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Telecooperation/RBG Technische Universität Darmstadt Copyrighted material; for TUD student use only Introduction to Computer Science I Topic 1: Basic Elements.

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Presentation on theme: "Telecooperation/RBG Technische Universität Darmstadt Copyrighted material; for TUD student use only Introduction to Computer Science I Topic 1: Basic Elements."— Presentation transcript:

1 Telecooperation/RBG Technische Universität Darmstadt Copyrighted material; for TUD student use only Introduction to Computer Science I Topic 1: Basic Elements of Programming Prof. Dr. Max Mühlhäuser Dr. Guido Rößling

2 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 What is Programming? Let us take a look at what some godfathers of programming have to say: 2 To program is to understand Kristen Nygaard Programming is a Good Medium for Expressing Poorly Understood and Sloppily Formulated Ideas Marvin Minsky, Gerald J. Sussman

3 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 The Elements of Programming A powerful programming language (PL) is more than just a means for instructing a computer to perform tasks It also serves as a framework within which we organize our ideas about a problem domain 3 When we describe a language, we should pay attention to the means that it provides for combining simple ideas to more complex ones.

4 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 The Elements of Programming Every powerful language has three mechanisms to structure ideas about processes: –Primitive expressions Represent the simplest entities of the language –Means of combination Compound elements are built from simpler ones –Means of abstraction Compound elements can be named and manipulated as units 4

5 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Keys to Engineering Design Primitives –Resistors, capacitors, inductors, voltage sources, … Means of combination –Rules for how to wire together in a circuit –Standard interfaces (e.g. voltages, currents) between elements Means of abstraction –Black box abstraction – think about sub-circuit as a unit: e.g. amplifier, modulator, receiver, transmitter, … 5

6 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Language Elements - Primitives Numbers –Examples: 23, -36 –Numbers are self-evaluating: the values of the digits are the numbers they denote Boolean values –true and false –Also self evaluating Names for built-in procedures –Examples: +, *, /, -, =, … –What is the value of such an expression? –The value of + is a procedure We will later refer to these kinds of values as first-class procedures –Evaluating by looking up the value associated with the name 6

7 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Compound Elements 7 prefix notation (+ 2 3) left parenthesis Operator Operands right parenthesis The value of a compound element is determined by executing the procedure (denoted by the operator) with the values of the operands.

8 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 represents the application of the procedure to the numbers Compound Elements Compound Elements: –A sequence of expressions enclosed in parentheses –the expressions are primitives or compounds themselves Example: –Expressions representing numbers may be combined with expressions representing a primitive procedure ( + or * ) to form a compound expression 8 (+ 2 3) left parenthesis Operator Operands right parenthesis

9 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Compound Elements Can use nested combinations –just apply rules recursively 9 A combination always denotes a procedure application parentheses cannot be inserted or omitted without changing the meaning of the expression (+ 4 (* 2 3)) = (4 + (2 * 3)) = 10 (* (+ 3 4) (- 8 2)) = ((3 + 4) * (8 - 2)) = 42

10 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Abstractions 10 Create a complex thing by combining more primitive things, name it, treat it like a primitive. (define score (+ 23 7)) (define PI 3.14) Simple mean of abstraction: define

11 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Naming Compound Elements Special form: A bracketed expression, starting with one of the few keywords of scheme Example: define –using define we can pair a name with a value example: (define score (+ 23 7)) –The define special form does not evaluate the second expression (in the example: score ) –Rather, it pairs that name with the value of the third expression in an environment The return value of a special form is unspecified 11

12 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Naming and the Environment An important aspect of a programming language is the means it provides to refer to computational objects using names. –A name identifies a variable whose value is the object Environment: the interpreter maintains some sort of memory to keep track of the name-object pairs. –Associating values with symbols –Retrieve them later 12

