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‎assignments.html‎

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<title>Assignments - Machine Programming - Fall 2025</title>
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<title>Assignments - Machine Programming | Johns Hopkins University</title>
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<meta name="description" content="Programming assignments for EN.601.727 Machine Programming course at Johns Hopkins University. Inductive synthesis, coding LLMs evaluation, and coding agents projects.">
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<meta name="author" content="Ziyang Li">
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<meta property="og:description" content="Programming assignments for EN.601.727 Machine Programming course covering inductive synthesis, coding LLMs evaluation, and coding agents.">
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‎index.html‎

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<title>Machine Programming - Fall 2025</title>
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<title>Machine Programming - Fall 2025 | Johns Hopkins University</title>
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<meta name="description" content="EN.601.727 Machine Programming course at Johns Hopkins University. Learn program synthesis, LLM-driven programming, and automated software development. Fall 2025 semester.">
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<meta name="author" content="Ziyang Li">
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<meta property="og:title" content="Machine Programming - Fall 2025 | Johns Hopkins University">
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<meta property="og:description" content="EN.601.727 Machine Programming course covering program synthesis, LLM-driven programming, and automated software development at Johns Hopkins University.">
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<meta name="twitter:image:alt" content="Machine Programming Course Logo">
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"name": "Machine Programming",
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"description": "This course explores both the foundations and frontiers of program synthesis, covering traditional symbolic techniques alongside LLM-driven approaches. Students will study a variety of synthesis paradigms, including example-based, type- and specification-guided, and interactive methods.",
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"name": "Johns Hopkins University",
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"teaches": ["Program synthesis", "Large language models", "Automated programming", "Code generation", "Software development", "Machine learning", "Programming languages"],
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‎presentation.html‎

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<title>Oral Presentations - Machine Programming - Fall 2025</title>
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<title>Oral Presentations - Machine Programming | Johns Hopkins University</title>
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<meta name="description" content="Oral presentation guidelines for EN.601.727 Machine Programming course at Johns Hopkins University. Student presentations on program synthesis and LLM research topics.">
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<meta name="keywords" content="machine programming presentations, program synthesis talks, LLM research presentations, Johns Hopkins University, computer science presentations">
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<meta name="author" content="Ziyang Li">
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<meta property="og:title" content="Oral Presentations - Machine Programming | Johns Hopkins University">
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<meta property="og:description" content="Oral presentation guidelines for EN.601.727 Machine Programming course covering student presentations on program synthesis and LLM research.">
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<meta property="og:url" content="https://machine-programming.github.io/presentation.html">
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‎project.html‎

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<title>Final Project - Machine Programming - Fall 2025</title>
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<title>Final Project - Machine Programming | Johns Hopkins University</title>
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<meta name="description" content="Final project guidelines for EN.601.727 Machine Programming course at Johns Hopkins University. Research-oriented project in program synthesis and LLM-driven programming.">
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<meta name="keywords" content="machine programming final project, program synthesis research, LLM programming project, Johns Hopkins University, computer science project">
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<meta name="author" content="Ziyang Li">
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<meta property="og:title" content="Final Project - Machine Programming | Johns Hopkins University">
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<meta property="og:description" content="Final project guidelines for EN.601.727 Machine Programming course covering research in program synthesis and LLM-driven programming.">
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<meta property="og:type" content="website">
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<meta property="og:url" content="https://machine-programming.github.io/project.html">
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<meta property="og:site_name" content="Machine Programming Course">
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‎readings.html‎

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<title>Readings - Machine Programming | Johns Hopkins University</title>
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<meta name="description" content="Required and recommended readings for EN.601.727 Machine Programming course at Johns Hopkins University. Research papers on program synthesis, LLMs, and automated programming.">
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<meta name="keywords" content="machine programming readings, program synthesis papers, LLM research papers, automated programming literature, Johns Hopkins University, computer science readings">
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<meta name="author" content="Ziyang Li">
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<meta property="og:title" content="Readings - Machine Programming | Johns Hopkins University">
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<meta property="og:description" content="Required and recommended readings for EN.601.727 Machine Programming course covering research papers on program synthesis, LLMs, and automated programming.">
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<meta property="og:type" content="website">
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<meta property="og:url" content="https://machine-programming.github.io/readings.html">
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<h2>Course Readings</h2>
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<p>This page contains relevant papers, courses, and webpages organized by topic.</p>
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<h3>Topic: Code Large Language Models</h3>
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<li><a href="https://arxiv.org/pdf/2402.01935" target="_blank">CodeSage</a> - [2024]</li>
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<li><a href="https://arxiv.org/abs/2310.06266" target="_blank">CodeFuse</a> - [2023]</li>
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<li><a href="https://arxiv.org/abs/2201.07520" target="_blank">Casual Masking</a> - [2022]</li>
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<li><a href="https://arxiv.org/pdf/1911.02150" target="_blank">Multi-Query-Attention</a> - [2019]</li>
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<li><a href="https://arxiv.org/abs/1810.04805" target="_blank">BERT</a> - [2018]</li>
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<!-- <h5>Supplemental for Paper 3 (DeepSeek Coder)</h5> -->
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<li><a href="https://arxiv.org/abs/1508.07909" target="_blank">BPE</a> - [2015]</li>
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<li><a href="https://arxiv.org/abs/2104.09864" target="_blank">RoPE</a> - [2021]</li>
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<li><a href="https://aclanthology.org/2021.emnlp-main.552/" target="_blank">SimCSE</a> - [2021]</li>
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<li><a href="https://aclanthology.org/2022.acl-long.499/" target="_blank">UniXCoder</a> - [2022]</li>
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<li><a href="https://openreview.net/forum?id=3ez9BSHTNT" target="_blank">DOBF</a> - [2022]</li>
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<li><a href="https://arxiv.org/abs/2403.07974" target="_blank">LiveCodeBench</a> - [2024]</li>
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<li><a href="https://arxiv.org/abs/2310.06770" target="_blank">SWE-bench: Can Language Models Resolve Real-World GitHub Issues?</a> - [2023]</li>
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<li><a href="https://arxiv.org/abs/2212.10264" target="_blank">ReCode: Robustness Evaluation of Code Generation Models (Trustworthiness)</a> - [2022]</li>
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<li><a href="https://arxiv.org/abs/2108.07732" target="_blank">MBPP</a> - [2021]</li>
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<li><a href="https://arxiv.org/abs/2403.08604" target="_blank">DevBench: A Comprehensive Benchmark for Software Development</a> - [2024]</li>
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<li><a href="https://arxiv.org/abs/2401.06401" target="_blank">DevEval: Evaluating Code Generation in Practical Software Projects</a> - [2024]</li>
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<li><a href="https://arxiv.org/abs/2310.11248" target="_blank">CrossCodeEval: A Diverse and Multilingual Benchmark for Cross-File Code Completion</a> - [2023]</li>
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<li><a href="https://arxiv.org/abs/2304.10778" target="_blank">Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPT</a> - [2023]</li>
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‎robots.txt‎

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Sitemap: https://machine-programming.github.io/sitemap.xml
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