Handling Exceptions and Effects with Automatic Resource Analysis

2026-02-28

AI Summary

This work addresses the challenge that existing automatic resource analysis techniques struggle to handle non-local control transfers induced by exceptions and effect handlers. We present the first automated amortized resource analysis framework that supports such features, extending type-based AARA (Automatic Amortized Resource Analysis) with a novel type system and a stack-based abstract machine to automatically derive resource bounds for programs with exceptions and algebraic effects. Key technical contributions include linear and polynomial potential functions, a syntax-directed type soundness theorem, and a prototype implementation in Standard ML. Experimental evaluation demonstrates that our approach successfully analyzes programs beyond the scope of prior techniques, with only modest performance overhead introduced by the handling of exceptions and effect mechanisms.

Technology Category

• Knowledge Representation and Reasoning: Automated Reasoning and Theorem Proving
• Constraint Satisfaction and Optimization: Satisfiability Modulo Theories
• Multiagent Systems: Agreement, Argumentation & Negotiation

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Systems and Infrastructure for Web, Mobile and WoT: Virtualization and resource management in Web systems and infrastructures
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

There exist many techniques for automatically deriving parametric resource (or cost) bounds by analyzing the source code of a program. These techniques work effectively for a large class of programs and language features. However, non-local transfer of control as needed for exception or effect handlers has remained a challenge. This paper presents the first automatic resource bound analysis that supports non-local control transfer between exceptions or effects and their handlers. The analysis is an extension of type-based automatic amortized resource analysis (AARA), which automates the potential method of amortized analysis. It is presented for a simple functional language with lists and linear potential functions. However, the ideas are directly applicable to richer settings and implemented for Standard ML and polynomial potential functions. Apart from the new type system for exceptions and effects, a main contribution is a novel syntactic type-soundness theorem that establishes the correctness of the derived bounds with respect to a stack-based abstract machine. An experimental evaluation shows that the new analysis is capable of analyzing programs that cannot be analyzed by existing methods and that the efficiency overhead of supporting exception and effect handlers is low.

Problem

• resource analysis
• non-local control transfer
• exception handling
• effect handlers
• amortized analysis

Innovation

• automatic resource analysis
• non-local control transfer
• amortized analysis
• type system
• exception handling