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....

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.

Program slicing is a technique for automatically identifying all the lines in a program which affect a selected subset of variables. A large program can be divided into a number of smaller programs (its slices), each constructed for different variable subsets. The slices are typically simpler than the original program, thereby simplifying the process of testing a property of the program which only concerns a subset of its variables. Some aspects of a program's computation are not captured by a set of variables, rendering slicing inapplicable. To overcome this difficulty we make a program introspective, adding assignments to denote these `implicit' computations. Initially this makes the program longer. However, slicing can now be applied to the introspective program, forming a slice concerned solely with the implicit computation. We improve the simplification power of slicing using program transformation. To illustrate our approach we consider the implicit computation which ...

Dynamic program slicing methods are widely used for debugging, because many statements can be ignored in the process of localizing a bug. A dynamic program slice wrt a variable contains only those statements that actually had an influence on this variable. However, during debugging we also need to identify those statements that actually did not affect the variable but could have affected it had they been evaluated differently. A relevant slice includes these potentially affecting statements as well, therefore it is appropriate for debugging. In this paper a forward algorithm is introduced for the computation of relevant slices of programs. The space requirement of this method does not depend on the number of different dynamic slices nor on the size of the execution history, hence it can be applied for real size applications. Keywords Dynamic slicing, relevant slicing, debugging 1 INTRODUCTION Program slicing methods are widely used for debugging, testing, reverse engineering and mai...

Program slicing is a viable method to restrict the focus of a task to specific sub-components of a program. Examples of applications include debugging, testing, program comprehension, restructuring, downsizing, and parallelization. This paper discusses different statement deletion based slicing methods, together with algorithms and applications to software engineering.

Many program evolution tasks involve source code that is not modularized as a single unit. Furthermore, the source code relevant to a change task often implements different concerns, or high-level concepts that a developer must consider. Finding and understanding concerns scattered in source code is a difficult task that accounts for a large proportion of the effort of performing program evolution. One possibility to mitigate this problem is to produce textual documentation that describes scattered concerns. However, this approach is impractical because it is costly, and because, as a program evolves, the documentation becomes inconsistent with the source code. The thesis of this dissertation is that a description of concerns, representing program structures and linked to source code, that can be produced cost-effectively during program investigation activities, can help developers perform software evolution tasks more systematically, and on different versions of a system. To validate the claims of this thesis, we have developed a model for a structure, called concern graph, that describes concerns in source code in terms of relations between program elements. The model also defines precisely the notion of inconsistency between a concern graph and the

An alternative approach to developing reusable components from scratch is to recover them from existing systems. In this paper, we apply program slicing, a program decomposition method, to the problem of extracting reusable functions from illstructured programs. As with conventional slicing first described by Weiser, a slice is obtained by iteratively solving data flow equations based on a program flow graph. We extend the definition of program slice to a transform slice, one that includes statements which contribute directly or indirectly to transform a set of input variables into a set of output variables. Unlike conventional program slicing, these statements do not include either the statements necessary to get input data or the statements which test the binding conditions of the function. Transform slicing presupposes the knowledge that a function is performed in the code and its partial specification, only in terms of input and output data. Using domain knowledge we discuss how to formulate expectations of the functions implemented in the code. In addition to the input/output parameters of the function, the slicing criterion depends on an initial statement, which is difficult to obtain for large programs. Using the notions of decomposition slice and concept validation we show how to produce a set of candidate functions, which are independent of line numbers but must be evaluated with respect to the expected behavior. Although human interaction is required, the limited size of candidate functions makes this task easier than looking for the last function instruction in the original source code.

Although many slicing algorithms have been proposed for object-oriented programs, no slicing algorithm has been proposed which can be used to handle the problem of slicing concurrent Java programs correctly. In this paper, we propose a slicing algorithm for concurrent Java programs. To slice concurrent Java programs, we present a dependence-based representation called multithreaded dependence graph, which extends previous dependence graphs, to represent concurrent Java programs. We also show how static slices of a concurrent Java program can be computed efficiently based on its multithreaded dependence graph. 1 Introduction Java is a new object-oriented programming language and has achieved widespread acceptance because it emphasizes portability. Java has multithreading capabilities for concurrent programming. To provide synchronization between asynchronously running threads, the Java language and runtime system uses monitors. Because of the nondeterministic behaviors of concurrent J...

Generic language technology and compiler construction techniques are a prerequisite to build analysis and conversion tools that are needed for the re-engineering of large software systems. We argue that generic language technology is a crucial means to do fundamental re-engineering. Furthermore, we address the issue that the application of compiler construction techniques in re-engineering generates new research questions in the field of compiler construction.