Adam Welc | Searcharxiv

arXiv2026

Optimizing an IDE for an Evolving Language Ecosystem

This paper describes a strategy for developing a high performance and feature-rich IDE for an evolving smart contract language ecosystem. Our target is Move, a programming language for the Sui smart contracts platform. The strategy we chose to support the Move language ecosystem utilizes Language Server Protocol (LSP) and it is based on the already existing "core" language machinery, in particular the core language compiler. We discuss alternatives we considered, as well as the evolution of our infrastructure that was necessary to keep up with the growth of the language ecosystem, particularly with respect to optimizations (and their impact) that needed to be implemented to accommodate this growth. We conclude with lessons learned during the IDE support development process that we hope will be beneficial for others attempting to follow a similar path.

cs.SE↗

arXiv2021

Optimistic Concurrency Control for Real-world Go Programs (Extended Version with Appendix)

We present a source-to-source transformation framework, GOCC, that consumes lock-based pessimistic concurrency programs in the Go language and transforms them into optimistic concurrency programs that use Hardware Transactional Memory (HTM). The choice of the Go language is motivated by the fact that concurrency is a first-class citizen in Go, and it is widely used in Go programs. GOCC performs rich inter-procedural program analysis to detect and filter lock-protected regions and performs AST-level code transformation of the surrounding locks when profitable. Profitability is driven by both static analyses of critical sections and dynamic analysis via execution profiles. A custom HTM library, using perceptron, learns concurrency behavior and dynamically decides whether to use HTM in the rewritten lock/unlock points. Given the rich history of transactional memory research but its lack of adoption in any industrial setting, we believe this workflow, which ultimately produces source-code patches, is more apt for industry-scale adoption. Results on widely adopted Go libraries and applications demonstrate significant (up to 10x) and scalable performance gains resulting from our automated transformation while avoiding major performance regressions.

cs.DC↗