13 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Naming and the Environment To get the value of a name, just look it up in environment –Example: the evaluation of score is 30 (define score (+ 27 3)) (define total ( )) (* 100 (/ score total)) –Note: we already did this implicty (looking up a name in an environment) for +, *, … 13 + * / … score total 30 25

14 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Evaluation Rules 1.Self evaluating return the value The values of digits are the numbers that they name 2.Built-in operator return the machine instruction sequence that carry out the corresponding operations. 3.Name return the value that is associated with that name in the environment. 4.Special form do something special. 5.Combination I.Evaluate the sub expressions (arbitrary order) II.Apply the procedure that is the value of the leftmost sub expression (the operator) to the arguments that are the values of the other sub expressions (the operands). Example of a combination: (+ 4 (* 2 3)) 14

15 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Evaluating Combinations The evaluation rule is recursive as one of its steps, the rule needs to invoke itself –Every element has to be evaluated before the whole evaluation can be done Evaluating the following combination requires that the evaluation rule be applied to 4 different combinations. 15 ( * (+ 2 (* 4 6) ) ( ) )

16 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Read-Eval-Print-Loop define-rule: –Only evaluate the second operand –The name of the first operand is bound to the calculated value –The overall value of the expression is undefined 16 (define PI 3.14) eval define-rule undefined print Differences between Scheme versions Name Value PI3.14 PI --> 3.14" Visible world Execution world

17 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Read-Eval-Print-Loop calculate self-rule print Expression Value printed representation of the value PI 3.14 eval name-rule print Value Naming-rule: Look-up the value in the current environment using the name Visible World Execution World Expression

18 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Capturing common patterns Here are some common patterns (* 3.14 (* 5 5)) (* 3.14 (* )) (* 3.14 (* x x)) How do we generalize –(e.g. the last expression)? –i.e. how to express the idea of circle area computation? 18 They are instances of a circle area computation

19 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Creating new procedures We use procedures to capture ways of doing things –sometimes we also use the name function –similar to a function in mathematics The define special form is used to create new procedures 19 Name Parameter (define (area-of-disk r) (* 3.14 (* r r))) Body of procedure

20 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Creating new Procedures As soon as a procedure has been defined, we can use it as if it were a primitive procedure (such as +, * etc.) –Example - area of a circle: (area-of-disk 5) = 78.5 –Example - area of a ring: (- (area-of-disk 5) (area-of-disk 3)) = ( ) = = -

21 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Creating new procedures Existing procedures can be combined to new, more powerful procedures –Example: calculate area of a ring –Example: Using the new procedure –(area-of-ring 5 3) = (- (area-of-disk 5) (area-of-disk 3)) = (- (* 3.14 (* 5 5)) (* 3.14 (* 3 3))) = … = (define (area-of-ring outer inner) (- (area-of-disk outer) (area-of-disk inner)))

22 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Informal specifications Typical program specification –Usually not in mathematical terms that can be directly transformed into programs –Often rather informal problem specifications May contain irrelevant or ambiguous information Example: 22 Company XYZ & Co. pays all its employees $12 per hour. A typical employee works between 20 and 65 hours per week. Develop a program that determines the wage of an employee from the number of hours of work. problem analysis (define (wage hours) (* 12 hours))

23 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Errors Your programs will contain errors –This is normal –Dont get confused or frustrated by your errors Possible errors: –Wrong number of brackets, i.e. (* 3 (5) –The operator of a procedure call is not a procedure (10) ( ) –other typical runtime errors: (+ 3 true) (/ 3 0) Try out what is happening in erroneous programs and try to understand the error message! 23

24 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Designing Programs The design of programs is not trivial The following design recipe helps you in writing your first program: –step-by-step prescription of what you should do –Later we will refine this recipe 24 Any program development requires at least the following four activities: 1. Understanding the program's purpose 2. Thinking about program examples 3. Implementing the program body 4. Testing

