979 research outputs found
Interacting via the Heap in the Presence of Recursion
Almost all modern imperative programming languages include operations for
dynamically manipulating the heap, for example by allocating and deallocating
objects, and by updating reference fields. In the presence of recursive
procedures and local variables the interactions of a program with the heap can
become rather complex, as an unbounded number of objects can be allocated
either on the call stack using local variables, or, anonymously, on the heap
using reference fields. As such a static analysis is, in general, undecidable.
In this paper we study the verification of recursive programs with unbounded
allocation of objects, in a simple imperative language for heap manipulation.
We present an improved semantics for this language, using an abstraction that
is precise. For any program with a bounded visible heap, meaning that the
number of objects reachable from variables at any point of execution is
bounded, this abstraction is a finitary representation of its behaviour, even
though an unbounded number of objects can appear in the state. As a
consequence, for such programs model checking is decidable.
Finally we introduce a specification language for temporal properties of the
heap, and discuss model checking these properties against heap-manipulating
programs.Comment: In Proceedings ICE 2012, arXiv:1212.345
COSMICAH 2005: workshop on verification of COncurrent Systems with dynaMIC Allocated Heaps (a Satellite event of ICALP 2005) - Informal Proceedings
Lisboa Portugal, 10 July 200
Modular Construction of Shape-Numeric Analyzers
The aim of static analysis is to infer invariants about programs that are
precise enough to establish semantic properties, such as the absence of
run-time errors. Broadly speaking, there are two major branches of static
analysis for imperative programs. Pointer and shape analyses focus on inferring
properties of pointers, dynamically-allocated memory, and recursive data
structures, while numeric analyses seek to derive invariants on numeric values.
Although simultaneous inference of shape-numeric invariants is often needed,
this case is especially challenging and is not particularly well explored.
Notably, simultaneous shape-numeric inference raises complex issues in the
design of the static analyzer itself.
In this paper, we study the construction of such shape-numeric, static
analyzers. We set up an abstract interpretation framework that allows us to
reason about simultaneous shape-numeric properties by combining shape and
numeric abstractions into a modular, expressive abstract domain. Such a modular
structure is highly desirable to make its formalization and implementation
easier to do and get correct. To achieve this, we choose a concrete semantics
that can be abstracted step-by-step, while preserving a high level of
expressiveness. The structure of abstract operations (i.e., transfer, join, and
comparison) follows the structure of this semantics. The advantage of this
construction is to divide the analyzer in modules and functors that implement
abstractions of distinct features.Comment: In Proceedings Festschrift for Dave Schmidt, arXiv:1309.455
On Verifying Complex Properties using Symbolic Shape Analysis
One of the main challenges in the verification of software systems is the
analysis of unbounded data structures with dynamic memory allocation, such as
linked data structures and arrays. We describe Bohne, a new analysis for
verifying data structures. Bohne verifies data structure operations and shows
that 1) the operations preserve data structure invariants and 2) the operations
satisfy their specifications expressed in terms of changes to the set of
objects stored in the data structure. During the analysis, Bohne infers loop
invariants in the form of disjunctions of universally quantified Boolean
combinations of formulas. To synthesize loop invariants of this form, Bohne
uses a combination of decision procedures for Monadic Second-Order Logic over
trees, SMT-LIB decision procedures (currently CVC Lite), and an automated
reasoner within the Isabelle interactive theorem prover. This architecture
shows that synthesized loop invariants can serve as a useful communication
mechanism between different decision procedures. Using Bohne, we have verified
operations on data structures such as linked lists with iterators and back
pointers, trees with and without parent pointers, two-level skip lists, array
data structures, and sorted lists. We have deployed Bohne in the Hob and Jahob
data structure analysis systems, enabling us to combine Bohne with analyses of
data structure clients and apply it in the context of larger programs. This
report describes the Bohne algorithm as well as techniques that Bohne uses to
reduce the ammount of annotations and the running time of the analysis
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