program Planning using Transformer-Driven Feedback

We’ve had a few projects now that address this idea of teaching students to plan out solutions to programming problems. A thus-far missing but critical piece is feedback on this planning process. Ideally we want to give students feedback on their plans before they commit to any code details. Our early studies had students express their plans in a semi-formalized way which would’ve allowed us to automatically generate feedback based on formal structure. However, our most recent project highlighted a strong preference towards more freedom in notation, with plans expressed in far less structured language. This presents a challenge when designing automated feedback.

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Differential Analysis: A Summary

For multiple decades we have worked on a the problem of differential analysis. This post explains where it comes from, what it means, and what its consequences are.

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