On the Use of Constraints in Dynamic Slicing for Program Debugging

Wotawa, Franz

doi:10.1109/icstw.2011.61

Cited by 2 publications

(2 citation statements)

References 28 publications

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“…A dynamic slice [4] contains all statements that actually affect the value of a variable at a program point for an executable part of the program rather than all statements which behavior is identical. Dynamic Slicing [5] is computed on a given input and computed slice. The idea of dynamic slicing has been also extended for distributed programs.…”

Section: Program Slicingmentioning

confidence: 99%

Extracting Data Invariants from Promela

2018

Proceedings of 2018 the 8th International Workshop on Computer Science and Engineering

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Data Invariants are the essential conditions that hold during the execution of program. In software verification, the data invariants should be assessed to ensure the correctness of the system behavior. Unfortunately, it has been difficult to indicate the data invariants in a given source code. In this paper, we aim to extract relevant data invariants automatically from the Promela source code. The Promela code is typically used as the software modelling language in model checking tool, called SPIN model checker. We exploit the program slicing technique to minimize the Promela source code and track all of the relevant active bound variables to recognize the data invariants in term of their possible and valid bounded values. The data invariants are written in propositions and their temporal logic formula (LTL formula). The resulting data invariants are checked using model checking tool.

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Section: Program Slicingmentioning

confidence: 99%

Extracting Data Invariants from Promela

2018

Proceedings of 2018 the 8th International Workshop on Computer Science and Engineering

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“…The set of statements that can affect the value of a variable at some point in a program is called a program backward slice. In several software engineering applications, such as program debugging and measuring program cohesion and parallelism, several slices are computed at different program points [2]. Program slicing can be static or dynamic.…”

Section: Dynamic Slicingmentioning

confidence: 99%

Identifying the Behavioral Difference using Differential Slicing

Suguna¹,

Chandrasekaran²

2013

IJAIS

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The programmer has to understand the behavior of two similar programs and then identify the execution difference which produces difference in output. When two similar programs are executed under two different environments which shows different behavior in output. The main difference exists in the program behavior is due to two different types of input. This paper proposes differential slicing based on trace alignment algorithm which produces the execution differences and generates a casual difference graph. We implement differential slicing for C# programs and identify the execution difference. The results shows that differential slicing identifies the input difference and casual difference graph reduces the amount of time for the programmers to understand the execution difference. Our experimental results show the proposed differential slicing performs better than existing approach. KeywordsCasual Difference Graph (CDG), Program Dependence Graph (PDG) 1.Introduction:Differential program Analysis is the process of finding two similar programs to determine the behavioral difference between them.Programs are frequently maintained by the programmers who are far removed from software development process. The purpose of modifications in the program development is not always clear. The actual effect on the programs behavior is the presence of a particular part of the program may be unknown,a particular line may be crucial or it may have no effect at all. The previous research shows that difference in behavior is caused by the presence or absence of particular element would help the maintainers in understanding the program. A set of automated techniques is needed to analyze the effect of modifications. We use differential slicing to focus on differences between two similar programs [1]. We proposed a differential slicing for C# programs. It identifies the aligned and disaligned region and generates a casual difference graph. We compare the differential slicing and existing approach and the results are tabulated. Our results also show that differential slicing identifies the input difference and CDG decreases the time and effort needed for an analyst to understand the observed difference. The paper is organized as follows. Section 2 describes the existing differential slicing techniques. Section 3 explains about Dynamic slicing. Section 4 explains about differential slicing. Section 5 describes about slice alignment. Section 6 describes the performance result of differential slicing. Section 7 describes conclusion. Related WorkDifferential program analysis is the task of analyzing two related programs which identified the behavioral difference between them. Joel Winsted et al presents a technique to find an input for which the two programs will produce different outputs ,Thus illustrating the behavioral difference between the two programs [1]. A combination of static and dynamic techniques are used to find the differential inputs. Sumner and Zhang [4] finds the casual path of two executions by first patching the...

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On the Use of Constraints in Dynamic Slicing for Program Debugging

Cited by 2 publications

References 28 publications

Extracting Data Invariants from Promela

Extracting Data Invariants from Promela

Identifying the Behavioral Difference using Differential Slicing

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