... This paper concerns the problem of interprocedural slicing---generating a slice of an entire program, where the slice crosses the boundaries of procedure calls. To solve this problem, we introduce a new kind of graph to represent programs, called a system dependence graph, which extends previous dependence representations to incorporate collections of procedures (with procedure calls) rather than just monolithic programs. Our main result is an algorithm for interprocedural slicing that uses the new representation. (It should be noted that our work concerns a somewhat restricted kind of slice: Rather than permitting a program to be sliced with respect to program point p and an arbitrary variable, a slice must be taken with respect to a variable that is defined or used at p.) The chief

A program slice consists of the parts of a program that (potentially) affect the values computed at some point of interest, referred to as a slicing criterion. The task of computing program slices is called program slicing. The original definition of a program slice was presented by Weiser in 1979. Since then, various slightly different notions of program slices have been proposed, as well as a number of methods to compute them. An important distinction is that between a static and a dynamic slice. The former notion is computed without making assumptions regarding a program's input, whereas the latter relies on some specific test case. Procedures, arbitrary control flow, composite datatypes and pointers, and interprocess communication each require a specific solution. We classify static and dynamic slicing methods for each of these features, and compare their accuracy and efficiency. Moreover, the possibilities for combining solutions for different features are investigated....

The conventional notion of a program slice---the set of all statements that might affect the value of a variable occurrence---is totally independent of the program input values. Program debugging, however, involves analyzing the program behavior under the specific inputs that revealed the bug. In this paper we address the dynamic counterpart of the static slicing problem---finding all statements that really affected the value of a variable occurrence for the given program inputs. Several approaches for computing dynamic slices are examined. The notion of a Dynamic Dependence Graph and its use in computing dynamic slices is discussed. We introduce the concept of a Reduced Dynamic Dependence Graph whose size does not depend on the length of execution history, which is unbounded in general, but whose size is bounded and is proportional to the number of dynamic slices arising during the program execution.

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 effects of a proposed change by isolating those effects in a single component of the decomposition. This gives maintainers a straightforward technique for determining those statements and variables that may be modified in a component and those that may not. Using the decomposition, we provide a set of principles to prohibit changes that will interfere with unmodified components. These semantically consistent ch...

The need to integrate several versions of a program into a common one arises frequently, but it is a tedious and time consuming task to integrate programs by hand. To date, the only available tools for assisting with program integration are variants of text-based differential file comparators; these are of limited utility because one has no guarantees about how the program that is the product of an integration behaves compared to the programs that were integrated. This paper concerns the design of a semantics-based tool for automatically integrating program versions. The main contribution of the paper is an algorithm that takes as input three programs A, B, and Base, where A and 8 are two variants of Base. Whenever the changes made to Base to create A and B do not “interfere ” (in a sense defined in the paper), the algorithm produces a program M that integrates A and B. The algorithm is predicated on the assumption that differences in the behavior of the variant programs from that of Base, rather than differences in the text, are significant and must be preserved in M. Although it is undecidable whether a program modification actually leads to such a difference, it is possible to determine a safe approximation by comparing each of the variants with Base. To determine this information, the integration algorithm employs a program representation that is similar (although not identical) to the dependence graphs that have been used

The first interprocedural modification side-effects analysis for C (MOD_C) that obtains better than worst-case precision on programs with general-purpose pointer usage is presented with empirical results. The analysis consists of an algorithm schema corresponding to a family of MODC algorithms with two independent phases: one for determining pointer-induced aliases and a subsequent one for propagating interprocedural side effects. These MOD_C algorithms are parameterized by the aliasing method used. The empirical results compare the performance of two dissimilar MOD_C algorithms: MOD_C(FSAlias) uses a flow-sensitive, calling-context-sensitive interprocedural alias analysis [LR92]; MOD_C(FIAlias) uses a flow-insensitive, calling-context-insensitive alias analysis which is much faster, but less accurate. These two algorithms were profiled on 45 programs ranging in size from 250 to 30,000 lines of C code, and the results demonstrate dramatically the possible cost-precision tradeoffs. This first comparative implementation of MODC analyses offers insight into the differences between flow-/context-sensitive and flow-/context-insensitive analyses. The analysis cost versus precision tradeoffs in side-effect information obtained is reported. The results show surprisingly that the precision of flow-sensitive side-effect analysis is not always prohibitive in cost, and that the precision of flow-insensitive analysis is substantially better than worst-case estimates and seems sufficient for certain applications. On average MODC (FSAlias) for procedures and calls is in the range of 20% more precise than MODC (F IAlias); however, the performance was found to be at least an order of magnitude slower than MODC (F IAlias).

We examine the functional cohesion of procedures using a data slice abstraction. Our analysis identifies the data tokens that lie on more than one slice as the "glue" that binds separate components together. Cohesion is measured in terms of the relative number of glue tokens, tokens that lie on more than one data slice, and super-glue tokens, tokens that lie on all data slices in a procedure, and the adhe- siveness of the tokens. The intuition and measurement scale factors are demonstrated through a set of abstract transfor- mations.

Program slicing is a decomposition technique that elides program components not relevant to a chosen computation, referred to as a slicing criterion. The remaining components form an executable program called a slice that computes a projection of the original program’s semantics. Using examples coupled with fundamental principles, a tutorial introduction to program slicing is presented. Then applications of program slicing are surveyed, ranging from its first use as a debugging technique to current applications in property verification using finite state models. Finally, a summary of research challenges for the slicing community is discussed.

Traditional, syntax-preserving program slicing simpli es a program by deleting components (e.g., statements and predicates) that do not aect a computation of interest. Amorphous slicing removes the limitation to component deletion as the only means of simpli cation, while retaining the semantic property that a slice preserves the selected behaviour of interest from the original program. This leads to slices which are often considerably smaller than their syntax-preserving counterparts.

This paper describes a language-independent program representation-the program dependence graph—and &mCusses how program dependence graphs, together with operations such as program slicing, can provide the basis for powerfid programming tools that address important software-engineering problems, such as understanding what an existing program does and how it works, understanding the differences between several versions of a program, and creating new programs by combining pieces of old programs. The paper primarily surveys work in this mea that has been czried out at the University of Wisconsin during the past five years.