CCE Theses and Dissertations
Date of Award
2016
Document Type
Dissertation
Degree Name
Doctor of Philosophy in Computer Science (CISD)
Department
College of Engineering and Computing
Advisor
Francisco J. Mitropoulos
Committee Member
Renata Rand McFadden
Committee Member
Sumitra Mukherjee
Keywords
Aspect mining, Computer science
Abstract
Aspect oriented programming languages provide a new enhanced composition mechanism between the functional sub units as compared to earlier non aspect oriented languages. For this reason the refactoring process requires a new approach to the analysis of existing code that focuses on how the functions cross cut one another. Aspect mining is a process of studying an existing program in order to find these cross cutting functions or concerns so they may be implemented using new aspect oriented constructs and thus reduce the complexity of the existing code. One approach to the detection of these cross cutting concerns generates a method call tree that outlines the method calls made within the existing code. The call tree is then examined to find recurring patterns of methods that can be symptoms of cross cutting concerns. The conducted research focused on enhancing this approach to detect and quantify cross cutting concerns that are a result of code tangling as well as code scattering. The conducted research also demonstrates how this aspect mining approach can be used to overcome the difficulties in detection caused by variations in the coding structure introduced by over time.
NSUWorks Citation
Saleem Obaidullah Mir. 2016. Enhanced Method Call Tree for Comprehensive Detection of Symptoms of Cross Cutting Concerns. Doctoral dissertation. Nova Southeastern University. Retrieved from NSUWorks, College of Engineering and Computing. (962)
https://nsuworks.nova.edu/gscis_etd/962.