Saifullah Mahbub

ORCID: 0000-0003-2423-9991
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About
Contact & Profiles
Research Areas
  • Software Engineering Research
  • Irrigation Practices and Water Management
  • Software Testing and Debugging Techniques
  • Software Reliability and Analysis Research
  • Soil and Unsaturated Flow
  • Water-Energy-Food Nexus Studies
  • Software System Performance and Reliability
  • Rice Cultivation and Yield Improvement
  • Water resources management and optimization
  • Plant Water Relations and Carbon Dynamics
  • Climate change impacts on agriculture

United International University
2024

Bangladesh Agricultural University
2023

The plant–water relationship of maize under conservation practices needs to be assessed quantify the effectiveness in conserving soil water for crop production. This study evaluated three trials how straw and plastic film mulching organic manure application could potentially change fluxes root zone increase yield. A mathematical model HYDRUS-1D was calibrated against observed content drainage data predict soil. simulated dynamics with satisfactory performance (RMSE 0.6–2.3%, CD 0.37–1.41,...

10.1016/j.agwat.2023.108394 article EN cc-by-nc-nd Agricultural Water Management 2023-05-31

Inspection of code review process effectiveness and continuous improvement can boost development productivity. Such inspection is a time-consuming human-bias-prone task. We propose semi-supervised learning based system ReviewRanker which aimed at assigning each confidence score expected to resonate with the quality review. Our proposed method trained on simple well defined labels provided by developers. The labeling task requires little no effort from has potential minimizing back-and-forth...

10.1145/3639478.3643111 article EN 2024-04-14

Code review is considered a key process in the software industry for minimizing bugs and improving code quality. Inspection of effectiveness continuous improvement can boost development productivity. Such inspection time-consuming human-bias-prone task. We propose semi-supervised learning based system ReviewRanker which aimed at assigning each confidence score expected to resonate with quality review. Our proposed method trained on simple well defined labels provided by developers. The...

10.48550/arxiv.2307.03996 preprint EN cc-by arXiv (Cornell University) 2023-01-01
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