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<!DOCTYPE html>
<html lang="en">
<head>
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<title>Machine Programming - Fall 2026 | 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 2026 semester.">
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<meta name="author" content="Ziyang Li">
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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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"keywords": ["machine programming", "program synthesis", "LLM", "large language models", "automated programming", "computer science", "programming languages", "code generation"],
"teaches": ["Program synthesis", "Large language models", "Automated programming", "Code generation", "Software development", "Machine learning", "Programming languages"],
"about": ["Computer Science", "Programming Languages", "Machine Learning", "Software Engineering"]
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<body>
<header>
<img src="img/machine-programming-white.png" alt="Machine Programming" class="logo" width="400">
<!-- <h1>EN.601.727 Machine Programming</h1> -->
<p style="line-height: 20px;">
<img src="img/jhu-white.png" alt="Johns Hopkins University" class="logo" width="15" />
Johns Hopkins University — Fall 2026
</p>
</header>
<nav>
<a href="index.html" class="active">Home</a>
<a href="assignments.html">Assignments</a>
<a href="readings.html">Readings</a>
<a href="project.html">Final Project</a>
<a href="presentation.html">Presentations</a>
<a href="#calendar">Calendar</a>
</nav>
<main>
<section>
<h2>Course Information</h2>
<ul class="info-list">
<li><strong>Course Number:</strong> EN.601.727</li>
<li><strong>Credits:</strong> 3</li>
<li><strong>Instructor:</strong> <a href="https://liby99.github.io">Ziyang Li</a></li>
<li><strong>Email:</strong> <a href="mailto:ziyang@cs.jhu.edu">ziyang@cs.jhu.edu</a></li>
<li><strong>Time:</strong> Tuesday and Thursday 12:00pm - 1:15pm</li>
<li><strong>Location:</strong> Latrobe 107, Homewood Campus</li>
<li><strong>Office Hours:</strong> Friday 10:00am - 11:00am, held online over <a href="https://wse.zoom.us/my/ziyang">Zoom</a>; can also be arranged in person at Ziyang's office, Malone Hall 325, on request. Also available by appointment through email</li>
<li><strong> </strong></li>
<li><strong>TA:</strong> Qi Sun (Email: <a href="mailto:qsun28@jh.edu">qsun28@jh.edu</a>)</li>
<li><strong>TA Office Hours:</strong> Thursday 10:00am - 11:00am, <a href="https://JHUBlueJays.zoom.us/my/mikesun">Zoom</a></li>
<li><strong>CA:</strong> Yuming Feng (Email: <a href="mailto:yfeng97@jh.edu">yfeng97@jh.edu</a>)</li>
<li><strong>CA Office Hours:</strong> Wednesday 11:00am - 12:00pm, <a href="https://JHUBlueJays.zoom.us/my/yumingfeng">Zoom</a></li>
</ul>
</section>
<section>
<h2>Course Description</h2>
<p>
Programs are the fundamental medium through which humans interact with computers.
With the advent of large language models (LLMs), the automated synthesis of programs is rapidly transforming how we build software.
Instead of manual code writing, we specify intent through examples, specifications, and natural language.
</p>
<p>
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.
We will examine how LLMs are applied to general-purpose programming tasks as well as to specialized domains such as theorem proving, program repair, planning, and verification.
</p>
<p>
Throughout the course, students will gain exposure to a wide range of programming languages, from widely-used ones like Python and C, to emerging and domain-specific languages such as Rust, Lean, CodeQL, and PDDL.
The course offers a research-oriented perspective combined with hands-on assignments and projects, providing students with both conceptual understanding and practical experience at the intersection of programming languages and machine learning.
</p>
</section>
<section>
<h2>Course Logistics</h2>
<ul>
<li>We are going to use <a href="https://www.gradescope.com/courses/1377842" target="_blank">GradeScope</a> for grading your programming assignments and final projects.</li>
<li>Course discussion (questions, notes, announcements) are going to be made on <a href="https://courselore.org/courses/9704862006" target="_blank">Courselore</a>; you can <a href="https://courselore.org/courses/9704862006/invitations/91898841638832525272" target="_blank">enroll yourself</a>.</li>
</ul>
</section>
<section>
<h2>Grading Rubrics</h2>
<p>
Students will be evaluated based on participation, assignments, a presentation, and a final project.
Active engagement throughout the course is strongly encouraged, both in class discussions and in peer feedback.
Exceptional oral presentation or final project may be rewarded with extra credit.
