Static Slicing of Interprocedural Programs

Program slicing has many applications in a software development environment such as debugging, testing, anomaly detection, program understanding and many more. The concept being introduced by Weiser and it was started with static slicing calculation. Talking about static slicing, it is a subset of statements of a program which directly or indirectly affect the values of the variables computed providing a slicing criterion. In this project, we have developed an approach for creating an intermediate representation of a program in the form of System Dependence Graph (SDG) which is to be, again taken as input for computing the slicing of a program with respect to slicing criterion. The slicing approach computes the slices with respect to a given slicing criterion. For generating the graph, we have analysed the input program, identified the tokens and finally generated the relation between tokens as data dependent or control dependent. For calculating the slice, we have used two-phase graph reachability algorithm developed by Horwitz, Reps and Binkley, which creates a graph consisting of only those nodes that are dependent on slicing criterion. Finally we have plotted a graph between time taken to create graph versus number of functions used in program. Our approach of calculating slices has been limited only to C programs

Extracting Reusable Functions by Program Slicing

An alternative approach to developing reusable components from scratch is to recover them from existing systems. In this paper, we apply program slicing, introduced by Weiser, to the problem of extracting reusable functions from ill-structured programs. 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 neither the statements necessary to get input data nor 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 demonstrate 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. (Also cross-referenced as UMIACS-TR-96-13

Test Case Purification for Improving Fault Localization

Finding and fixing bugs are time-consuming activities in software development. Spectrum-based fault localization aims to identify the faulty position in source code based on the execution trace of test cases. Failing test cases and their assertions form test oracles for the failing behavior of the system under analysis. In this paper, we propose a novel concept of spectrum driven test case purification for improving fault localization. The goal of test case purification is to separate existing test cases into small fractions (called purified test cases) and to enhance the test oracles to further localize faults. Combining with an original fault localization technique (e.g., Tarantula), test case purification results in better ranking the program statements. Our experiments on 1800 faults in six open-source Java programs show that test case purification can effectively improve existing fault localization techniques

ConSUS: A light-weight program conditioner

Program conditioning consists of identifying and removing a set of statements which cannot be executed when a condition of interest holds at some point in a program. It has been applied to problems in maintenance, testing, re-use and re-engineering. All current approaches to program conditioning rely upon both symbolic execution and reasoning about symbolic predicates. The reasoning can be performed by a ‘heavy duty’ theorem prover but this may impose unrealistic performance constraints. This paper reports on a lightweight approach to theorem proving using the FermaT Simplify decision procedure. This is used as a component to ConSUS, a program conditioning system for the Wide Spectrum Language WSL. The paper describes the symbolic execution algorithm used by ConSUS, which prunes as it conditions. The paper also provides empirical evidence that conditioning produces a significant reduction in program size and, although exponential in the worst case, the conditioning system has low degree polynomial behaviour in many cases, thereby making it scalable to unit level applications of program conditioning

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

Amorphous slicing of extended finite state machines

Slicing is useful for many Software Engineering applications and has been widely studied for three decades, but there has been comparatively little work on slicing Extended Finite State Machines (EFSMs). This paper introduces a set of dependency based EFSM slicing algorithms and an accompanying tool. We demonstrate that our algorithms are suitable for dependence based slicing. We use our tool to conduct experiments on ten EFSMs, including benchmarks and industrial EFSMs. Ours is the first empirical study of dependence based program slicing for EFSMs. Compared to the only previously published dependence based algorithm, our average slice is smaller 40% of the time and larger only 10% of the time, with an average slice size of 35% for termination insensitive slicing