Team, Visitors, External Collaborators
Overall Objectives
Research Program
Application Domains
Highlights of the Year
New Software and Platforms
New Results
Bilateral Contracts and Grants with Industry
Partnerships and Cooperations
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Section: New Results

Relational Static Analysis

Relational abstraction for memory properties

Participants : Hugo Illous, Matthieu Lemerre, Xavier Rival [correspondant] .

Static analyses aim at inferring semantic properties of programs. We can distinguish two important classes of static analyses: state analyses and relational analyses. While state analyses aim at computing an over-approximation of reachable states of programs, relational analyses aim at computing functional properties over the input-output states of programs. Several advantages of relational analyses are their ability to analyze incomplete programs, such as libraries or classes, but also to make the analysis modular, using input-output relations as composable summaries for procedures. In the case of numerical programs, several analyses have been proposed that utilize relational numerical abstract domains to describe relations. On the other hand, designing abstractions for relations over input-output memory states and taking shapes into account is challenging. We have proposed a set of novel logical connectives to describe such relations, which are inspired by separation logic. This logic can express that certain memory areas are unchanged, freshly allocated, or freed, or that only part of the memory was modified. Using these connectives, we have built an abstract domain and design a static analysis that over-approximates relations over memory states containing inductive structures. We implemented this analysis and evaluated it on a basic library of list manipulating functions.

This work was done as part of the Phd of Hugo Illous [10] and a journal paper is currently under submission.