Lecture 3: A Brief History of
Programming Languages
Available within the network will be functions and services to which you
subscribe on a regular basis and others that you call for when you need them.
In the former group will be investment guidance, tax counseling, selective
dissemination of information in your field of specialization, announcement of
cultural, sport, and entertainment events that fit your interests, etc. In the latter
group will be dictionaries, encyclopedias, indexes, catalogues, editing
programs, teaching programs, testing programs, programming systems, data
bases, and – most important – communication, display, and modeling
programs. All these will be – at some late date in the history of networking systematized and coherent; you will be able to get along in one basic language
up to the point at which you choose a specialized language for its power or
terseness.
J. C. R. Licklider and Robert W. Taylor,
The Computer as a Communication Device, April
1968
CS655: Programming Languages
David Evans
University of Virginia
http://www.cs.virginia.edu/~evans
Computer Science
Menu
• Brief History of Programming
Languages
• Projects Kick-off
• Wenger Discussion
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Really Brief History
• 50s, 60s: Exciting Time
– Invention of: assemblers, compilers, interpreters,
first high-level languages, structured
programming, abstraction, formal syntax, objectoriented programming, LISP, program verification
• 70s, 80s, 90s: Boring Time
– Refinement of earlier ideas, better
implementations, making theory more practical
– A few new/refined ideas: functional languages,
data abstraction, concurrent languages, data flow,
type theory, etc.
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00s and beyond?
• Pessimist’s View:
– Like the 70s-90s: the most important concepts
have been discovered, and nothing has really
changed; slow incremental progress will continue.
• Optimist’s View:
– New environments (large scale networks, dynamic
collections of unpredictable devices) provide new
programming challenges (scalability, security,
reliability), and new exciting developments will
result. First time since 60s that PLs are behind
the curve!
• Alan Kay: “The best way to predict the future
is to invent it.”
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UVA’s Info Systems
Language
COBOL
Mantis
Clipper 5
PDL (DBS 4GL)
Assembler
SAS
C
Lines of Code
3,630,650
505,016
224,420
196,697
53,387
52,609
5,000
Source: http://www.virginia.edu/year2000/att7-3.htm
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What drives programming language design?
• Advances in Theory
– BNF Grammars  Algol60
– Lambda Calculus  LISP
– Type theory  CLU, ML
• Changes in computing environment
–
–
–
–
Analytical engine  first programming system
von Neumann Machines  Procedural Languages
Parallel Machines  Functional Languages
Large scale networks  ???
• Changes in desired programs
–
–
–
–
Calculating missile trajectories  Assembly
Scientific computations  FORTRAN
Business computations  COBOL, PL/I
Larger programs  Data languages, Components
– Even larger programs  ???
– Security requirements  ???
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Less Brief History of PLs
• Language Design Really Big Ideas
–
–
–
–
–
B0: The First Programs (1830s)
B1: High-level Languages (1950s-)
B2: Structured Languages (1960s-)
B3: Functional Languages (1960s-)
B4: Data Languages (1970s-)
• Language Theory Really Big Ideas
–
–
–
–
–
L0: Chomsky’s Hierarchy
L1: Formal Syntax (BNF1960)
L2: Formal Semantics (Floyd 67, Scott 71)
L3: Program Verification (Hoare 69, etc.)
L4: Type Theory (60s-2000s)
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B0: Ada Byron, Lady Lovelace
The First Programmer
• Described program to solve Bernoulli
equations using Babagge’s Analytical Engine
• Store data and program (Jacquard punch
cards)
• Concepts of:
– operator
– numerical and symbolic computation (types)!
– object-oriented programming!
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“It may be desirable to explain, that by the word operation,
we mean any process which alters the mutual relation of
two or more things, be this relation of what kind it may.
This is the most general definition, and would include all
subjects in the universe . . . Again, it [the Analytical Engine]
might act upon other things besides number, were objects
found whose mutual fundamental relations could be
expressed by those of the abstract science of operations,
and which should be also susceptible of adaptations to the
action of the operating notation and mechanism of the
engine . . . Supposing, for instance, that the fundamental
relations of pitched sounds in the science of harmony and
of musical composition were susceptible of such
expression and adaptations, the engine might compose
elaborate and scientific pieces of music of any degree of
complexity or extent.”
