An Empirical Evaluation of Ensemble Models for Python Code Smell Detection [PDF]
Applied SciencesCode smells, which represent poor design choices or suboptimal code implementations, reduce software quality and hinder the code maintenance process. Detecting code smells is, therefore, essential during software development.
Rajwant Singh Rao +2 more
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Automated Code-Smell Detection in Microservices Through Static Analysis: A Case Study
Applied Sciences, 2020 Microservice Architecture (MSA) is becoming the predominant direction of new cloud-based applications. There are many advantages to using microservices, but also downsides to using a more complex architecture than a typical monolithic enterprise ...
Andrew Walker, Dipta Das, Tomas Cerny
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Towards Semantic Detection of Smells in Cloud Infrastructure Code [PDF]
Proceedings of the 10th International Conference on Web Intelligence, Mining and Semantics, 2020 Automated deployment and management of Cloud applications relies on descriptions of their deployment topologies, often referred to as Infrastructure Code. As the complexity of applications and their deployment models increases, developers inadvertently introduce software smells to such code specifications, for instance, violations of good coding ...
Indika Kumara +7 more
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Identifying co-occurrences of message chains and member ignoring method in android applications using static program analysis and dynamic stacking ensemble [PDF]
Scientific ReportsThe co-occurrence of multiple code smells in Android applications poses a more serious threat to software maintainability and stability than individual smells. However, most existing studies still concentrate on detecting single types of smells.
Zhichao Ma +3 more
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IEEE AccessHyperparameter optimization plays a pivotal role in the reliability and generalization of machine-learning models for software quality prediction. This paper presents a comparative evaluation of three search strategies: Grid Search, Random Search, and a ...
Marcela Mosquera +2 more
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Optimizing Pre-Trained Code Embeddings With Triplet Loss for Code Smell Detection
IEEE AccessCode embedding represents code semantics in vector form. Although code embedding-based systems have been successfully applied to various source code analysis tasks, further research is required to enhance code embedding for better code analysis ...
Ali Nizam +3 more
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Enhancing Software Quality with AI: A Transformer-Based Approach for Code Smell Detection [PDF]
Applied SciencesSoftware quality assurance is a critical aspect of software engineering, directly impacting maintainability, extensibility, and overall system performance.
Israr Ali +2 more
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Code Smell Detection Driven by Hybrid Feature Selection and Ensemble Learning [PDF]
Jisuanji gongcheng, 2022 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
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Detection of Bad Smell in Code Based on BP Neural Network [PDF]
Jisuanji gongcheng, 2020 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
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On the Assessment of Interactive Detection of Code Smells in Practice: A Controlled Experiment
IEEE Access, 2023 Code smells are structures in a program that often indicate the presence of deeper maintainability problems. Code smells should be detected as soon as they are introduced, enabling refactoring actions with less effort and time. Non-Interactive Detection (
Danyllo Albuquerque +6 more
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