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Automatic discovery of relationships among values of array elements is a challenging problem due to the unbounded nature of arrays. We present a framework for analyzing array operations that is capable of capturing numeric properties of array elements.In particular, the analysis is able to establish that all array elements are initialized by an array-initialization loop, as well as to discover numeric constraints on the values of initialized elements.The analysis is based on the combination of canonical abstraction and summarizing numeric domains. We describe a prototype implementation of the analysis and discuss our experience with applying the prototype to several examples, including the verification of correctness of an insertion-sort procedure.

The goal of this work is to develop compile-time algorithms for automatically verifying properties of imperative programs that manipulate dynamically allocated storage. The paper presents an analysis method that uses a characterization of a procedure's behavior in which parts of the heap not relevant to the procedure are ignored. The paper has two main parts: The first part introduces a non-standard concrete semantics, LSL, in which called procedures are only passed parts of the heap. In this semantics, objects are treated specially when they separate the "local heap" that can be mutated by a procedure from the rest of the heap, which-from the viewpoint of that procedure-is non-accessible and immutable. The second part concerns abstract interpretation of LSL and develops a new static-analysis algorithm using canonical abstraction.

Programs are hierarchical compositions of formulae satisfying structural and extra-structural relationships. A program editor can use knowledge of such relationships to detect and provide immediate feedback about violations of them. The Synthesizer Generator is a tool for creating such editors from language descriptions. An editor designer specifies the desired relationships and the feedback to be given when they are violated, as well as a user interface; from the specification, the Synthesizer Generator creates a full-screen editor for manipulating programs in the language.

In this paper, we present a technique to synthesize machine-code instructions from a semantic specification, given as a Quantifier-Free Bit-Vector (QFBV) logic formula. Our technique uses an instantiation of the CounterExample Guided Inductive Synthesis (CEGIS) framework, in combination with search-space pruning heuristics to synthesize instruction-sequences. To counter the exponential cost inherent in enumerative synthesis, our technique uses a divide-and-conquer strategy to break the input QFBV formula into independent sub-formulas, and synthesize instructions for the sub-formulas. Synthesizers created by our technique could be used to create semantics-based binary rewriting tools such as optimizers, partial evaluators, program obfuscators/de-obfuscators, etc. Our experiments for Intel's IA-32 instruction set show that, in comparison to our baseline algorithm, our search-space pruning heuristics reduce the synthesis time by a factor of 473, and our divide-andconquer strategy reduces the synthesis time by a further 3 to 5 orders of magnitude.