Ada Lovelace, around 1830
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P1: High-Level Languages
• Assemblers, Macro Processors
• Pseudo-Code Interpreters
– Wilkes, Wheeler & Gill, 1951 (Appendix D)
• First Compiler: Grace Murray Hopper, 1950s
• Automatic Programming [A-2 compiler, 1953]
– Symbolic addresses, decimal numbers
• Laning and Zierler’s algebraic system
– First algebraic compiler
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FORTRAN (Backus, 1954)
• Radical idea: computers were more expensive than
programmers – if performance suffered, would be
failure
– Experience with machine code hacking and automatic
programming systems convinced programmers efficient code
could not be generated automatically
•
“As far as we were aware, we simply made up the language as we went
along. We did not regard language design as a difficult problem, merely
a simple prelude to the real problem: designing a compiler which could
produce efficient programs.” [Backus, HOPL-I 1978]
• Used familiar mathematical notations
• Project to design an automatic programming system
for the IBM 704, not design a general language
“We certainly has no idea that languages almost identical to the one
we were working on would be used for more than one IBM
computer, not to mention those of other manufacturers. (After all,
there were very few computers around then.) [Backus, 1978]
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Hopelessly Naïve
“In our naïve unawareness of language design problems
- of course we knew nothing of many issues which were
later thought to be important, e.g., block structure,
conditional expressions, type declarations - it seemed to
use that once one had the notions of the assignment
statement, the subscripted variable, and the DO
statement in hand, then the remaining problems of
language design were trivial: either their solution was
thrust upon one by the need to provide some machine
facility such as reading input, or by some programming
task which could not be done with existing structures.”
[Backus 1978]
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Hopelessly Optimistic
“Unfortunately we were hopelessly
optimistic in 1954 about the problems of
debugging FORTRAN programs (thust
we find on page 2 of the Report: “Since
FORTRAN should virtually eliminates
coding and debugging…[!]”) and hence
syntactic error checking facilities …
were weak.”
[Backus 1978]
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P2: Structured Languages: Algol
(also called: Procedural, Imperative, etc.)
• Algol58: captured ideas of FORTRAN in an elegant
way – types, conditionals, loops; still limited
abstraction from machine
• Algol60:
– First language designed with principles in mind
• Explicit goal: language for publishing algorithms
– Introduced:
• Formal language syntax (BNF)
• Block structure, compound statements, type declarations,
variable scopes
• Dynamic lifetimes, arrays with dynamic bounds
• Notion of actual and formal parameters, call-byvalue/call-by-name
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Algol’s Successors
FORTRAN
1954
1960
Algol60
Classes
CPL
BCPL
C
Simula67
PL/I
Algol-W
Algol68
Pascal CLU Smalltalk
1970
Modula-2
C++
Oberon
Modula-3
Java
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1980
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P3: Functional Languages
•
•
•
•
Imperative languages: assign
Functional languages: compose
No state (pure functional languages)
First class functions, closures
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Functional Languages
FORTRAN
1960
LISP
Algol60
ISWIM
ML
Mac Lisp
FP
1970
Scheme
1980
Miranda
Common Lisp
SML
Haskell
1990
ML2000
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FL: Example
def f    intsto
f:5
(  intsto):5
*:(intsto:5)
*:<1, 2, 3, 4, 5>
120
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(f  g):x  f:(g:x)
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Functional Languages
• Claimed Advantages:
– Easier to write interpreter for
– Easier to learn to program
– Easier to reason about programs
• Reality:
– Hard to get decent performance
– Useful for PL research
• Especially ML, type systems
– Useful for teaching
• especially Scheme
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P4: Data Abstraction
• FORTRAN: No declarations, types – integer, float, ?; identifier name
determined type
• Algol60: declarations, types:
• Pascal, Algol68: User-defined types, confused about type
equivalence
• Simula67: added classes to Algol60
– Inheritance
• CLU: data abstraction
– Methodology for building programs by defining data types
– Support for encapsulation (data hiding), iterators
– Others: Ada (83), Oberon, Alphard
• Smalltalk: object-orientation
– Inheritance, subtyping (?), method dispatch
• Other O-O languages: C++, Java, Eiffel, Sather, Ada (95), etc.
