An Analysis of the Current Program Slicing and Algorithmic Debugging Based Techniques

This thesis presents a classification of program slicing based techniques. The classification allows us to identify the differences between existing techniques, but it also allows us to predict new slicing techniques. The study identifies and compares the dimensions that influence current techniques.Silva Galiana, JF. (2008). An Analysis of the Current Program Slicing and Algorithmic Debugging Based Techniques. http://hdl.handle.net/10251/14300Archivo delegad

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

A Denotational Interprocedural Program Slicer

This paper extends a previously developed intraprocedural denotational program slicer to handle procedures. Using the denotational approach, slices can be defined in terms of the abstract syntax of the object language without the need of a control flow graph or similar intermediate structure. The algorithm presented here is capable of correctly handling the interplay between function and procedure calls, side-effects, and short-circuit expression evaluation. The ability to deal with these features is required in reverse engineering of legacy systems, where code often contains side-effects

A Change Impact Analysis to Characterize Evolving Program Behaviors

Change impact analysis techniques estimate the potential effects of changes made to software. Directed Incremental Symbolic Execution (DiSE) is an intraprocedural technique for characterizing the impact of software changes on program behaviors. DiSE first estimates the impact of the changes on the source code using program slicing techniques, and then uses the impact sets to guide symbolic execution to generate path conditions that characterize impacted program behaviors. DiSE, however, cannot reason about the flow of impact between methods and will fail to generate path conditions for certain impacted program behaviors. In this work, we present iDiSE, an extension to DiSE that performs an interprocedural analysis. iDiSE combines static and dynamic calling context information to efficiently generate impacted program behaviors across calling contexts. Information about impacted program behaviors is useful for testing, verification, and debugging of evolving programs. We present a case-study of our implementation of the iDiSE algorithm to demonstrate its efficiency at computing impacted program behaviors. Traditional notions of coverage are insufficient for characterizing the testing efforts used to validate evolving program behaviors because they do not take into account the impact of changes to the code. In this work we present novel definitions of impacted coverage metrics that are useful for evaluating the testing effort required to test evolving programs. We then describe how the notions of impacted coverage can be used to configure techniques such as DiSE and iDiSE in order to support regression testing related tasks. We also discuss how DiSE and iDiSE can be configured for debugging finding the root cause of errors introduced by changes made to the code. In our empirical evaluation we demonstrate that the configurations of DiSE and iDiSE can be used to support various software maintenance task

Understanding Program Slices

Program slicing is a useful analysis for aiding different software engineering activities. In the past decades, various notions of program slices have been evolved as well as a number of methods to compute them. By now program slicing has numerous applications in software maintenance, program comprehension, reverse engineering, program integration, and software testing. Usability of program slicing for real world programs depends on many factors such as precision, speed, and scalability, which have already been addressed in the literature. However, only a little attention has been brought to the practical demand: when the slices are large or difficult to understand, which often occur in the case of larger programs, how to give an explanation for the user why a particular element has been included in the resulting slice. This paper describes a reasoning method about elements of static program slices

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