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arXiv:2610.36341 (cs)
[Submitted on 26 Oct 2026]

Title:Executable Archaeology of Programs That Model Programming:
Reanimating the Heuristic Compiler (1961) and KBEmacs (1984)

Authors:Jeff Shrager, Kent M. Pitman, Mia Golec
View a PDF of the paper titled Executable Archaeology of Programs
That Model Programming: Reanimating the Heuristic Compiler (1961) and
KBEmacs (1984), by Jeff Shrager and 2 other authors
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    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
          Focus to learn more
          arXiv-issued DOI via DataCite

Submission history

From: Jeff Shrager [view email]
[v1] Mon, 26 Oct 2026 22:09:13 UTC (20 KB)
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