Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/452901
Title: | Refactoring Opportunity Identification and Sequencing Using Dynamic Analysis |
Researcher: | Satnam Kaur |
Guide(s): | A. L. Sangal |
Keywords: | Computer Science Computer Science Artificial Intelligence Engineering and Technology |
University: | Dr B R Ambedkar National Institute of Technology Jalandhar |
Completed Date: | 2021 |
Abstract: | Software systems have become prevalent and significant in our today s society. newlineConsequently, these systems are becoming the core business of many software newlineindustries and are developed considering several design principles during their newlinedesign phase to stay competitive in the market. However, during maintenance, newlinethese systems are subjected to the frantic modifications every day with respect newlineto introduction of new functionalities or correction of bugs. While making these newlineamendments, developers do not execute ideal solutions due to the strict project newlinedeadlines and limited resources, which leads to the origin of code smells. newlineCode smells are structural characteristics of software that indicate design problems newlinein the source code. These smells put a negative impact on design quality and are newlineeradicated by the right choice of refactoring activities. Refactoring improves design newlinestructure of a software while preserving its external behavior. In object-oriented newlinecommunity, several studies highlighted the positive aspects of refactoring in terms newlineof its impact on internal as well as external software quality attributes. On newlinecontrary, many researchers identified the negative effects of refactoring activities on newlinesoftware extendibility, maintainability and readability while decreasing the speed newlineat which the programmers can write and maintain their code in the optimal newlineformat. To close this research gap, in the first part of this dissertation, we perform newlinea profound systematic mapping study that identifies, assesses, and presents the newlineavailable empirical literature concerning the impact of refactoring activities on newlinesoftware quality, with the aim of specifying the current state of the art along newlinewith the identification of potential open challenges. Our findings indicate that newlinethe refactoring activities have variable effects on most of the quality attributes, newlineindicating that refactoring does not always improve all quality attributes. newlineMoreover, we thoroughly analysed the literature specific to refactoring opportunity newlineid |
Pagination: | |
URI: | http://hdl.handle.net/10603/452901 |
Appears in Departments: | Department of Computer Science and Engineering |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
80_recommendation.pdf | Attached File | 669.36 kB | Adobe PDF | View/Open |
abstract.pdf | 238.22 kB | Adobe PDF | View/Open | |
chapter 1.pdf | 4.74 MB | Adobe PDF | View/Open | |
chapter 2.pdf | 426.29 kB | Adobe PDF | View/Open | |
chapter 3.pdf | 26.34 MB | Adobe PDF | View/Open | |
chapter 4.pdf | 4.82 MB | Adobe PDF | View/Open | |
chapter 5 6 7.pdf | 22.34 MB | Adobe PDF | View/Open | |
contents.pdf | 402.4 kB | Adobe PDF | View/Open | |
prelim.pdf | 557.65 kB | Adobe PDF | View/Open | |
references.pdf | 308.75 kB | Adobe PDF | View/Open | |
title.pdf | 322.83 kB | Adobe PDF | View/Open |
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