25 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Designing Programs 1.Understanding the program's purpose –calculate the area of a ring: –calculate the area of the ring that has an outer radius outer and an inner radius inner –It can be calculated using the radius of the circle with radius outer and subtracting the area of the circle with radius inner –… 25 If you can't write it down in English, you can't code it. Peter Halpern

26 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Designing Programs 1.Understanding the program's purpose –Giving the program a meaningful name –Definition of a contract What kind of information is consumed and produced? –Adding the program header –Formulate a short purpose statement for the program, that is a brief comment of what the program is to compute 26 ;; area-of-ring :: number number -> number ;; ;; to compute the area of a ring, ;; whose hole has a radius of inner (define (area-of-ring outer inner) … )

27 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Designing Programs 2.Program Examples –Help to characterize the input and output –Examples help us to understand the computational process of a program and to discover logical errors –It is easier to understand something difficult with an example For our example: 27 ;; area-of-ring :: number number -> number ;; to compute the area of a ring, ;; whose hole has a radius of inner ;; Example: (area-of-ring 5 2) is (define (area-of-ring outer inner) … )

28 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Designing Programs 3.Implement the program body –Replace the... in our header with an expression –If the input-output relationship is given as a mathematical formula, we just translate –In case of an informally stated formula, we have to understand the computational task the examples of step 2 can help us 28 ;; area-of-ring :: number number -> number ;; to compute the area of a ring, ;; whose hole has a radius of inner ;; Example: (area-of-ring 5 2) is (define (area-of-ring outer inner) (- (area-of-disk outer) (area-of-disk inner)))

29 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Designing Programs Testing i.e. with the DrScheme Testcases (Special -> Insert Testcase) to discover mistakes in particular for non local errors

30 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 30 Testing can show the presence of bugs, but not their absence. Edsger W. Dijkstra Beware of bugs in the above code; I have only proved it correct, not tried it Donald E. Knuth

31 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Auxiliary Functions When should we use auxiliary functions? Example: 31 The owner of a performance theater wants you to design a program that computes the relationship between profit and ticket price At a price of 5 per ticket, 120 people attend a performance. Decreasing the price by 0.10 increases attendance by 15 people. Each performance costs the owner 180. Each attendee costs 0.04.

32 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Auxiliary Functions: Bad Design 32 ;; How NOT to design a program (define (profit price) (- (* (+ 120 (* (/ 15.10) ( price))) price) (+ 180 (*.04 (+ 120 (* (/ 15.10) ( price)))))))

33 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Auxiliary Functions: Good Design 33 ;; How to design a program (define (profit ticket-price) (- (revenue ticket-price) (cost ticket-price))) (define (revenue ticket-price) (* (attendees ticket-price) ticket-price)) (define (cost ticket-price) (+ 180 (* 0.04 (attendees ticket-price)))) (define (attendees ticket-price) (+ 120 (* 15 (/ ( ticket-price) 0.10))))

34 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Guideline on Auxiliary Functions Formulate auxiliary function definitions for every dependency between quantities mentioned in the problem statement or quantities discovered with example calculations. 34

35 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Procedures as Black-Box-Abstractions Abstraction helps hiding complexity Details that are irrelevant for understanding from a special point of view are ignored. 35

36 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Procedures as Black-Box abstractions 36 Will consider several fundamental kinds of abstraction in this course. Procedural abstraction is one: –area-of-ring computes the area of a ring –user doesn't have to think about the internals Input Output We know what it does, but not how. black-box-abstraction

37 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Procedures as Black-Box abstractions A computing problem is often broken down into natural, smaller sub-problems. –Example: area of a ring 2* Calculating the area of a circle –Procedures are written for each of these sub problems. area-of-disk,… primitive procedures … 37

38 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Procedures as Black-Box abstractions The procedure attendees can be seen as black box. We know that it calculates the number of attendees. But we do not want to know how it works. These details can be ignored. attendees is a procedural abstraction for revenue/cost. 38 profit revenue cost attendees

