Making Abstract Domains Condensing
R. Giacobazzi, F. Ranzato, F. Scozzari

TL;DR
This paper introduces condensing abstract domains that preserve analysis precision in logic languages by refining domains to align goal-driven and goal-independent semantics, leveraging linear logic structures.
Contribution
It formalizes condensing abstract domains as a property and provides a systematic method to refine any domain to be condensing using linear logic-based techniques.
Findings
Condensing domains ensure goal-driven and goal-independent analyses agree.
Refinement of domains can be achieved via a simple operator based on linear logic.
Condensing domains can be explicitly characterized using linear logic formulations.
Abstract
In this paper we show that reversible analysis of logic languages by abstract interpretation can be performed without loss of precision by systematically refining abstract domains. The idea is to include semantic structures into abstract domains in such a way that the refined abstract domain becomes rich enough to allow approximate bottom-up and top-down semantics to agree. These domains are known as condensing abstract domains. Substantially, an abstract domain is condensing if goal-driven and goal-independent analyses agree, namely no loss of precision is introduced by approximating queries in a goal-independent analysis. We prove that condensation is an abstract domain property and that the problem of making an abstract domain condensing boils down to the problem of making the domain complete with respect to unification. In a general abstract interpretation setting we show that when…
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Taxonomy
TopicsLogic, programming, and type systems · Formal Methods in Verification · Model-Driven Software Engineering Techniques
