An Empirical Analysis for Predicting Source Code File Reusability Using Meta-Classification Algorithms

2018 ◽  
pp. 493-504
Author(s):  
Loveleen Kaur ◽  
Ashutosh Mishra
Keyword(s):  
Empirical Analysis ◽  
Source Code ◽  
Classification Algorithms

scholarly journals An Empirical Analysis on Effectiveness of Source Code Metrics for Aging Related Bug Prediction

2019 ◽  
Vol 2019 (2) ◽  
pp. 117-126
Author(s):  
Chinmay Hota ◽  
Lov Kumar ◽  
Lalita Bhanu Murthy Neti
Keyword(s):  
Empirical Analysis ◽  
Source Code ◽  
Code Metrics ◽  
Source Code Metrics

AN EMPIRICAL ANALYSIS OF THE OPEN SOURCE DEVELOPMENT PROCESS BASED ON MINING OF SOURCE CODE REPOSITORIES

2007 ◽  
Vol 17 (02) ◽  
pp. 231-247 ◽  
Author(s):  
MARCO SCOTTO ◽  
ALBERTO SILLITTI ◽  
GIANCARLO SUCCI
Keyword(s):  
Open Source ◽  
Empirical Analysis ◽  
Open Source Software ◽  
Development Process ◽  
Source Code ◽  
Point Of View ◽  
Show Evidence ◽  
Recurrent Patterns ◽  
Development Application ◽  
Open Source Development

This paper presents an empirical analysis of the Open Source development process from the point of view of the involvement of the developers in the production process. The study focuses on how developers contribute to projects in terms of involvement, size and kind of their contribution. Data have been collected from 53 Open Source projects and target application domains include different areas: web and application servers, databases, operating systems, and window managers. Collected data include the number of developers, patterns of code modifications, and evolution over the time of size and complexity. The results of this study show evidence that there are recurrent patterns in Open Source software development and these patterns are common to all the projects considered even if there are no superimposed processes for development, application domains are different, and there are contributions from people spread across the world.

An Empirical Analysis on the Prediction of Web Service Anti-patterns Using Source Code Metrics and Ensemble Techniques

2021 ◽  
pp. 263-276
Author(s):  
Sahithi Tummalapalli ◽  
Juhi Mittal ◽  
Lov Kumar ◽  
Lalitha Bhanu Murthy Neti ◽  
Santanu Kumar Rath
Keyword(s):  
Web Service ◽  
Empirical Analysis ◽  
Source Code ◽  
Ensemble Techniques ◽  
Code Metrics ◽  
Source Code Metrics

scholarly journals Empirical Analysis of Re-Factoring Techniques

2021 ◽  
Vol 9 (11) ◽  
pp. 1274-1280
Author(s):  
Dendi Naishika Reddy
Keyword(s):  
Comparative Analysis ◽  
Empirical Study ◽  
Empirical Analysis ◽  
Source Code ◽  
Software Project ◽  
Functional Attributes ◽  
Complete Knowledge ◽  
Negative Impacts ◽  
Internal Architecture

Abstract: The process or technique of Code Re-factoring is restructuring the existing source code by making changes in factoring without any changes in external behaviour. The main intention of re-factoring is to improve non-functional attributes of the software. The advantages include improving the code readability and reducing the complexity of any given source code, and these can overall enhance code maintainability and produce a much more elaborated internal architecture or objectoriented model to boost the extensibility of the code. The effect that re-factoring has on any software project is analysable and customisable. But, before customising the factoring techniques, it is essential to have a complete knowledge of all possible refactoring techniques, and all its possible effects. Our main focus will be on few main re-factoring techniques like Red-Green refactoring, preparatory re-factoring, Abstraction re-factoring, composing methods re-factoring etc. Every software project has both internal and external attributes, that highly influence the software’s maintainability, reusability, understandability, flexibility, testability, extensibility, reliability, efficiency, modularity, complexity and composition. The research mainly focuses on the effect of re-factoring on them. Study of researched data will give us comparative analysis, pointing out both the positive and negative impacts, re-factoring can have. Overall, the project aims to perform an empirical study to find out the impacts of refactoring techniques. The research aims to explore the change in the quality of the code after re-factoring. Improvement, decrement and stability are analysed. Study is also done to find the possibilities of applying more than one re-factoring techniques, independently or in an aggregation. Keywords: maintainability; extensibility; reliability; modularity

Source code

2004 ◽  
pp. 236-252
Keyword(s):  
Source Code

Spectral and Topographic Microstructure of Brain Alpha Activity During Drowsiness at Sleep Onset and REM Sleep

2000 ◽  
Vol 14 (3) ◽  
pp. 151-158 ◽  
Author(s):  
José Luis Cantero ◽  
Mercedes Atienza
Keyword(s):  
Rem Sleep ◽  
Spectral Component ◽  
Sleep Onset ◽  
Quantitative Information ◽  
Maximum Energy ◽  
Alpha Activity ◽  
The Other ◽  
Classification Algorithms ◽  
Microstructural Properties ◽  
Brain States

Abstract High-resolution frequency methods were used to describe the spectral and topographic microstructure of human spontaneous alpha activity in the drowsiness (DR) period at sleep onset and during REM sleep. Electroencephalographic (EEG), electrooculographic (EOG), and electromyographic (EMG) measurements were obtained during sleep in 10 healthy volunteer subjects. Spectral microstructure of alpha activity during DR showed a significant maximum power with respect to REM-alpha bursts for the components in the 9.7-10.9 Hz range, whereas REM-alpha bursts reached their maximum statistical differentiation from the sleep onset alpha activity at the components between 7.8 and 8.6 Hz. Furthermore, the maximum energy over occipital regions appeared in a different spectral component in each brain activation state, namely, 10.1 Hz in drowsiness and 8.6 Hz in REM sleep. These results provide quantitative information for differentiating the drowsiness alpha activity and REM-alpha by studying their microstructural properties. On the other hand, these data suggest that the spectral microstructure of alpha activity during sleep onset and REM sleep could be a useful index to implement in automatic classification algorithms in order to improve the differentiation between the two brain states.

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