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

Window inference is a transformational style of reasoning that provides an intuitive framework for managing context during the transformation of subterms under transitive relations. This report describes the design for a prototype window inference tool in Isabelle, and discusses possible directions for the final tool. 1

Abstract. Our goal is to help the developers of computer-based systems to make informed design decisions on the basis of insights gained from the rigorous analysis of abstract system models. The early work on model-oriented specification has inspired the development of numerous formalisms and tools supporting modelling and analysis. There are also many stories of successful industrial application, often driven by a few champions possessing deep a priori understanding of formalisms. There are fewer cases of successful take-up or adoption of the technology in the long term. We argue that successful industrial adoption of this technology requires that potential users strike a balance between the effort expended in producing and analysing a model and insight gained. In order to support this balancing act, tools need to offer a range of levels of effort and insight. Further, educators need to recognise that training in formal development techniques must support this trade-off process. 1