NPRG075

History and philosophy of programming

Tomáš Petříček, 309 (3rd floor)
petricek@d3s.mff.cuni.cz
https://tomasp.net | @tomaspetricek

Lectures: Monday 12:20, S7
https://d3s.mff.cuni.cz/teaching/nprg075

Philosophy of science

Why does it matter?

Philosophy of science

What can we learn about programming?

  • What designers assume and never question
  • How to understand odd designs of the past
  • What is the nature of programming concepts
  • What social forces shape programming

What do philosophers do?

Origins, languages, systems, correctness

How could it have
gone differently?

Reflections on ethics, politics, development

What if we took one aspect as primary?

Doing philosophy of programming

Methods

Try to explain
how scientists think and work

Entities

How concepts evolve & what
are they?

Social forces

How social aspects shape technology

Paradigm shifts

Classic philosophy of science

Scientific revolutions

Periods of normal science disrupted by revolutions

New era with new assumptions when the old ways stop working

New incommensurable with the old thinking

Philosophy of science

Research programmes (Lakatos)

  • Groups of scientists share assumptions
  • Explain failures by blaming
    secondary auxiliary assumptions

Against method (Feyerabend)

  • No single rule explains science
  • Hard to say what is reasonable!

Programming language revolution

(Gabriel, 2012)

From thinking about programming systems

Running, with evolving state, modified interactively

To thinking about programming languages

Relationships in static code

Smalltalk language

"Smalltalk is an object-oriented, dynamically typed reflective programming language"

What makes it interesting?

Smalltalk as a programming system

Think not about source code, but about evolving system state!

Demo

Smalltalk 72 and 78

Smalltalk

Programming system view

  • Image-based persistence rather than source
  • Application ships with developer tools
  • Class browser allows inspecting & editing
  • Reflection lets the system change itself

LISP language

Functional programming language
derived from the lambda calculus?

LISP environment

Time-sharing

  • Batch processing in the 1950s
  • TX-0 ('58) allowed interactive use
  • Multi-user machines via teletype

AI research requirements

  • Programming with symbolic data
  • Interactive experimentation
  • Programs that improve themselves

LISP editor

(Deutsch, 1967)

Interactive program editing on the terminal

Teletype, not a screen!

Print using: P
Delete child: (3)
Replace child: (2 ..)

Interlisp: Interactive Lisp

PILOT (1966)

  • Edit code via list transformations
  • Advising to enhance procedures
  • Modifying state of a running system

DWIM (1974)

  • Interactive program correction
  • Suggests automatic fixes when error occurs
  • Do What I Mean / Damn Warren's Infernal Machine

Symbolics Lips Machines (1980s)

Machines optimized for LISP with LISP-based environment

Persistent memory with just cons-cells

Response to new hardware architecture

Scientific revolutions

Paradigm shifts in programming

  • Understand what people really thought!
  • The invention of a programming language
  • The shift from systems to languages
  • Functional programming "research programme"

Entities

Evolution of programming concepts

How mathematical concepts evolve?

Polyhedra, space, graph, function, convergence, measurable set

How does the definition change and why?

Polyhedra

Euler's formula

\(V-E+F=2\)

A polyhedron is a solid whose surface consists of polygonal faces?

Counter example?

Convex polygons!

Through any point in space there will be at least one plane whose cross-section with the polyhedron will consist of one single polygon.

Monster-barring

I turn aside with a shudder of horror from this lamentable plague of functions which have no derivatives.
(Charles Hermite, 1893)

Concepts

Proofs and refutations

  • Concept definitions are not constant but change
  • Arising from proofs, counter-examples, lemmas
  • Monster-barring and exception-barring
  • Concept stretching when understanding evolves

Concepts in programming

Change over time!

  • Data types, logical types
  • Monads and "railway" metaphor
  • Processes become abstract

Multiple forces for change

  • New implementation of the concept
  • Different metaphor for thinking
  • New formalization in a proof

Evolution of types

Implementation & formal modality

Data types like records, modelled as sets

Implementation modality evolves

Abstract data types for modularity
Type checking ala lambda calculus

Intuitive modality evolves

Well-typed programs do not go wrong
New type systems based on this

Implementation modality evolves

Types for documentation and editor tooling

Understanding Monads

What are monads

  • Origins in category theory
  • Abstraction in functional programming
  • Used for stateful computations

Writing about monads

Evolution of monads

Formal and intuitive modality

Standard construction in algebraic topology Monad as a "box" intuition

Implementation modality appears

Used for sequencing effectful computations
Definition in terms of bind and return

Implementation & intuition evolves

Monads in Haskell and the do notation
Monad as a "sequencing" intuition

Concepts

Programming language design

  • There is more to concepts than just a name
  • Ideas come from logic, linguistics, biology!
  • Beware of concept stretching as with types?
  • Capture a new intuition in the design?

Social forces

What shapes programming?

Social history
of computing

How commercial
interests or gender bias shape computing

Redefinition of programming as more masculine software engineering in the 1960s

Structured programming

Goto considered harmful (1968)

The quality of programmers is a decreasing function of the density
of go to statements in the programs they produce.

Problems with goto

  • Hard to reason about informally
  • Hard to reason about formally
  • Code structure does not match runtime behaviour

Structured programming

Not obvious at the time!

  • Everyone used to assembly!
  • Can the compiler optimize code?
  • Is it possible to avoid gotos?

Structured Programming Theorem (1966)

Us converts waved this interesting bit of news under the noses of the unreconstructed assembly-language programmers who kept trotting forth twisty bits of logic and saying, 'I betcha can’t structure this.'

Datamation (1973)

What is structured programming and how to do it in practice

From engineering concept to managerial concept

Chief programmer teams

Top-down management technique

  • Structured programming for organizing people
  • Chief-programmer leading & dividing code
  • Supported by programmers, secretary, backup
  • Hostile exchanges between Dijkstra and Mills

Conway's law

Any organization that designs a system will produce a design whose structure is a copy of the organization's communication structure.

Social forces

Programming language design

  • Language features linked to social structures
  • Organizational structure and escape hatches
  • Structured, microservices, information hiding
  • Origins of languages - COBOL, Fortran, Algol

Conclusions

History and philosophy

History and philosophy

Learning from the past

Complex reasons why & how programming ideas work and do not work

Reading

10 PRINT CHR$(205.5+RND(1));
20 GOTO 10

Why should you read this?

  • Fun look at an unexpected bit of programming history
  • What can we learn from the past?

Conclusions

History and philosophy of programming

  • Scientific paradigms and paradigm shifts
  • The history of programming concepts
  • How social forces shape programming

Tomáš Petříček, 309 (3rd floor)
petricek@d3s.mff.cuni.cz
https://tomasp.net | @tomaspetricek
https://d3s.mff.cuni.cz/teaching/nprg075

References (1/2)

Philosophy of science

History & reflections

References (2/2)

Historical materials