LISP Power and Elegance in ONE Overview The

LISP: Power and Elegance in ONE

Overview The History of Lips n Lisp, Mathematics and Elegance n The Power of Lisp n Lisp in Commercial Use n

Some Interesting Quotations “Lisp is worth learning for the profound enlightenment experience you will have when you finally get it; that experience will make you a better programmer for the rest of your days, even if you never actually use Lisp itself a lot” -Eric Raymond, “How to Become a Hacker”

More Quotations “I have heard more than one Lisp advocate state such subjective comments as, “Lisp is the most powerful and elegant programming language in the world” and expect such comments to be taken as objective truth. I have never heard a Java, C++, C, Perl, or Python advocate make the same claim about their own language of choice” - A guy on Slashdot. com “Lisp… made me aware that software could be close to executable mathematics. ” -L. Peter Deutsch

History of Lisp n In 1960 John Mc. Carthy published a paper where he outlined that given some simple operations and notation for functions, one can build a whole programming language. – Primitive operation were either an atom or a list of atoms. So, foo, (), (foo) , (foo bar) , were all considered expressions. – Functions were denoted as (lambda (p. . ) e) a. . ). n This was more of a theoretical exercise, in an effort to define a more convenient alternative to the Turning Machine.

Lisp as Theory “Another way to show that Lisp was neater than Turning machines was to write a universal Lisp function and show that it is briefer and more comprehensible than the description of a universal Turning Machine. This was the Lisp function eval…, which computes the value of a Lisp expression… Writing eval requires inventing a notation representing Lisp functions as Lisp data, and such a notation was devised for the purposes of the paper with no thought that I would used to express Lisp programs in practice. ” -John Mc. Carthy

Theory turns to Practice: the birth of Lisp the language n Later that year one of Mc. Carthy’s graduate students, Steve Russell, figured out a way to translate the eval function into machine language. “Steve Russell said, look, why don’t I program this eval… and I said to him, ho, you’re confusing theory with practice, this eval is intended for reading, not for computing, But he went ahead and did it. That is, he compiled the eval in my paper into [IBM] 704 machine code, fixing bugs, and then advertised this as a Lisp interpreter, which it certainly was. So at that point Lisp had essentially the form that it has today…. ” -John Mc. Carthy

What made Lisp Different n n n n n Conditionals: such as if-then-else construct. Function types: where functions are just like integers and strings Recursion: first language to support it. Dynamic typing: all variable are pointers. Garbage-Collection. Programs composed of expressions. A symbol type. A notations for code using trees of symbols and constants. The whole language is there all the time.

Lisp, Mathematics and Elegance “Lisp is the only computer programming language that is mathematically respectable, because its the only one that I can prove theorems about” -G. J. Chaitin

Lisp and Mathematics n Lisp is Set Theory for computable mathematics rather than for abstract mathematics. – A set is made up of objects. ä In mathematics a set is represented like so {A, B, C, }. ä In lisp, this simple set would look like (A B C). ä A more complex set- (A (B C) 123)

More on Lisp and Mathematics n Why Lips is mathematical: – time is not a constraint – a program is essentially an expression – expressions are evaluated returning a value – the programmer is not forced to assign value to variables

Elegant Lisp Programs n Lisp can be used to prove interesting mathematical problems dealing with formal axiomatic systems. – Gödel’s Incompleteness Theorem: which states that within any formal system, there are truths which may be expressed though they are not provable within the system. n n Gödel's original proof of the incompleteness theorem is based on the paradox of the liar: “This statement is false. '' e. g. , try to prove that a Lisp expression is elegant if no smaller expression gives the same value that it does. (YOU CAN’T!!!!)

The Power of Lisp n n The Power of Simplicity Rapid Prototyping Unique Functionality High-Performance: Lisp vs. Java, C, C++

The Power of Simplicity n Lisp is syntactically clean and simple – symbolically designed – faster learning-curve – more time spend on coding

Rapid Prototyping Lisp is comprehensive n It supports modular design. n – Using complex constants in code – Macros – Optional Declaration – Higher Order Function

Lisp is Comprehensive n Lisp includes an extraordinary powerful set of predefined tools: – – – Numbers Characters Arrays Cones Symbols, Packages, and Readtables Functions Hash Tables Streams Classes, Methods, and Generic Functions Pathnames Conditions and Restarts

Lisp Supports Modular Design n Using complex literals in code: – in production code, you might want to make a global variable to keep track of a quantity shared by several modules, >(defvar *club-members* ‘()) >(defun add-club-member (who) (pushnew who *club-member*)) >(defun is-club-member? (who) (member who *club-member*)) – in prototyping doing minimal amount of work is needed to make the program run, >(defun is-club-member (who) (member who ‘(joe sally fred))

Continuation n Macros – Macros is what makes Lisp superior compared all other languages. – Macros introduce a unique functionality that allows programs to write other programs. – It’s a real boon to rapid prototyping. Instead of writing >(setf x nil) We can write a macro >(defmacro nil! (x) (list ‘setf x nil)) >(nil! x) NIL

Continuation n Higher Order Functions – Lisp posses the ability to pass functions as arguments to other functions. n Optional Declarations – Lisp does not enforce declarations, so writing a function such as, >(defun twice (x) (* 2 x)) will suffice for prototyping.

Lisp vs. Java, C++ n In a recent study Prechelt (1999) compared the relative performance of Java and C++ in execution time and memory usage.

Lisp vs. Java, C++ n n Lisp’s performance is comparable to or better than C++ in execution speed. Significantly lower variability, which translates into reduced project risk. Development time was found to be significantly lower and less variable than either C++ or Java. Memory consumption is comparable to Java.

Some Data n n Development time for Lisp ranged from low of 2 hours to high of 8. 5 hours, compared to a range of 3 to 25 hours for C and 4 to 63 hours for Java. Lisp programs were significantly shorter than C, C++, and Java programs – Lisp programs ranged from 51 to 182 lines of code, median was 134 lines. – C, C++, and Java programs ranged from 107 to 614 lines of code, with the median of 244 lines.

The Power is in the Code n Consider the following problem, where we want to write a function that generates accumulators, i. e, a function that takes a number n, and returns a function that takes another number i and returns n incremented by i. – In Common Lisp this would be: >(defun foo (n) #’ (lambda (i) (incf n i))) – In Java we get: public interface Inttoint { public int call(int i); } public static Inttoint foo(final int n) { return new Inttoint() { int s = n; public int call(int i) {s = s+i; return s; }}; }

Lisp in Commercial Use n Yahoo Store, used to be called Viaweb. – Founded by Paul Graham – Lisp was the primary development language for the server-based applications. – 20 -25% of the source code for Viaweb was made up macros. n Orbitz. com – came in rather late into the online travel market, with competitors such as Travelocity and Expedia already dominating the industry. – Completely rewrote the entire flight search engine package in Lisp, giving greater functionality and searching capabilities than with the standard legacy systems used by its competitors. – Using Lisp, made Orbitz almost completely self-sufficient, with minimal dependence on third-party vendors.

QUESTIONS?