</p>
<ol>
<li>(10%) Class participation and active discussion</li>
<li>(10%) <a href="presentation.html">Oral presentation</a></li>
<li>(15%) <a href="https://github.com/machine-programming/assignment-1" target="_blank">Assignment 1: Inductive Synthesis</a></li>
<li>(15%) Assignment 2: Evaluating Coding LLMs</li>
<li>(15%) Assignment 3: Coding Agents</li>
<li>(35%) <a href="project.html">Final Project</a></li>
</ol>
</section>
<section id="calendar">
<h2>Course Calendar</h2>
<table class="calendar">
<tr>
<th>Week</th>
<th>Date</th>
<th>Topic / Event</th>
</tr>
<tr><td colspan="3"><strong>Module 1: Programming Languages and Synthesis</strong></td></tr>
<tr><td rowspan="2">1</td>
<td>Sep 1 (Tue)</td><td><a target="_blank" href="lectures/lecture-1.pdf">Overview & Introduction to Machine Programming</a></td></tr>
<tr><td>Sep 3 (Thu)</td><td><a target="_blank" href="lectures/lecture-2.pdf">Syntax, Semantics, and Bottom-up Inductive Synthesis</a></td></tr>
<tr><td rowspan="2">2</td>
<td>Sep 8 (Tue)</td><td><a target="_blank" href="lectures/lecture-3.pdf">Type Systems and Top-down Enumerative Synthesis</a></td></tr>
<tr><td>Sep 10 (Thu)</td><td><a target="_blank" href="lectures/lecture-4.pdf">Functional Specifications and Synthesis</a></td></tr>
<tr><td colspan="3"><strong>Module 2: Coding Large Language Models</strong></td></tr>
<tr><td rowspan="2">3</td>
<td>Sep 15 (Tue)</td><td>Language Modeling for Synthesis</td></tr>
<tr><td>Sep 17 (Thu)</td><td>Decoding and Prompting for Synthesis</td></tr>
<tr><td rowspan="2">4</td>
<td>Sep 22 (Tue)</td><td>Iterative Refinement with Feedback | <a target="_blank" href="https://github.com/machine-programming/assignment-1">[Assignment 1 Due]</a></td></tr>
<tr><td>Sep 24 (Thu)</td><td>Controlled Decoding for Synthesis</td></tr>
<tr><td rowspan="2">5</td>
<td>Sep 29 (Tue)</td><td>Agentic Frameworks for Programming (1)</td></tr>
<tr><td>Oct 1 (Thu)</td><td>Agentic Frameworks for Programming (2)</td></tr>
<tr><td rowspan="2">6</td>
<td>Oct 6 (Tue)</td><td>Agentic Frameworks for Programming (3)</td></tr>
<tr><td>Oct 8 (Thu)</td><td>Pre-training of Coding LLMs (1): Architecture and Dataset</td></tr>
<tr><td rowspan="2">7</td>
<td>Oct 13 (Tue)</td><td>Pre-training of Coding LLMs (2): Learning and Evaluation</td></tr>
<tr><td>Oct 15 (Thu)</td><td>Post-training of Coding LLMs: Fine-tuning and Reinforcement Learning</td></tr>
<tr><td colspan="3"><strong>Module 3: Applications of Machine Programming</strong></td></tr>
<tr><td rowspan="2">8</td>
<td>Oct 20 (Tue)</td><td>LLM for Software Analysis: Dynamic Analysis</td></tr>
<tr><td>Oct 22 (Thu)</td><td>(Fall break, no class — date TBD)</td></tr>
<tr><td rowspan="2">9</td>
<td>Oct 27 (Tue)</td><td>LLM for Software Analysis: Static Analysis</td></tr>
<tr><td>Oct 29 (Thu)</td><td>LLM for Software Security</td></tr>
<tr><td rowspan="2">10</td>
<td>Nov 3 (Tue)</td><td>Programming Languages for Software Security</td></tr>
<tr><td>Nov 5 (Thu)</td><td>Oral Presentations (1)</td></tr>
<tr><td rowspan="2">11</td>
<td>Nov 10 (Tue)</td><td>Oral Presentations (2)</td></tr>
<tr><td>Nov 12 (Thu)</td><td>Oral Presentations (3)</td></tr>
<tr><td rowspan="2">12</td>
<td>Nov 17 (Tue)</td><td>Oral Presentations (4)</td></tr>
<tr><td>Nov 19 (Thu)</td><td>Oral Presentations (5)</td></tr>
<tr><td rowspan="2">13</td>
<td>Nov 24 (Tue)</td><td>Fall recess (no class)</td></tr>
<tr><td>Nov 26 (Thu)</td><td>Thanksgiving (no class)</td></tr>
<tr><td rowspan="2">14</td>
<td>Dec 1 (Tue)</td><td>Oral Presentations (6)</td></tr>
<tr><td>Dec 3 (Thu)</td><td>Special Topic: Neurosymbolic Programming</td></tr>
<tr><td rowspan="2">15</td>
<td>Dec 8 (Tue)</td><td>Special Topic: Synthesizing Diverse DSLs</td></tr>
<tr><td>Dec 10 (Thu)</td><td>TBD</td></tr>
<tr><td colspan="3"><strong>Final Presentation Session</strong></td></tr>
<tr><td></td><td>TBD</td><td>Final Presentation Session (during the final exam period, Dec 15–23)</td></tr>
</table>
<p class="mt-4">
<a href="past-versions.html" class="btn btn-outline-primary btn-sm">Past Versions</a>
</p>
</section>
<section>
<h2>Policy</h2>
<p>
<strong>Auditing:</strong>
Students are welcome to audit this course, whether formally (registered as an auditor) or informally (simply sitting in on lectures).
Auditing students are welcome to join the course on
<a href="https://courselore.org/courses/9704862006" target="_blank">Courselore</a> and
<a href="https://www.gradescope.com/courses/1377842" target="_blank">GradeScope</a>,
and to take part in discussions and the assignments.
If you would like to audit, please send the instructor an email at
<a href="mailto:ziyang@cs.jhu.edu">ziyang@cs.jhu.edu</a>.
</p>
</section>
</main>
</body>
</html>