可执行考古学：复跑 1961 年 Heuristic Compiler 与 1984 年 KBEmacs
Executable Archaeology of Programs That Model Programming: Reanimating the Heuristic Compiler (1961) and KBEmacs (1984)
AI 导读
研究者以"可执行考古学"方法复跑了两个早期 AI 编程系统：Herbert Simon 的 Heuristic Compiler（1961）重现了其 1963 年论文中的编译代码，MIT Programmer's Apprentice 项目的 KBEmacs（1984）重现了其 1984 年 12 月自测的 SQRT 序列。
正文 · 原文
Abstract:Early AI programs were often also theories of how people think, and programs that wrote programs were, in part, theories of how people program. Here we report on the reanimation of two such programs that offer two seemingly different theories of programming and were developed for quite different purposes. The first, Herbert Simon's Heuristic Compiler (1961), was an experimental model of programming as problem-solving, applying the means-ends analysis methods of the General Problem Solver to investigate the nature of the programming task. The second, KBEmacs (1984), was a working prototype of an intelligent programming assistant developed by MIT's Programmer's Apprentice project, built on the view that expert programmers recognize and combine familiar patterns, or "cliches." It let a programmer build up programs by combining cliches through a stylized English command language. We approach both through the methodology of Executable Archaeology, the study of historical computational systems by running their original code, a process we call "reanimation." Our reanimation of the Heuristic Compiler reproduces the compiled code appearing in Simon's 1963 paper, and our reanimation of KBEmacs reproduces the SQRT sequence of its December 1984 self-test. Examined side by side, the two theories turn out to have much in common: the Heuristic Compiler also works by adapting existing routines, and Simon later argued that search alone requires a large body of programming knowledge. To highlight the reflexivity of this project, we deliberately used a modern AI-assisted programming tool, Anthropic's Claude Code (Opus 5.5), to carry out much of the detailed reanimation work, building on a significant base of existing software. The explicit, executable theories of programming that both systems embodied are largely absent from today's far more capable AI coding assistants.
| Subjects: | Artificial Intelligence (cs.AI); Human-Computer Interaction (cs.HC); Programming Languages (cs.PL) |
| Cite as: | arXiv:2610.36341 [cs.AI] |
| (or arXiv:2610.36341v1 [cs.AI] for this version) | |
| https://doi.org/10.48550/arXiv.2610.36341 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Jeff Shrager [view email]
[v1]
Mon, 26 Oct 2026 22:09:13 UTC (20 KB)
来源：arXiv cs.AI · arxiv.org