scholarly journals Neural Network based Refactoring Area Identification in Software System with Object Oriented Metrics

2016 ◽  
Vol 9 (10) ◽  
Author(s):  
Jaspreet Kaur ◽  
Satwinder Singh
Keyword(s):  
Neural Network ◽  
Object Oriented ◽  
Software System ◽  
Object Oriented Metrics

scholarly journals Maintainability Evaluation for Object Oriented Software Metrics Using Tool Cohesion Inheritance (COIN)

2021 ◽  
Vol 12 (1S) ◽  
pp. 233-238
Author(s):  
Amit Sharma, Et. al.
Keyword(s):  
Software Development ◽  
Software Metrics ◽  
Object Oriented ◽  
Software System ◽  
Development Cost ◽  
Modern Era ◽  
Object Oriented Metrics

In modern era, maintainability is an important part for software development that covers approx. 70-75% of development cost of the software system. It can allow the customer to adapt the software quickly and easily in an agile manner. Object oriented software metrics plays an important role for the designing of software development. Its features can be categorized into the object oriented metrics and the hierarchies of the class. In this paper, a tool named as COIN can help for evaluating the maintainability factors of object oriented software system using metrics like cohesion, coupling, inheritance and other object oriented metrics as well as through which we can analyzed the all metrics for the software system for evaluating the maintainability factors and testability also.

scholarly journals Finding Bad Code Smells with Neural Network Models

2017 ◽  
Vol 7 (6) ◽  
pp. 3613 ◽  
Author(s):  
Dong Kwan Kim
Keyword(s):  
Neural Network ◽  
Network Model ◽  
Software Maintenance ◽  
Detection System ◽  
Object Oriented ◽  
Network Models ◽  
Training Dataset ◽  
Neural Network Models ◽  
Code Smell ◽  
Object Oriented Metrics

Code smell refers to any symptom introduced in design or implementation phases in the source code of a program. Such a code smell can potentially cause deeper and serious problems during software maintenance. The existing approaches to detect bad smells use detection rules or standards using a combination of different object-oriented metrics. Although a variety of software detection tools have been developed, they still have limitations and constraints in their capabilities. In this paper, a code smell detection system is presented with the neural network model that delivers the relationship between bad smells and object-oriented metrics by taking a corpus of Java projects as experimental dataset. The most well-known object-oriented metrics are considered to identify the presence of bad smells. The code smell detection system uses the twenty Java projects which are shared by many users in the GitHub repositories. The dataset of these Java projects is partitioned into mutually exclusive training and test sets. The training dataset is used to learn the network model which will predict smelly classes in this study. The optimized network model will be chosen to be evaluated on the test dataset. The experimental results show when the modelis highly trained with more dataset, the prediction outcomes are improved more and more. In addition, the accuracy of the model increases when it performs with higher epochs and many hidden layers.

CODE CLONE DETECTION USING OBJECT ORIENTED METRICS

2020 ◽  
Vol 9 (6) ◽  
pp. 3925-3931
Author(s):  
S. Sharma ◽  
D. Rattan ◽  
K. Singh
Keyword(s):  
Object Oriented ◽  
Clone Detection ◽  
Code Clone ◽  
Object Oriented Metrics

Applying object-oriented metrics to Ada 95

1996 ◽  
Vol XVI (5) ◽  
pp. 48-58 ◽  
Author(s):  
William W. Pritchett
Keyword(s):  
Object Oriented ◽  
Ada 95 ◽  
Object Oriented Metrics

Applicability of Weyuker's Property 9 to object oriented metrics

2006 ◽  
Vol 32 (3) ◽  
pp. 209-211 ◽  
Author(s):  
Naveen Sharma ◽  
Padmaja Joshi ◽  
R.K. Joshi
Keyword(s):  
Object Oriented ◽  
Object Oriented Metrics
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