Results 21 to 30 of about 2,490,650 (228)
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
doaj +1 more source
Research Trends, Detection Methods, Practices, and Challenges in Code Smell: SLR
IEEE Access, 2023 Context: A code smell indicates a flaw in the design, implementation, or maintenance process that could degrade the software’s quality and potentially cause future disruptions.
Muhammad Anis Al Hilmi +5 more
doaj +1 more source
Detecting Code Smells in React-based Web Apps
Information and Software Technology, 2022 DBR
openalex +3 more sources
Code Smells for Machine Learning Applications [PDF]
2022 IEEE/ACM 1st International Conference on AI Engineering – Software Engineering for AI (CAIN), 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.
Haiyin Zhang, Luís Cruz, A. Deursen
semanticscholar +1 more source
Investigating the Role of Code Smells in Preventive Maintenance [PDF]
Journal of Information Technology Management, 2019 The quest for improving the software quality has given rise to various studies which focus on the enhancement of the quality of software through various processes.
Junaid Ali Reshi, Satwinder Singh
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The Effect of Code Smells on the Relationship Between Design Patterns and Defects
IEEE Access, 2021 The relationship between design patterns and defects was investigated in the literature, but with mixed results. While the majority of studies found the presence of patterns to be positively correlated with defects, other works reported the opposite ...
Tarek Alkhaeir, Bartosz Walter
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Code Smells in Machine Learning Systems [PDF]
arXiv.org, 2022 As Deep learning (DL) systems continuously evolve and grow, assuring their quality becomes an important yet challenging task. Compared to non-DL systems, DL systems have more complex team compositions and heavier data dependency.
Jiri Gesi +8 more
semanticscholar +1 more source
Code Smells in Elixir: Early Results from a Grey Literature Review [PDF]
IEEE International Conference on Program Comprehension, 2022 Elixir is a new functional programming language whose popularity is rising in the industry. However, there are few works in the literature focused on studying the internal quality of systems implemented in this language.
L. F. M. Vegi, M. T. Valente
semanticscholar +1 more source
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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Security Code Smells in Android ICC [PDF]
, 2018 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 +2 more sources