Dynamic slicing of concurrent AspectJ programs: An explicit context‐sensitive approach

Summary This paper presents a context‐sensitive dynamic slicing technique for the concurrent and aspectized programs. To effectively represent the concurrent aspect‐oriented programs, we propose an intermediate graph called the multithreaded aspect‐oriented dependence graph (MAODG). The MAODG is a d...

Full description

Saved in:
Bibliographic Details
Published in:Software, practice & experience Vol. 48; no. 1; pp. 233 - 260
Main Authors: Singh, Jagannath, Mohapatra, Durga Prasad
Format: Journal Article
Language:English
Published: Bognor Regis Wiley Subscription Services, Inc 01.01.2018
Subjects:
Algorithms
Aspect‐oriented programming
Computer programs
concurrent aspect
concurrent programming
context‐sensitive slicing
dynamic slicing
Experimentation
Interference
program slicing
Slicing
Software engineering
Source programs
ISSN:0038-0644, 1097-024X
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Summary This paper presents a context‐sensitive dynamic slicing technique for the concurrent and aspectized programs. To effectively represent the concurrent aspect‐oriented programs, we propose an intermediate graph called the multithreaded aspect‐oriented dependence graph (MAODG). The MAODG is a dynamic graph generated from the execution trace of a given program with respect to a particular set of values given as an input. Interference dependencies between the statements are shown by a distinguished edge called the interference dependence edge in the MAODG. Based on this intermediate representation, we propose a precise and accurate dynamic slicing algorithm for the concurrent aspect‐oriented programs implemented using AspectJ. The proposed dynamic slicing algorithm is implemented in a slicing tool developed using the ASM framework. Several open source programs are studied and evaluated using the proposed technique along with some existing techniques. The experimentation shows that our proposed slicing algorithm generates slices of the same or smaller size, as compared with the existing algorithms. Furthermore, we found that the slice computation time is significantly less in our proposed algorithm, as compared with the existing algorithms.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0038-0644
1097-024X
DOI:10.1002/spe.2520