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🏛️ The Software Engineering Crypt
cs.SE: Where Software Engineering papers rest without their code.
16252
Total Papers
13410
No Code
294
Twilight
2548
Has Code
15.7%
Survival Rate
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The AutoProof Verifier: Usability by Non-Experts and on Standard Code
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TACTICS: TACTICal Service Oriented Architecture
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Advancing Software Security and Reliability in Cloud Platforms through AI-based Anomaly Detection
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Beyond Random Inputs: A Novel ML-Based Hardware Fuzzing
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Applications and Implications of Large Language Models in Qualitative Analysis: A New Frontier for Empirical Software Engineering
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When Fine-Tuning LLMs Meets Data Privacy: An Empirical Study of Federated Learning in LLM-Based Program Repair
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MR-Adopt: Automatic Deduction of Input Transformation Function for Metamorphic Testing
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DeepREST: Automated Test Case Generation for REST APIs Exploiting Deep Reinforcement Learning
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API-guided Dataset Synthesis to Finetune Large Code Models
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You Augment Me: Exploring ChatGPT-based Data Augmentation for Semantic Code Search
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What do we know about Hugging Face? A systematic literature review and quantitative validation of qualitative claims
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HumanEvo: An Evolution-aware Benchmark for More Realistic Evaluation of Repository-level Code Generation
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Calibration of Large Language Models on Code Summarization
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Lessons from the Use of Natural Language Inference (NLI) in Requirements Engineering Tasks
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An AI System Evaluation Framework for Advancing AI Safety: Terminology, Taxonomy, Lifecycle Mapping
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The Cartographer
A Survey of using Large Language Models for Generating Infrastructure as Code
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Leveraging Large Language Models for Preliminary Security Risk Analysis: A Mission-Critical Case Study
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On the effectiveness of Large Language Models for GitHub Workflows
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Analyzing and Mitigating (with LLMs) the Security Misconfigurations of Helm Charts from Artifact Hub
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Knowledge-aware Alert Aggregation in Large-scale Cloud Systems: a Hybrid Approach
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A compendium and evaluation of taxonomy quality attributes
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FuzzSlice: Pruning False Positives in Static Analysis Warnings Through Function-Level Fuzzing
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