39 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Procedures as Black-Box abstractions A user defined procedure is called by a name, as are primitive procedures How a procedure works remains hidden. 39 At this level of abstraction, any procedure that calculates squares is as good as any other. (define (square x) (* x x)) (define (square x) (* (* x 10) (/ x 10))) area-of-ring area-of-circle square

40 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 constant definition Guideline on Variable Definitions: –Better to read –Easier to maintain changes must be made at one point only –In our example: (define PI 3.14) –We only need one change for a better approximation (define PI ) 40 Give names to frequently used constants and use the names instead of the constants in programs

41 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Conditional Expressions Two modes: 1) (if ) not optional in Scheme Example : (define (absolute x) (if (< x 0) (- x) x)) 41

42 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Conditional Expressions Two modes: 2) (cond [ ] [ ]... [else ]) optional Example : (define (absolute x) (cond [(> x 0) x] [(= x 0) 0] [else (- x)])) 42

43 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Comments on conditionals A test is true if the evaluation is true A branch of a cond can have more than one expression: (... ) –As long as we have no side effects, we do not need more than one expression ( ) returns value of The else branch must contain at least one expression 43

44 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Boolean functions (and... ) – (i = 1..N) evaluated in order of appearance; –returns false if any expression is evaluated to false, else the return is true (shortcut). –If one of the expressions returns neither true or false, then an error will occur. –Some expressions will not be evaluated due to the shortcut-Rule 44 (and (= 4 4) (< 5 3)) false (and true (+ 3 5)) Error: and: question result is not true or false: 8 (and false (+ 3 5)) Shortcut-Rule: false

45 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Boolean functions (or... ) – (i = 1..N) evaluated in order of occurrence; –returns true after the first value is evaluated to true ; –returns false if all expressions are false –An error occurs if a value evaluates to neither true or false 45 (or (= 4 4) (< 5 3)) true (or true (+ 3 5)) Shortcut-Rule: true (or false (+ 3 5)) Error: or: question result is not true or false: 8

46 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Boolean functions (boolean=? ) –expr1, expr2 evaluated in order of appearance; –returns true, if expr1 and expr2 both produce true or both produce false –returns false, if the operands have different Boolean values –an error occurs, if an operand evaluates to neither true or false (not ) –returns true when evaluates to false –returns false when evaluates to true 46

47 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Designing Conditional Functions How does our design process change? –New Phase: Data analysis Which different situations exist? –Examples choose at least one example per situation –Implementing the program body First write down the skeleton of a cond/if expression, then implement the individual cases –Testing tests should cover all situations 47 Program development requires at least the following four activities 1. Understanding the program's purpose 2. Making up examples 3. Implementing the program body 4. Testing

48 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Symbols Up to this point, we know numbers and Booleans as primitive values Often we want to store symbolic information –names, words, directions A symbol in Scheme is a sequence of characters, headed by a single quotation mark: –the dog ate a cat! two^3 and%so%on? –Not all characters are allowed (i.e. no space) Only one operation on this data type: symbol=? –(symbol=? hello hello) true –(symbol=? hello abc) false –(symbol=? 1 2) error Symbols are atomic (like numbers, Booleans) –Symbols cannot be separated 48

49 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Symbols: Example 49 (define (reply s) (cond [(symbol=? s 'GoodMorning) 'Hi] [(symbol=? s 'HowAreYou?) 'Fine] [(symbol=? s 'GoodAfternoon) 'INeedANap] [(symbol=? s 'GoodEvening) 'BoyAmITired] [else 'Error_in_reply:unknown_case] ))

50 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Symbols vs. Strings Many of you may know the data type String Symbols are different from Strings –Symbols: Are used for symbolic names atomic, no manipulation, very efficient comparison certain restrictions which characters can be represented –Strings: Are used for text data Manipulation possible –(i.e. search, compose etc.) Comparison is expansive Any kind of character (string) is possible –Strings are also available in Scheme To generate with a double quotation mark; compare with string=? –For now we will ignore strings 50

51 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Reminder: The Evaluation-Rule 1.self evaluated … 2.built-in operator … 3.Name … 4.special form … 5.Combination I.Evaluate the sub expressions (in any order) II.Apply the procedure that is the value of the leftmost sub expression (the operator) to the arguments that are the values of the other sub expressions (the operands). 51 Up to now we have only considered built-in procedures. How to evaluate procedures that are defined by the programmer?

