Search Results for author: Nibir Chandra Mandal

Found 4 papers, 0 papers with code

Can Transformer Models Effectively Detect Software Aspects in StackOverflow Discussion?

no code implementations24 Sep 2022 Nibir Chandra Mandal, Tashreef Muhammad, G. M. Shahariar

Through extensive experimentation, we have found that transformer models improve the performance of baseline SVM for most of the aspects, i. e., `Performance', `Security', `Usability', `Documentation', `Bug', `Legal', `OnlySentiment', and `Others'.

Effectiveness of Transformer Models on IoT Security Detection in StackOverflow Discussions

no code implementations29 Jul 2022 Nibir Chandra Mandal, G. M. Shahariar, Md. Tanvir Rouf Shawon

However, finding discussions that are relevant to IoT issues is challenging since they are frequently not categorized with IoT-related terms.

An Empirical Study of IoT Security Aspects at Sentence-Level in Developer Textual Discussions

no code implementations7 Jun 2022 Nibir Chandra Mandal, Gias Uddin

We have two goals: (1) Develop a model that can automatically find security-related IoT discussions in SO, and (2) Study the model output to learn about IoT developer security-related challenges.

Sentence

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