Zobrazeno 1 - 10
of 29
pro vyhledávání: '"Sushant Kumar Pandey"'
Publikováno v:
2022 International Conference on Knowledge Engineering and Communication Systems (ICKES).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ffa7042470eb68607f86d6bc3e00d22d
https://doi.org/10.1109/ickecs56523.2022.10059946
https://doi.org/10.1109/ickecs56523.2022.10059946
Publikováno v:
Soft Computing. 25:13465-13492
The quality of the defect datasets is a critical issue in the domain of software defect prediction (SDP). These datasets are obtained through the mining of software repositories. Resent studies claims over the quality of the defect dataset. It is bec
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3b7156c2cfd35f530717c2321f2b9ade
https://doi.org/10.1007/s00500-021-06096-3
https://doi.org/10.1007/s00500-021-06096-3
Autor:
Vasilii Mosin, Miroslaw Staron, Darko Durisic, Francisco Gomes de Oliveira Neto, Sushant Kumar Pandey, Ashok Chaitanya Koppisetty
Publikováno v:
2022 48th Euromicro Conference on Software Engineering and Advanced Applications (SEAA).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::68c176a649523e86b18bd85188155470
https://doi.org/10.1109/seaa56994.2022.00020
https://doi.org/10.1109/seaa56994.2022.00020
Publikováno v:
IET Software. 14:768-782
Predicting defects during software testing reduces an enormous amount of testing effort and help to deliver a high-quality software system. Owing to the skewed distribution of public datasets, software defect prediction (SDP) suffers from the class i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5a08b3bd70667c7bffd0fa23c8349fcd
https://doi.org/10.1049/iet-sen.2020.0119
https://doi.org/10.1049/iet-sen.2020.0119
Publikováno v:
SSRN Electronic Journal.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::deec750774b1dc3c871ee2760d19a95e
https://doi.org/10.2139/ssrn.4089137
https://doi.org/10.2139/ssrn.4089137
Publikováno v:
2021 8th International Conference on Smart Computing and Communications (ICSCC).
Software practitioners are continuing to build advanced software defect prediction (SDP) models to help the tester find fault-prone modules. However, the Class Imbalance (CI) problem consists of uncommonly few defective instances, and more non-defect
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::211768c9fa3e3c0b3d6085b3133d6e83
https://doi.org/10.1109/icscc51209.2021.9528170
https://doi.org/10.1109/icscc51209.2021.9528170
Publikováno v:
Procedia Computer Science. 132:1412-1421
Software bug prediction becomes the vital activity during software development and maintenance. Fault prediction model able to engaged to identify flawed software code by utilizing machine learning techniques. Naive Bayes classifier has often used ti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::800d0201570d1a372d279b276cd67992
https://doi.org/10.1016/j.procs.2018.05.071
https://doi.org/10.1016/j.procs.2018.05.071
Publikováno v:
Knowledge-Based Systems. 233:107541
Software defect prediction (SDP) is the process of detecting fault-prone classes or modules in a software system. It helps in allocating resources before the testing phase more optimally. Due to a lack of an adequate dataset, defects can be predicted
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::81d59427eb989d9049b1edbbe215aadf
https://doi.org/10.1016/j.knosys.2021.107541
https://doi.org/10.1016/j.knosys.2021.107541
Publikováno v:
Expert Systems with Applications. 172:114595
Several prediction approaches are contained in the arena of software engineering such as prediction of effort, security, quality, fault, cost, and re-usability. All these prediction approaches are still in the rudimentary phase. Experiments and resea
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::de4df8dd407d0a784f2e2664e414d022
https://doi.org/10.1016/j.eswa.2021.114595
https://doi.org/10.1016/j.eswa.2021.114595
Publikováno v:
Expert Systems with Applications. 144:113085
In software fault prediction systems, there are many hindrances for detecting faulty modules, such as missing values or samples, data redundancy, irrelevance features, and correlation. Many researchers have built a software bug prediction (SBP) model
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1c30113452295ede6c2570fc06e75542
https://doi.org/10.1016/j.eswa.2019.113085
https://doi.org/10.1016/j.eswa.2019.113085