PROGRAM SLICING TECHNIQUES AND ITS APPLICATIONS

Program understanding is an important aspect in Software Maintenance and Reengineering. Understanding the program is related to execution behaviour and relationship of variable involved in the program. The task of finding all statements in a program that directly or indirectly influence the value for an occurrence of a variable gives the set of statements that can affect the value of a variable at some point in a program is called a program slice. Program slicing is a technique for extracting parts of computer programs by tracing the programs’ control and data flow related to some data item. This technique is applicable in various areas such as debugging, program comprehension and understanding, program integration, cohesion measurement, re-engineering, maintenance, testing where it is useful to be able to focus on relevant parts of large programs. This paper focuses on the various slicing techniques (not limited to) like static slicing, quasi static slicing, dynamic slicing and conditional slicing. This paper also includes various methods in performing the slicing like forward slicing, backward slicing, syntactic slicing and semantic slicing. The slicing of a program is carried out using Java which is a object oriented programming language

A trajectory-based strict semantics for program slicing

We define a program semantics that is preserved by dependence-based slicing algorithms. It is a natural extension, to non-terminating programs, of the semantics introduced by Weiser (which only considered terminating ones) and, as such, is an accurate characterisation of the semantic relationship between a program and the slice produced by these algorithms. Unlike other approaches, apart from Weiser’s original one, it is based on strict standard semantics which models the ‘normal’ execution of programs on a von Neumann machine and, thus, has the advantage of being intuitive. This is essential since one of the main applications of slicing is program comprehension. Although our semantics handles non-termination, it is defined wholly in terms of finite trajectories, without having to resort to complex, counter-intuitive, non-standard models of computation. As well as being simpler, unlike other approaches to this problem, our semantics is substitutive. Substitutivity is an important property becauseit greatly enhances the ability to reason about correctness of meaning-preserving program transformations such as slicing

Minimal slicing and the relationships between forms of slicing.

The widespread interest in program slicing within the source code analysis and manipulation community has led to the introduction of a large number of different slicing techniques. Each preserves some aspect of a program's behaviour and simplifies the program to focus exclusively upon this behaviour In order to understand the similarities and differences between slicing techniques, a formal mechanism is required. This paper establishes a formal mechanism for comparing slicing techniques using a theory of program projection. Sets of minimal slices, which form the ideal for any slicing algorithm, are used to reveal the ordering relationship between various static and dynamic slicing techniques