Program slicing, introduced by Weiser, is known to help programmers in understanding foreign code and in debugging. We apply program slicing to the maintenance problem by extending the notion of a program slice (that originally required both a variable and line number) to a decomposition slice, one that captures all computation on a given variable; i.e., is independent of line numbers. Using the lattice of single variable decomposition slices, ordered by set inclusion, we demonstrate how to form a slice-based decomposition for programs. We are then able to delineate the e ects of a proposed change by isolating those e ects in a single component of the decomposition. This gives maintainers a straightforward technique for determining those statements and variables that may be modi ed in a component and those that may not. Using the decomposition, we provide a set of principles to prohibit changes that will interfere with unmodi ed components. These semantically consistent changes can then be merged back into the original program in linear time. Moreover, the maintainer can test the changes in the component with the assurance that there are no linkages into other components. Thus, decomposition slicing induces a new software maintenance process model that eliminates the need for regression testing.

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A dependence cluster is a set of program statements, all of which are mutually inter-dependent. This article reports a large scale empirical study of dependence clusters in C program source code. The study reveals that large dependence clusters are surprisingly commonplace. Most of the 45 programs studied have clusters of dependence that consume more than 10% of the whole program. Some even have clusters consuming 80% or more. The widespread existence of clusters has implications for source code analyses such as program comprehension, software maintenance, software testing, reverse engineering, reuse, and parallelization.

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