1. INTRODUCTION
"When the only tool you have is a hammer, everything looks like a nail" (Abraham Maslow)

2. Course Themes/Topics Syntax & Feature decisions
Support for Reuse/Polymorphism
Error handling
Dynamic vs static, implicit vs explicit
Meta programming
Functional programming

3. Course Format Sage on stage vs Guide on side...
Group discussions are not intended to return you to kindergarten. Some questions are just at the factual level, but some require you to go to stackoverflow etc. to compare, contrast, etc.
Stackoverflow discussions can actually be richer than textbook definitions, because they are written by professionals who have spent a lot of time reflecting. Lifelong learning.
Tests tend to focus less on code, more on language concepts.

4. Categories of Programming Languages
ming_languages_by_type
With a partner:
What categories include Java?
What categories include Ruby?
Read through all the categories. Which ones are familiar? Which have you never heard of?

5. Language Evaluation Criteria
What criteria would you use to evaluate/choose a language?
Brainstorm – don’t look ahead!

6. Language Evaluation Criteria
Writability: how easy is it to write a program?
Readability: how easy is it to read a program?
Reliability: does it include features that help to produce more reliable software?
Cost: what’s the ultimate cost?
Categories proposed by Sebesta

7. Writeable and Readable
Simplicity
Support for abstraction
Control statements
Data types
Syntax
Orthogonality
Expressivity
What aspects of a language might make it easier to read than write (or vice versa)?

8. Orthogonality
A relatively small set of primitive constructs can be combined in a relatively small number of ways
Every possible combination is legal
Changing one thing has no effect on another
As stated by Michael Scott:
Orthogonality means that features can be used in any combination, the combinations all make sense, and the meaning of a given feature is consistent regardless of other features with which it is combined.
261 example: arrays
Java: no default params

9. Evaluation Criteria: Reliability
Type checking
Testing for type errors
Exception handling
Intercept run-time errors and take corrective measures
Aliasing
Presence of two or more distinct referencing methods for the same memory location
Readability and writability
A language that does not support “natural” ways of expressing an algorithm will necessarily use “unnatural” approaches, and hence reduced reliability

10. Evaluation Criteria: Cost
Training programmers to use language
Writing programs (closeness to particular applications)
Compiling programs
Executing programs
Language implementation system: availability of free compilers (Ada vs Java)
Reliability: poor reliability leads to high costs
Maintaining programs
How does this relate to programming languages?

11. Evaluation Criteria: Others
Portability
The ease with which programs can be moved from one implementation to another
Generality
The applicability to a wide range of applications
Well-definedness
The completeness and precision of the language’s official definition
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12. Language Design Trade-Offs
Reliability vs. cost of execution
Conflicting criteria
Example: Java demands all references to array elements be checked for proper indexing but that leads to increased execution costs
Readability vs. writability
Another conflicting criteria
Example: APL provides many powerful operators (and a large number of new symbols), allowing complex computations to be written in a compact program but at the cost of poor readability
Writability (flexibility) vs. reliability
Example: C++ pointers are powerful and very flexible but not reliably used. Not included in Java.

13. Expressivity
Find something to share with the class – turn in for attendance points
ranked-by-expressiveness/
when-referring-to-programming-languages
programming-language-literature.html
programming.html

14. Evaluation Criteria: the Players
Language implementors: concerned with difficulty of implementing constructs and features
Language users: worried about writability first, readability later
Language designers: likely to emphasize elegance and ability to attract widespread use
(on your own:
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15. Influences on Language Design
Computer Architecture
Programming Methodologies
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16. Computer Architecture Influence
Well-known computer architecture: Von Neumann
Imperative languages, most dominant, because of von Neumann computers
Data and programs stored in memory
Memory is separate from CPU
Instructions and data are piped from memory to CPU
Basis for imperative languages
Variables model memory cells
Assignment statements model piping
Iteration is efficient
John Von Neuman ( ). Mathematician, influential in set theory, quantum mechanics, game theory, self-replicating cellular automata, pseudo-random numbers and more. On faculty of Princeton Institute for Advanced Studies with Einstein and Godel. VonNeumann architecture based on ENIAC.
Copyright © 2006 Addison-Wesley. All rights reserved.

17. Programming Methodologies Influences
1950s and early 1960s: Simple applications; worry about machine efficiency
Late 1960s: People efficiency became important; readability, better control structures
structured programming
top-down design and step-wise refinement
Late 1970s: Process-oriented to data-oriented
data abstraction
Middle 1980s: Object-oriented programming
Data abstraction + inheritance + polymorphism
Current
Functional programming, concurrency

18. Language Categories Imperative/Procedural Functional Logic
Central features are variables, assignment statements, and iteration
Examples: C, Pascal, scripting languages such as Perl
Functional
Main means of making computations is by applying functions to given parameters
Examples: LISP, Scheme, Haskell
Logic
Rule-based (rules are specified in no particular order)
Example: Prolog, SQL
Object-oriented
Data abstraction, inheritance, late binding
Examples: Java, C++, C#
Markup
New; not a programming language per se, but used to specify the layout of information in Web documents
Examples: XHTML, XML
What about CSS?

19. More Language Categories
Stack Based
Stack is central feature
Examples: PostScript, Forth
Prototype
Use the object, not the class, as the basis for object definition and inheritance
Examples: Io, Lua, Self, JavaScript

20. End of Lecture
More info for you to explore on your own

21. Implementation Methods
Compilation
Pure Interpretation
Hybrid Implementation Systems

22. Think like a compiler
Scanner (lexical analyzer): identifies the tokens of a program statement
Parser (syntax analyzer): determines whether the statement is valid, based on the language definition/grammar
int count = 20;
Tokens:
int
count = 20 ;
Grammar:
Based on BNF

23. The Compilation Process
Compilation process has several phases:
lexical analysis: converts characters in the source program into lexical units
syntax analysis: transforms lexical units into parse trees which represent the syntactic structure of program
Semantics analysis: generate intermediate code
code generation: machine code is generated
Slow translation, fast execution
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24. Additional Compilation Terminologies
Load module (executable image): the user and system code together
Linking and loading: the process of collecting system program and linking them to user program