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🏛️ The Software Engineering Crypt
cs.SE: Where Software Engineering papers rest without their code.
16551
Total Papers
13410
No Code
294
Twilight
2847
Has Code
17.2%
Survival Rate
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Deep Learning-based Code Reviews: A Paradigm Shift or a Double-Edged Sword?
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REACCEPT: Automated Co-evolution of Production and Test Code Based on Dynamic Validation and Large Language Models
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Developer Challenges on Large Language Models: A Study of Stack Overflow and OpenAI Developer Forum Posts
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Exascale Workflow Applications and Middleware: An ExaWorks Retrospective
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Large Language Models as Robust Data Generators in Software Analytics: Are We There Yet?
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TimeLess: A Vision for the Next Generation of Software Development
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Impact of LLM-based Review Comment Generation in Practice: A Mixed Open-/Closed-source User Study
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Anchor Attention, Small Cache: Code Generation with Large Language Models
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Feature Importance in the Context of Traditional and Just-In-Time Software Defect Prediction Models
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Quantum Neural Network Classifier for Cancer Registry System Testing: A Feasibility Study
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How do practitioners gain confidence in assurance cases?
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Towards Interoperability Testing of Smart Energy Systems -- An Overview and Discussion of Possibilities
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Disrupting Test Development with AI Assistants
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Fast Fixes and Faulty Drivers: An Empirical Analysis of Regression Bug Fixing Times in the Linux Kernel
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Investigating the Impact of Interpersonal Challenges on Feeling Welcome in OSS
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Envisioning Responsible Quantum Software Engineering and Quantum Artificial Intelligence
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Secret Breach Prevention in Software Issue Reports
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VisualCoder: Guiding Large Language Models in Code Execution with Fine-grained Multimodal Chain-of-Thought Reasoning
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Automated Personnel Selection for Software Engineers Using LLM-Based Profile Evaluation
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LLMs Integration in Software Engineering Team Projects: Roles, Impact, and a Pedagogical Design Space for AI Tools in Computing Education
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From Cool Demos to Production-Ready FMware: Core Challenges and a Technology Roadmap
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Deep Learning and Data Augmentation for Detecting Self-Admitted Technical Debt
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