This dissertation describes an approach for automatically verifying data structures, focusing on techniques for automatically proving formulas that arise in such verification. I have implemented this approach with my colleagues in a verification system called Jahob. Jahob verifies properties of Java programs with dynamically allocated data structures. Developers write Jahob specifications in classical higher-order logic (HOL); Jahob reduces the verification problem to deciding the validity of HOL formulas. I present a new method for proving HOL formulas by combining automated reasoning techniques. My method consists of 1) splitting formulas into individual HOL conjuncts, 2) soundly approximating each HOL conjunct with a formula in a more tractable fragment and 3) proving the resulting approximation using a decision procedure or a theorem prover. I present three concrete logics; for each logic I show how to use it to approximate HOL formulas, and how to decide the validity of formulas in this logic. First, I present an approximation of HOL based on a translation to first-order logic, which enables the use of existing resolution-based theorem provers. Second, I present an approximation of HOL based on field constraint analysis, a new technique that enables

We define a new decidable logic for expressing and checking invariants of programs that manipulate dynamically-allocated objects via pointers and destructive pointer updates. The main feature of this logic is the ability to limit the neighborhood of a node that is reachable via a regular expression from a designated node. The logic is closed under boolean operations (entailment, negation) and has a finite model property. The key technical result is the proof of decidability. We show how to express preconditions, postconditions, and loop invariants for some interesting programs. It is also possible to express properties such as disjointness of datastructures, and low-level heap mutations. Moreover, our logic can express properties of arbitrary data-structures and of an arbitrary number of pointer fields. The latter provides a way to naturally specify postconditions that relate the fields on the entry of a procedure to the field on the exit of a procedure. Therefore, it is possible to use the logic to automatically prove partial correctness of programs performing low-level heap mutations.

An important feature of object-oriented programming languages is the ability to dynamically instantiate user-defined container data structures such as lists, trees, and hash tables. Programs implement such data structures using references to dynamically allocated objects, which allows data structures to store unbounded numbers of objects, but makes reasoning about programs more difficult. Reasoning about object-oriented programs with complex data structures is simplified if data structure operations are specified in terms of abstract sets of objects associated with each data structure. For example, an insertion into a data structure in this approach becomes simply an insertion into a dynamically changing set-valued field of an object, as opposed to a manipulation of a dynamically linked structure linked to the object. In this paper we explore...

Spatial conjunction is a powerful construct for reasoning about dynamically allocated data structures, as well as concurrent, distributed and mobile computation. While researchers have identified many uses of spatial conjunction, its precise expressive power compared to traditional logical constructs was not previously known.