Abstract Program Slicing: an Abstract Interpretation-based approach to Program Slicing

In the present paper we formally define the notion of abstract program slicing, a general form of program slicing where properties of data are considered instead of their exact value. This approach is applied to a language with numeric and reference values, and relies on the notion of abstract dependencies between program components (statements). The different forms of (backward) abstract slicing are added to an existing formal framework where traditional, non-abstract forms of slicing could be compared. The extended framework allows us to appreciate that abstract slicing is a generalization of traditional slicing, since traditional slicing (dealing with syntactic dependencies) is generalized by (semantic) non-abstract forms of slicing, which are actually equivalent to an abstract form where the identity abstraction is performed on data. Sound algorithms for computing abstract dependencies and a systematic characterization of program slices are provided, which rely on the notion of agreement between program states

Making Slicing Mainstream How can we be Weiser?

By now, the concept of program slicing has been known in the research community for around 25 years. As a research topic, it has enjoyed a fair share of popularity, evidenced by the number of articles published on the topic following Mark Weiser\u27s seminal paper. However, outside research circles, program slicing appears to be virtually unknown. In this report, we take the premise that program slicing is both technically relevant, and has a sufficient theoretical foundation, to be applied in practice within the software industry. With this premise in mind, we ask ourselves, ``what are the mechanisms by which we as a community could make program slicing mainstream\u27\u27

Node coarsening calculi for program slicing

Several approaches to reverse and re-engineering are based upon program slicing. Unfortunately, for large systems, such as those which typically form the subject of reverse engineering activities, the space and time requirements of slicing can be a barrier to successful application. Faced with this problem, several authors have found it helpful to merge control flow graph (CFG) nodes, thereby improving the space and time requirements of standard slicing algorithms. The node-merging process essentially creates a 'coarser' version of the original CFG. The paper introduces a theory for defining control flow graph node coarsening calculi. The theory formalizes properties of interest, when coarsening is used as a precursor to program slicing. The theory is illustrated with a case study of a coarsening calculus, which is proved to have the desired properties of sharpness and consistency

Program slicing by calculation

Program slicing is a well known family of techniques used to identify code fragments which depend on or are depended upon specific program entities. They are particularly useful in the areas of reverse engineering, program understanding, testing and software maintenance. Most slicing methods, usually oriented towards the imperatice or object paradigms, are based on some sort of graph structure representing program dependencies. Slicing techniques amount, therefore, to (sophisticated) graph transversal algorithms. This paper proposes a completely different approach to the slicing problem for functional programs. Instead of extracting program information to build an underlying dependencies' structure, we resort to standard program calculation strategies, based on the so-called Bird-Meertens formalism. The slicing criterion is specified either as a projection or a hiding function which, once composed with the original program, leads to the identification of the intended slice. Going through a number of examples, the paper suggests this approach may be an interesting, even if not completely general, alternative to slicing functional programsFundação para a Ciência e a Tecnologia (FCT

A Survey on Program Slicing

Program slicing is an important technique for untangling programs by only focusing on selected aspects of semantics. The processing flow of slicing deletes those parts of the program that have no effect upon the semantics that are required to execute. For program slicing it is important to understand the important aspects that are related to execution and relationship of variable involved in the program. Slicing has applications in software maintenance, testing and debugging. Program slicing is a process of extracting parts of programs by tracing the programs in which the main task is to find out all statements in a program that directly or indirectly influence the value of a variable at some point in a program. In proposed paper a detailed survey is done on various slicing techniques and understanding the applications in various areas such as debugging, program comprehension and understanding, program integration

Safe Concurrency Introduction through Slicing

Traditional refactoring is about modifying the structure of existing code without changing its behaviour, but with the aim of making code easier to understand, modify, or reuse. In this paper, we introduce three novel refactorings for retrofitting concurrency to Erlang applications, and demonstrate how the use of program slicing makes the automation of these refactorings possible

Field-Sensitive Program Slicing

The granularity level of the program dependence graph (PDG) for composite data structures (tuples, lists, records, objects, etc.) is inaccurate when slicing their inner elements. We present the constrained-edges PDG (CE-PDG) that addresses this accuracy problem. The CE-PDG enhances the representation of composite data structures by decomposing statements into a subgraph that represents the inner elements of the structure, and the inclusion and propagation of data constraints along the CE-PDG edges allows for accurate slicing of complex data structures. Both extensions are conservative with respect to the PDG, in the sense that all slicing criteria (and more) that can be specified in the PDG can be also specified in the CE-PDG, and the slices produced with the CE-PDG are always smaller or equal to the slices produced by the PDG. An evaluation of our approach shows a reduction of the slices of 11.67%/5.49% for programs without/with loops