Program slicing is a program analysis technique that has been studied in the context of several different applications in the construction, optimization, maintenance, testing, and debugging of programs. Algorithms are available for constructing slices for a particular execution of a program (dynamic slices), as well as to approximate a subset of the behavior over all possible executions of a program (static slices). However, these algorithms have been studied only in the context of small abstract languages. Program slicing is bound to remain an academic exercise unless one can not only demonstrate the feasibility of building a slicer for nontrivial programs written in a real programming language, but also verify that a type of slice is sufficiently thin, on the average, for the application for which it is chosen. In this article, we present results from using SLICE , a dynamic program slicer for C programs, designed and implemented to experiment with several different kinds of program slices and to study them both qualitatively and quantitatively. Several application programs, ranging in size (i.e., number of lines of code) over two orders of magnitude, were sliced exhaustively to obtain average worst-case metrics for the size of program slices.

A tool that bridges the gap between the theory and practice of program analysis specifications is described. The tool supports a high-level specification language that enables clear and concise expression of analysis algorithms. The denotational nature of the specifications eases the derivation of formal proofs of correctness for the analysis algorithm. SPARE (structured program analysis refinement environment) is based on a hybrid approach that combines the positive aspects of both the operational and the semantics-driven approach. An extended denotational framework is used to provide specifications in a modular fashion. Several extensions to the traditional denotational specification language have been designed to allow analysis algorithms to be expressed in a clear and concise fashion. This extended framework eases the design of analysis algorithms as well as the derivation of correctness proofs. The tool provides automatic implementation for testing purposes.>

Program slicing is a source-to-source transformation

Abstract interpretation introduced the notion of formal specification of program analyses. Denotational frameworks are convenient for reasoning about such specifications. However, implementation considerations make denotational specifications complex and hard to develop. We present a framework that facilitates the construction and understanding of denotational specifications for program analysis techniques. The framework is exemplified by specifications for program analysis techniques from the literature and from our own research. This approach allows program analysis techniques to be incorporated into automatically generated program synthesizers by including their specifications with the language definition.