As part of the Digital Library's transition to Open Access, new features for researchers are available in the Premium Edition. Click here to learn more.
Fine-grained and accurate source code differencing | Proceedings of the 29th ACM/IEEE International Conference on Automated Software Engineering
As part of the Digital Library's transition to Open Access, new features for researchers are available in the Premium Edition. Click here to learn more.
The mythical matched modules | Proceedings of the 24th ACM SIGPLAN conference companion on Object oriented programming systems languages and applications
Certified compilers are complex software systems. Like other large systems, they demand modular, extensible designs. While there has been progress in extensible metatheory mechanization, scaling extensibility and reuse to meet the demands of full ...
Boomerang | Proceedings of the 35th annual ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Bidirectional programming languages are a practical approach to the view update problem. Programs in these languages, called lenses, define both a view and an update policy - i.e., every program can be read as a function mapping sources to views as well ...
Denicek: Computational Substrate for Document-Oriented End-User Programming
As part of the Digital Library's transition to Open Access, new features for researchers are available in the Premium Edition. Click here to learn more.
Bidirectionalization for free! (Pearl) | Proceedings of the 36th annual ACM SIGPLAN-SIGACT symposium on Principles of programming languages
A bidirectional transformation consists of a function get that takes a source (document or value) to a view and a function put that takes an updated view and the original source back to an updated source, governed by certain consistency conditions ...
Resugaring | Proceedings of the 35th ACM SIGPLAN Conference on Programming Language Design and Implementation
Syntactic sugar plays a crucial role in engineering programming languages. It offers convenient syntax and higher-level of abstractions, as witnessed by its pervasive use in both general-purpose and domain-specific contexts. Unfortunately, the ...
Nicholas Carlini - Black-hat LLMs | [un]prompted 2026
Convivial design heuristics for software systems
The theme of this workshop is the proliferation of ideas about calling into question the cultural roots of our current programming languages, and the search for alternative paradigms with other cultural bases.
Programming Language Foundations in Agda – Table of Contents
This book is an introduction to programming language theory using the proof assistant Agda.
Magicoder: Empowering Code Generation with OSS-Instruct
We introduce Magicoder, a series of fully open-source (code, weights, and data) Large Language Models (LLMs) for code that significantly closes the gap with top code models while having no more...
Tree Borrows | Proceedings of the ACM on Programming Languages
The Rust programming language is well known for its ownership-based type system, which offers strong guarantees like memory safety and data race freedom. However, Rust also provides unsafe escape hatches, for which safety is not guaranteed automatically ...
Engraft: An API for Live, Rich, and Composable Programming
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Exploring the AT Protocol as a legibility layer for local-first software | grjte
Check out the project at https://notebook.groundmist.xyzCross-posted to https://baincapitalcrypto.com/atproto-for-local-first-legibility/ Some people like vim and some people like emacs and some people like something else, and why not have our documents able to be edited in all of those programs? ...
Defeating Prompt Injections by Design
Large Language Models (LLMs) are increasingly deployed in agentic systems that interact with an untrusted environment. However, LLM agents are vulnerable to prompt injection attacks when handling untrusted data. In this paper we propose CaMeL, a robust defense that creates a protective system layer around the LLM, securing it even when underlying models are susceptible to attacks. To operate, CaMeL explicitly extracts the control and data flows from the (trusted) query; therefore, the untrusted data retrieved by the LLM can never impact the program flow. To further improve security, CaMeL uses a notion of a capability to prevent the exfiltration of private data over unauthorized data flows by enforcing security policies when tools are called. We demonstrate effectiveness of CaMeL by solving $77\%$ of tasks with provable security (compared to $84\%$ with an undefended system) in AgentDojo. We release CaMeL at https://github.com/google-research/camel-prompt-injection.
Coeffects: Context-aware programming languages
Interactive essay that explains theory of coeffects and lets you type-check and run sample programs.
