ENHANCING SOFTWARE QUALITY USING ARTIFICIAL NEURAL NETWORKS TO SUPPORT SOFTWARE REFACTORING / (Record no. 383358)
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000 -LEADER | |
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fixed length control field | 02554nam a2200229 4500 |
003 - CONTROL NUMBER IDENTIFIER | |
control field | APU |
005 - DATE AND TIME OF LATEST TRANSACTION | |
control field | 20230626103020.0 |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
fixed length control field | 200227b2019 ||||| |||| 00| 0 eng d |
050 ## - LIBRARY OF CONGRESS CALL NUMBER | |
Classification number | PM-32-14 |
100 0# - MAIN ENTRY--PERSONAL NAME | |
Personal name | PARVEENA SANDRASEGARAN (TP039382) |
9 (RLIN) | 45476 |
245 10 - TITLE STATEMENT | |
Title | ENHANCING SOFTWARE QUALITY USING ARTIFICIAL NEURAL NETWORKS TO SUPPORT SOFTWARE REFACTORING / |
Statement of responsibility, etc | PARVEENA SANDRASEGARAN. |
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
Place of publication, distribution, etc | Kuala Lumpur : |
Name of publisher, distributor, etc | Asia Pacific University, |
Date of publication, distribution, etc | 2019. |
300 ## - PHYSICAL DESCRIPTION | |
Extent | xiv, 45 pages : |
Other physical details | illustrations ; |
Dimensions | 30 cm. |
502 ## - DISSERTATION NOTE | |
Dissertation note | A thesis submitted in fulfilment of the requirements for the award of the degree of MSc. in Software Engineering (UCMF1808BSE). |
520 ## - SUMMARY, ETC. | |
Summary, etc | Current trends of software refactoring involve tools and techniques to eliminate code smells that hinder the software from achieving quality goals. This is carried out manually as the developer is required to analyse the system in order to identify how a particular quality attribute is being affected. This approach to software development is inefficient as a majority of software engineers lack this skill and it prolongs the time allocated for the software’s implementation and maintenance. This dissertation outlines the need for Artificial Neural Networks (ANN) to support software refactoring in order to enhance the system’s quality. This justification is emphasized by means of illustrating the issues that arise when software quality is affected by the presence of code smells that have been overlooked by the developers. By adhering to a research methodology that comprises of SEVEN major phases, an ANN model is able to measure software quality in terms of efficiency, maintainability, and reusability. This calculation is based on inputs that are generated through SciTools whereby an application is decomposed into metric parameters such as Cyclomatic Complexity (CC). The results of the quality of ELEVEN JAVA projects were quantified in order to further analyse patterns of code smells; this provides an insight on how the model may be utilized to enhance software quality. Furthermore, the performance of the model is evaluated relative to other Machine Learning (ML) models. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Computer software |
9 (RLIN) | 45477 |
General subdivision | Development. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Software refactoring. |
9 (RLIN) | 46691 |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name as entry element | Neural networks (Computer science). |
9 (RLIN) | 46653 |
700 0# - ADDED ENTRY--PERSONAL NAME | |
Personal name | Dr. Sivakumar Vengusamy |
Relator term | Supervisor. |
-- | 48429 |
856 40 - ELECTRONIC LOCATION AND ACCESS | |
Uniform Resource Identifier | https://cas.apiit.edu.my/cas/login?service=https://library.apu.edu.my/apres/ |
Link text | Available in APres |
Public note | - Requires login to view full text. |
942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
Source of classification or shelving scheme | |
Koha item type | Masters Theses |
Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Use restrictions | Not for loan | Collection code | Home library | Current library | Shelving location | Date acquired | Full call number | Barcode | Date last seen | Copy number | Koha item type | Public note |
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Not Withdrawn | Available | Not Damaged | Restricted access | Not for loan | Masters Theses | APU Library | APU Library | Reference Collection | 15/12/2020 | PM-32-14 | 00018473 | 15/12/2020 | 1 | Reference | Available in APres |