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Data Abstraction Ideas
• Type-checking to reduce errors
– Early languages: just manipulating bits
– Lose expressiveness (especially if statically
checked)
• Encapsulation to reduce errors, improve
maintainability
– Specified type used as abstract entity
• Subtyping to provide extensibility
– Define new properties for a type
• Inheritance to reuse code
– Use a different types implementation to implement
new type
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What’s missing?
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John’s Talk
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The Evolution of the C
Programming Language
The Making of a CS655 Semester Project
John Haskins, Jr.
University of Virginia Department of Computer Science
predator@cs.virginia.edu
The Setup (1/2)
The arrogant, irreverent assertion...
“I don’t know what the language of the future will look like, but
I know that its name will be FORTRAN.”
- Peter Naur, Alan Batson, C.A.R. Hoare, Niklaus Wirth, etc.
“I do know what the language of the future will look like and I
know that its name will be C.”
- John Haskins, Jr.
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The Setup (2/2)
Initial justification of tough claim…
• C has permeated virtually every field of computer
programming endeavor and--love it or hate it--simply will
not go away and therefore deserves to be periodically
revisited and refurbished to make it into a more mature and
“appropriate” tool.
• C’s appropriate use is as a language for developing low-level
systems and embedded applications.
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Details and Specific Proposals
The new and improved C should have…
• Rigorously defined built-in data types: int is too ambiguous,
varying from compiler to compiler, sometimes as a function
of machine word size
• Improved variadic function mechanisms: current solution is
clumsy and detached from the language itself
• Built-in I/O mechanisms: I/O should be integrated into the
language instead of being relegated to libraries separate from
the language
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The Follow-through (1/2)
• Alter the C lexer to recognize and return tokens for new
keywords:
– [s|u][8|16|32|64] and f[32|64|128], e.g., s32 means: “signed 32-
bit storage region”
– argc, argv and argt, e.g., if (argt[n]==f32) means: “If the type of
the nth variadic parameter is 32-bit float…”
– in() and out(), e.g., in(“/reg/$ra”,&r) means: “Place value contained
in the $ra register into the memory region pointed to by the variable
r.”; out(“/dev/tty”,famousquote()) means: “Send the output from
the function famousquote() to the tty device.”
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The Follow-through (2/2)
• Alter the C parser grammar to accept the new tokens in the
language
• Implement backend to generate actual assembly language
code (MIPS R2000, in my case) from the language (easier
said than done, but invaluable for proving that proposed
language extensions are indeed doable)
• Construct a paper detailing changes made to the language,
giving justifications and support for each
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Concluding Remarks
Important points…
• Start NOW!!! Don’t wait!!! The deadline is rapidly
approaching!!!
• Be bold. Be arrogant. Be sure to back up your claims with
adequate, compelling evidence!
• Lucidly express your ideas in writing with both principles and
examples.
• Collaborate with colleagues.
• Have fun.
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Course Project Calendar
•
•
•
•
•
•
•
Wednesday, 16 Feb: Proposal
Thursday, 17 Feb: Elevator Speeches
Week of 28 Feb - 4 Mar: Project meetings
Thursday, 23 Mar: Preliminary Report
Throughout Apr: Project meetings
Friday, 28 Apr: Final Report
Monday, 1 May, 6:30-9pm: Project
Presentations in the Rotunda, West Oval
Room
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Project Mantras 1
• Choose an ambitious topic, but be realistic
about what you can accomplish in one
semester
• Work steadily throughout the term; keep in
contact with your teammates using email and
regular group meetings
• Focus on design and understanding –
building things should be motivated by
solving a problem or conducting an
experiment
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Project Mantras 2
• Use Dave, John and your classmates are
resources
– Don’t wait for project meetings if you run into
problems, have ideas to bounce, etc.
• All teammates get same grade
– Let us know about team problems early
– Divide work in way so that you aren’t waiting for
teammates to finish their part
– Good team management is key (recommendation:
pick a manager)
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In Groups
• What are the important developments I
left out?
Use Wenger paper and your experience/knowledge
of things that have happened since 1976.
• Organize them into milestones.
• If time permits:
Develop a better overall history that
includes all the important
developments.
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Charge
• Read Algol papers
• How to read a language report
– Think about using features in a program
– Its not just a list of features, think about
interactions
• Meet in project groups, come up with a
project idea
• PS1 due Thursday in class
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