Results 11 to 20 of about 161,467 (336)
Security Code Smells in Android ICC [PDF]
Android Inter-Component Communication (ICC) is complex, largely unconstrained, and hard for developers to understand. As a consequence, ICC is a common source of security vulnerability in Android apps.
Frischknecht, Patrick +3 more
core +4 more sources
An empirical investigation into code smells rectifications through ADA_BOOSTER
Object Oriented Programming has become one of the most established paradigms. It offers us features like encapsulation, polymorphism, inheritance etc. By using these features we are able to develop good software’s that are easy to understand.
M. Sangeetha, C. Chandrasekar
doaj +2 more sources
Android code smells: From introduction to refactoring [PDF]
Object-oriented code smells are well-known concepts in software engineering that refer to bad design and development practices commonly observed in software systems. With the emergence of mobile apps, new classes of code smells have been identified by the research community as mobile-specific code smells.
Sarra Habchi, Naouel Moha, Romain Rouvoy
openalex +5 more sources
Python code smells detection using conventional machine learning models [PDF]
Code smells are poor code design or implementation that affect the code maintenance process and reduce the software quality. Therefore, code smell detection is important in software building.
Rana Sandouka, Hamoud Aljamaan
doaj +2 more sources
Code Smell Detection Driven by Hybrid Feature Selection and Ensemble Learning [PDF]
Code smell is a software feature that violates basic design principles or coding standards.When introduced into a source code, code smell increases the cost and difficulty of its maintenance.Machine learning can outperform other code smell detection ...
AI Chenghao, GAO Jianhua, HUANG Zijie
doaj +1 more source
Assessing code smell interest probability [PDF]
An important parameter in deciding to eliminate technical debt (TD) is the probability of a module to generate interest along software evolution. In this study, we explore code smells, which according to practitioners are the most commonly occurring type of TD in industry, by assessing the associated interest probability.
Charalampidou, Sofia +3 more
openaire +1 more source
Detection of Bad Smell in Code Based on BP Neural Network [PDF]
Bad smells in code seriously affect the quality of software and its maintenance.To address the low accuracy of machine learning algorithms in bad smell detection and the single type of bad smell dataset,this paper proposes a detection method for bad ...
WANG Shuyan, ZHANG Yiquan, SUN Jiaze
doaj +1 more source
Olfactory Coding: When Smells Collide [PDF]
Brain responses can significantly outlast sensory stimuli leading to potential ambiguity when responses overlap. Recent studies of locust olfaction found that the responses of individual second order projection neurons depend markedly on the previous few seconds' stimulus history; the population response, however, still conveys information about both ...
Antolin, Salomé +1 more
openaire +2 more sources
Evaluasi Deteksi Smell Code dan Anti Pattern pada Aplikasi Berbasis Java
This paper presents an evaluation result of smell code and anti pattern detection in java based application development. The main objective to be achieved in this research is to determine the proper way in the detection of smell code and anti pattern in ...
Sendy Ferdian Sujadi
doaj +1 more source
Do Missing Link Community Smell Affect Developers Productivity: An Empirical Study
Missing link smell occurs when developers contribute to the same source code without communicating with each other. Existing studies have analyzed the relationship of missing link smells with code smell and developer contribution.
Toukir Ahammed +2 more
doaj +1 more source

