Use of deep learning in early software bug detection by Syed Mibran Hassan Zaidi, Maria Khan, Mustafa Latif, Ali Akhtar, Sallar Khan

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A hot-repair method for the running software with zero suspends by Guoyuan Lin, Jiazhen Cai, Yonggang Li, Haonan Li, Jiahui Zhou, Wei Chen, Zhong Chen, Shanqing Guo

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Leveraging Cross-Project Similarity for Data Augmentation and Security Bug Report Prediction by Jinfeng Ji, Geunseok Yang

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Software Defect Prediction Based On Deep Learning Algorithms : A Systematic Literature Review by Akhlas Hasan, Shayma Mohi-Aldeen

“…Software bug prediction (SDP) techniques identify bugs in the early stages of the software development life cycle through a series of steps to produce reliable and high-quality software. …”
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Refactoring Alma: Simplifying Circulation Settings in the Alma Integrated Library System (ILS) by Wilhelmina Randtke

“…This resulted in frequent frustration with how circulation worked, difficulty knowing what was or wasn’t a software bug, and inability to quickly fix problems once problems were identified or to make requested changes. …”
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Optimal frequency bands for pupillography for maximal correlation with HRV by Júlio Medeiros, André Bernardes, Ricardo Couceiro, Paulo Oliveira, Henrique Madeira, César Teixeira, Paulo Carvalho

“…From a controlled experiment involving 21 programmers performing software bug inspection, our study pinpoints the optimal low-frequency (0.06-0.29 Hz) and high-frequency (0.29-0.49 Hz) bands. …”
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Naive Bayes Classification for Software Defect Prediction by Edwin Hari Agus Prastyo, Muhammad Ainul Yaqin, Suhartono, M. Faisal, Reza Augusta Jannatul Firdaus

“…The outcomes of this research bear significant implications for the implementation of the Naive Bayes method in software bug prediction analysis, particularly in the utilization of the Python programming language with the assistance of Google Colab. …”
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Detecting Phantom Data Usage on Smartphones with Analysis of Contextual Information by Shiqi Jiang, Pengfei Zhou, Mo Li

“…We investigate about 400 real PDU issues and find the causes of PDU are not only the exceptions of applications, for example, software bugs or malware, but also the user's personalized misuse. …”
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An approach of method‐level bug localization by Zhen Ni, Lili Bo, Bin Li, Tianhao Chen, Xiaobing Sun, Xiaoxue Wu

“…Finally, the scores are sorted to determine the list of methods that may need to be modified when fixing the software bugs. We built a method‐granular bug localization dataset, which contains five open‐source projects. …”
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SynergyBug: A deep learning approach to autonomous debugging and code remediation by Hong Chen

“…It resolves essential requirements by implementing an automated system that diagnoses and resolves software bugs automatically, thus minimising human involvement. …”
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Predicting Object Communication Errors in Constructor Development by Abdul Majid Soomro, Awad Bin Naeem, Susama Bagchi, Babul Salam KSM Kader Ibrahim, Sanjoy Kumar Debnath

“…The technique is intended to stop or fix software bugs, particularly in situations where it is believed that object communications would persist across different settings. …”
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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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