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Record W3035535885 · doi:10.1145/3386324

Evolution of Emacs Lisp

2020· article· en· W3035535885 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueProceedings of the ACM on Programming Languages · 2020
Typearticle
Languageen
FieldComputer Science
TopicLogic, programming, and type systems
Canadian institutionsUniversité de Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLispProgramming languageComputer scienceInterpreterException handlingSyntaxArtificial intelligence

Abstract

fetched live from OpenAlex

While Emacs proponents largely agree that it is the world’s greatest text editor, it is almost as much a Lisp machine disguised as an editor. Indeed, one of its chief appeals is that it is programmable via its own programming language. Emacs Lisp is a Lisp in the classic tradition. In this article, we present the history of this language over its more than 30 years of evolution. Its core has remained remarkably stable since its inception in 1985, in large part to preserve compatibility with the many third-party packages providing a multitude of extensions. Still, Emacs Lisp has evolved and continues to do so. Important aspects of Emacs Lisp have been shaped by concrete requirements of the editor it supports as well as implementation constraints. These requirements led to the choice of a Lisp dialect as Emacs’s language in the first place, specifically its simplicity and dynamic nature: Loading additional Emacs packages or changing the ones in place occurs frequently, and having to restart the editor in order to re-compile or re-link the code would be unacceptable. Fulfilling this requirement in a more static language would have been difficult at best. One of Lisp’s chief characteristics is its malleability through its uniform syntax and the use of macros. This has allowed the language to evolve much more rapidly and substantively than the evolution of its core would suggest, by letting Emacs packages provide new surface syntax alongside new functions. In particular, Emacs Lisp can be customized to look much like Common Lisp, and additional packages provide multiple-dispatch object systems, legible regular expressions, programmable pattern-matching constructs, generalized variables, and more. Still, the core has also evolved, albeit slowly. Most notably, it acquired support for lexical scoping. The timeline of Emacs Lisp development is closely tied to the projects and people who have shaped it over the years: We document Emacs Lisp history through its predecessors, Mocklisp and MacLisp, its early development up to the “Emacs schism” and the fork of Lucid Emacs, the development of XEmacs, and the subsequent rennaissance of Emacs development.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.738
Threshold uncertainty score0.545

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0030.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.021
GPT teacher head0.254
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it