Research

Research projects, ongoing and completed.

Input/test case generation for System Level Concurrency bugs
Ongoing
Prof. Dr. Tarannum Shaila Zaman, IS, UMBC
Jan 2026 – Present
System Level Concurrency BugsTest Case GenerationConcurrency TestingSoftware TestingBug Reproduction
Developer study on LLM-based commit message generation
Ongoing
Prof. Dr. Tarannum Shaila Zaman, IS, UMBC
Aug 2025 – Present
LLMCommit Message GenerationDeveloper StudySoftware DevelopmentNatural Language Processing
Developer study on Software Debugging
Ongoing
Prof. Dr. Tarannum Shaila Zaman, IS, UMBC
Aug 2025 – Present
Software DebuggingDeveloper StudySoftware DevelopmentSoftware Maintenance
Details
  • Conducting a developer study to understand the current practices of software debugging in the industry
Analyzing and Summarizing Citations in Software Engineering Literature
Published
Prof. Dr. Tarannum Shaila Zaman, IS, UMBC
Aug 2025 – Dec 2025
Citation AnalysisSoftware Engineering LiteratureCitation SummarizationNatural Language ProcessingText Summarization
Reproducing System Level Concurrency Bugs
Prof. Dr. Tarannum Shaila Zaman, IS, UMBC
Aug 2025 – Dec 2025
Concurrency BugsSystem Level BugsReproducibilityBug ReproductionSoftware Testing
Details
  • Reproduced & Analyzed 70+ real-world concurrency bugs from the Redhat Bugzilla, Debian Debbugs, and GNU Bug Tracker.
Investigating Developer Awareness of VS Code Extension Security.
Dr. A. B. M. Alim Al Islam, CSE, BUET
Nov 2024 – Jan 2025
VS Code ExtensionSecurityDeveloper AwarenessSurveyStatic Analysis
Details
  • Conducted an online survey to investigate developers’ awareness of security risks in VS Code extensions.
  • Analyzed the survey results to identify common security vulnerabilities and developer practices.
  • Developed an extension to analyze extensions for security vulnerabilities.
[Undergrad Thesis] Towards Intelligent Traffic Signaling in Dhaka City Based on Vehicle Detection and Congestion Optimization.
Archived
Dr. A. B. M. Alim Al Islam, CSE, BUET
Aug 2023 – Jun 2024
Computer VisionObject DetectionRTSP Video Stream ProcessingTraffic Signal OptimizationNSGA-IIRaspberry Pi 4B
Details
  • Developed an intelligent traffic system tailored for Dhaka’s non-lane-based and heterogeneous traffic, utilizing real-time video analysis with Raspberry Pi for vehicle detection and optimizing signal timings through the multi-objective optimization algorithm NSGA-II.
  • Developed a Novel Traffic Image Dataset for Non lane-based and Heterogeneous Traffic in YOLO format and established a benchmark for Raspberry PI.