Comparative analysis of impact of classification algorithms on security and performance bug reports by Said Maryyam, Bin Faiz Rizwan, Aljaidi Mohammad, Alshammari Muteb

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SynergyBug: A deep learning approach to autonomous debugging and code remediation by Hong Chen

“…Abstract Bug detection and resolution are pivotal to maintaining the quality, reliability, and performance of software systems. …”
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Cross-Platform Bug Localization Strategies: Utilizing Machine Learning for Diverse Software Environment Adaptability by Waqas Ali, Mariam Sabir

“…The LSTM model is trained and evaluated on a dataset of simulated bug reports, with the results interpreted using SHAP values to ensure clarity in decision-making. …”
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DeepBiteNet: A Lightweight Ensemble Framework for Multiclass Bug Bite Classification Using Image-Based Deep Learning by Doston Khasanov, Halimjon Khujamatov, Muksimova Shakhnoza, Mirjamol Abdullaev, Temur Toshtemirov, Shahzoda Anarova, Cheolwon Lee, Heung-Seok Jeon

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Uji Kualitas Website Admin Travel Booking Menggunakan Halstead’s Metric dan Equivalence Partitioning by Fauziah Nur Syifa, Trisana Nurul Anzali Nabil, Derrel Hendi Arifin, Rangga Sidik

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Automatic Thyroid Nodule Detection in Ultrasound Imaging With Improved YOLOv5 Neural Network by Daqing Yang, Jianfu Xia, Rizeng Li, Wencai Li, Jisheng Liu, Rongjian Wang, Dong Qu, Jie You

“…Afterward, 10 ultrasound images with wrong nodule types are added to the dataset for training, the result shows that the LSR module can significantly prevent the network from being misled by the bug data. …”
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In-depth exploration of software defects and self-admitted technical debt through cutting-edge deep learning techniques. by Sajid Ullah, M Irfan Uddin, Muhammad Adnan, Ala Abdulsalam Alarood, Abdulkream Alsulami, Safa Habibullah

“…The chosen data set comprises projects, designated SATD examples, and bug instances, facilitating thorough model training and evaluation. …”
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teaLeafBD: A comprehensive image dataset to classify the diseased tea leaf to automate the leaf selection process in BangladeshMendeley Data by B. M. Shahria Alam, Fahad Ahammed, Golam Kibria, Mohammad Tahmid Noor, Omar Faruq Shikdar, Kazi Isat Mahzabin, Nishat Tasnim Niloy, Md. Nawab Yousuf Ali

“…An automated disease classification system can be made utilizing deep learning techniques that will enable estate managers to take timely action to stop the spread of the disease, and this meticulously collected dataset will immensely help to train that model.…”
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Boost-Classifier-Driven Fault Prediction Across Heterogeneous Open-Source Repositories by Philip König, Sebastian Raubitzek, Alexander Schatten, Dennis Toth, Fabian Obermann, Caroline König, Kevin Mallinger

“…By examining each repository per file and per commit, we derive process metrics (e.g., churn, file age, revision frequency) alongside size metrics and entropy-based indicators of how scattered changes are over time. We train and tune a gradient boosting model to classify bug-prone commits under realistic class-imbalance conditions, achieving robust predictive performance across diverse repositories. …”
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Adapting the WHO ANC digital module for the NAMAI study: Formative research to inform implementation science interventions for enhanced quality service delivery following the WHO S... by Nachela Chelwa, Bernard R Ngabo, Muyereka Nyirenda, Musange F Sabine, María Barreix, Tigest Tamrat, Natasha Okpara, Chifundo Phiri, Nathalie K Murindahabi, David Nzeyimana, Tobias Makai, Gilbert Uwayezu, Gladys Yabalwazi, Mwamba Kangwa, Rosemary K Muliokela, Hedieh Mehrtash, Caren Chizuni, Vincent Mutabazi, Felix Sayinzoga, Michael T Mbizvo, Maurice Bucagu, Özge Tunçalp

“…Initial testing led to the identification and fixing of bugs in the system. The module was updated to include dashboards to support facility-based monitoring of ANC indicators. …”
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AVIATION ENGINES DIAGNOSTICS BY ESTIMATING THE METAL CONTAMINATION IN OILS by K. I. Gryadunov, A. N. Kozlov, M. L. Nemchikov, I. S. Mel’nikova

“…They show that with proper training of personnel the valuable information coming from the oil samples can be a source of important conclusions not only in aircraft engines accessories and assemblies state value, but also others systems, and also conclusions about the quality of fuel and lubricants used. …”
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Finding the balance between rigour and relevance: implementing adaptations to the implementation of a pragmatic randomised controlled trial of a two-way texting intervention for vo... by Caryl Feldacker, Geoffrey Setswe, Sarah Day, Felex Ndebele, Jacqueline Pienaar, Vuyolwethu Ncube

“…First, we categorised adaptations in a shared study-specific Google Docs that documented participant engagement with the 2wT system, tracked daily RCT implementation notes, reported software bugs and noted reminder emails about adaptations for the research team. …”
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Hybrid Quantum–Classical Deep Neural Networks Based Smart Contract Vulnerability Detection by Sinan Durgut, Ecir Uğur Küçüksille, Mahmut Tokmak

“…The SmartBugs Wild Dataset was used for training, with TF-IDF employed as a preprocessing technique optimized for hybrid architectures. …”
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Simulation of Two Stands Cold Rolling Mill Process Using Neural Networks and Genetic Algorithms in Combination to Avoid the Chatter Phenomenon by Behzad Bahraminejad, Mehrdad Dehghani, Sayed Ali Mousavi

“…To simulate the experiment, a neural network is trained and weights and bias values of the neural network with genetic optimization algorithm were used to get an optimal neural network which reduces bugs on the test data. …”
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