Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Seema Dewangan"'
Publikováno v:
Scientific Reports, Vol 13, Iss 1, Pp 1-18 (2023)
Abstract Detecting code smells may be highly helpful for reducing maintenance costs and raising source code quality. Code smells facilitate developers or researchers to understand several types of design flaws. Code smells with high severity can caus
Externí odkaz:
https://doaj.org/article/390201780b7440ceaddb104fbf034404
Publikováno v:
IEEE Access, Vol 9, Pp 162869-162883 (2021)
Code smells detection helps in improving understandability and maintainability of software while reducing the chances of system failure. In this study, six machine learning algorithms have been applied to predict code smells. For this purpose, four c
Externí odkaz:
https://doaj.org/article/d6b0149679174292a03622a1620db9ec
Publikováno v:
Applied Sciences, Vol 12, Iss 20, p 10321 (2022)
Code smells are the result of not following software engineering principles during software development, especially in the design and coding phase. It leads to low maintainability. To evaluate the quality of software and its maintainability, code sme
Externí odkaz:
https://doaj.org/article/ceadbaab626148909d67c379681a3ee8
Publikováno v:
2022 International Conference on Intelligent Controller and Computing for Smart Power (ICICCSP).
Autor:
Seema Dewangan, Rajwant Singh Rao
Publikováno v:
2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT).
Autor:
Seema Dewangan, Rajwant Singh Rao
Publikováno v:
2021 IEEE 6th International Conference on Computing, Communication and Automation (ICCCA).
Publikováno v:
2021 10th International Conference on Internet of Everything, Microwave Engineering, Communication and Networks (IEMECON).
Publikováno v:
ANTS
Data Collection from the remote or very callous environments is very challenging issue in wireless sensor network. In a remote or very callous environment, when sensor nodes are randomly deployed, it is observed that all sensor nodes are not fully co