Results 1 to 10 of about 2,621 (70)

Python code smells detection using conventional machine learning models. [PDF]

PeerJ Comput Sci, 2023
Sandouka R, Aljamaan H.
europepmc   +1 more source

Empirical study of the relationship between design patterns and code smells. [PDF]

PLoS One, 2020
Alfadel M, Aljasser K, Alshayeb M.
europepmc   +1 more source

Code smells analysis for android applications and a solution for less battery consumption. [PDF]

Sci Rep
Gupta A, Suri B, Sharma D, Misra S, Fernandez-Sanz L.   +4 more
europepmc   +1 more source

Identifying co-occurrences of message chains and member ignoring method in android applications using static program analysis and dynamic stacking ensemble. [PDF]

Sci Rep
Ma Z, Bian Y, Chen W, Huang L.
europepmc   +1 more source

Cigarette packs as advertising channels to promote heated tobacco products in South Korea. [PDF]

Tob Control
Cheon E, Kim S, Park S, Xu SS, Quah ACK, Cho SI, Kang H.   +6 more
europepmc   +1 more source

SmellyCode++: Multi-Label Dataset for Code Smell Detection. [PDF]

Sci Data
Alomari N, Alazba A, Aljamaan H, Alshayeb M.   +3 more
europepmc   +1 more source

How students use generative AI for software testing: An observational study. [PDF]

Empir Softw Eng
Ardic B, Le Dilavrec Q, Zaidman A.
europepmc   +1 more source

Locating community smells in software development processes using higher-order network centralities. [PDF]

Soc Netw Anal Min, 2023
Gote C, Perri V, Zingg C, Casiraghi G, Arzig C, von Gernler A, Schweitzer F, Scholtes I.   +7 more
europepmc   +1 more source

An empirical comparison of AI assisted software refactoring tools. [PDF]

Sci Rep
Saba G, Ahmed S, Sania H, Khan TA, Mohamad Nasir HB.   +4 more
europepmc   +1 more source

A study of dealing class imbalance problem with machine learning methods for code smell severity detection using PCA-based feature selection technique. [PDF]

Sci Rep, 2023
Rao RS, Dewangan S, Mishra A, Gupta M.
europepmc   +1 more source