Results 21 to 30 of about 2,448,745 (246)

A Novel Metric based Detection of Temporary Field Code Smell and its Empirical Analysis

open access: yesJournal of King Saud University: Computer and Information Sciences, 2022
Code smell causes side effects in the source code and impact the code quality. It is beneficial to recognize code smells to improve software quality. Despite 22 classical code smells as characterized by Martin Fowler, all classical code smells have not ...
Ruchin Gupta, Sandeep Kumar Singh
doaj   +1 more source

Does Code Smell Frequency Have a Relationship with Fault-proneness? [PDF]

open access: yesInternational Conference on Evaluation & Assessment in Software Engineering, 2023
Fault-proneness is an indication of programming errors that decreases software quality and maintainability. On the contrary, code smell is a symptom of potential design problems which has impact on fault-proneness.
Md. Masudur Rahman   +3 more
semanticscholar   +1 more source

On the relative value of imbalanced learning for code smell detection

open access: yesSoftware, Practice & Experience, 2023
Machine learning‐based code smell detection (CSD) has been demonstrated to be a valuable approach for improving software quality and enabling developers to identify problematic patterns in code. However, previous researches have shown that the code smell
Fuyang Li   +5 more
semanticscholar   +1 more source

How to Improve Deep Learning for Software Analytics (a case study with code smell detection) [PDF]

open access: yesIEEE Working Conference on Mining Software Repositories, 2022
To reduce technical debt and make code more maintainable, it is important to be able to warn programmers about code smells. State-of-the-art code small detectors use deep learners, usually without exploring alternatives.
Rahul Yedida, T. Menzies
semanticscholar   +1 more source

Evaluasi Deteksi Smell Code dan Anti Pattern pada Aplikasi Berbasis Java

open access: yesJuTISI (Jurnal Teknik Informatika dan Sistem Informasi), 2020
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

open access: yesKnowledge Engineering and Data Science, 2021
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

On the Assessment of Interactive Detection of Code Smells in Practice: A Controlled Experiment

open access: yesIEEE 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
doaj   +1 more source

Security‐based code smell definition, detection, and impact quantification in Android

open access: yesSoftware, Practice & Experience, 2023
Android's high market share and extensive functionality make its security a significant concern. Research reveals that many security issues are caused by insecure coding practices.
Yi Zhong   +4 more
semanticscholar   +1 more source

Security code smells in Android ICC [PDF]

open access: yesEmpirical Software Engineering, 2018
Accepted on 28 Nov 2018, Empirical Software Engineering Journal (EMSE ...
Pascal Gadient   +3 more
openaire   +5 more sources

Code smells for machine learning applications

open access: yesProceedings of the 1st International Conference on AI Engineering: Software Engineering for AI, 2022
The popularity of machine learning has wildly expanded in recent years. Machine learning techniques have been heatedly studied in academia and applied in the industry to create business value. However, there is a lack of guidelines for code quality in machine learning applications.
Zhang, H. (author)   +2 more
openaire   +3 more sources

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