52 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Extended Evaluation-Rule Evaluation rule for procedures –The procedure is a primitive procedure execute the respective machine instructions. –The procedure is a compound procedure Evaluate the procedure body Substitute each formal parameter with the respective actual value, that is passed when applying the procedure. 52 (define (f x ) (* x x)) (f 5 )

53 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Substitution Model Fictive names (formal parameters/variables): –allow the definition of general procedures that can be reused in various situations. When using the procedures, the actual values need to be associated with the fictive names. As known from algebra: 53 f(a, b) = a 2 + b 2 Declaring the formal parameters Defining the function using formal parameters f (3, 2) Using the general function to solve a particular problem

54 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Substitution Model 54 Associating the actual values when executing Calling environment ab a * a + b * b... (define b 2)... (f 3 2) (f b 2) (define b 2)... (f 3 2) (f b 2) Procedure environment of f (define (f a b) (+ (* a a) (* b b)))

55 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Substitution Model (define b 2)... (f 3 2) (f b 2) (define b 2)... (f 3 2) (f b 2) ab a * a * 3 13 b * b2 * 2 Associating the actual values when executing Calling environment Procedure environment of f (define (f a b) (+ (* a a) (* b b)))

56 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Substitution Model (define b 2)... (f 3 2) (f b 2) (define b 2)... (f 3 2) (f b 2) ab a * a + Procedure environment of f * 2 8 b * b2 * 2 Associating the actual value when executing Calling environment

57 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Substitution Model The purpose of the substitution model is to help us think about procedure application –It does not provide a description of how the interpreter really works –Typically, an interpreter does not evaluate procedure applications by manipulating the text of a procedure to substitute values for the formal parameters. This is a simplified model to get started thinking formally about the evaluation process –More detailed models will follow later on –Allows you to execute a program on a piece of paper 57

58 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Details of the Substitution Model: applicative order of evaluation (define (square x) (* x x))) (define (average x y) (/ (+ x y) 2))) (average 5 (square 3)) (average 5 (* 3 3)) (average 5 9) first evaluate the operands, then do the replacement (applicative order) (/ (+ 5 9) 2) (/ 14 2) If the operator is a simple procedure, replace it 7 with the result of the operation 58

59 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Details of the Substitution Model: normal order of evaluation (define (square x) (* x x)) (define (average x y) (/ (+ x y) 2)) (average 5 (square 3)) (/ (+ 5 (square 3)) 2) (/ (+ 5 (* 3 3)) 2) (/ (+ 5 9) 2) (/ 14 2) 7 59 normal order

60 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Applicative vs. normal order of evaluation Applicative: First evaluate the operator and all operands, then substitute Normal: Evaluate operator, then substitute the (not evaluated) operands for the formal arguments of the operator Important, non-trivial property: The result does not depend on the order of evaluation (confluence) –However, termination of the evaluation process may depend on the evaluation order –We will see features (assignment, in-/output) which destroy this characteristic later –Sometimes both strategies can be very different in the number of evaluation steps argument is not required normal order wins argument is required several times applicative order wins 60

61 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Review: Scheme Things that constitute a Scheme program: –self evaluating 23, true, false, –names +, PI, pi –combinations (+ 2 3) (* pi 4) –special forms (define PI 3.14) Syntax –combination: (oper-expression other-expressions …) –special form:a special keyword as first sub routine Semantics –combinations:evaluate subroutines in any order, use the operator for the operands substitution for user-defined procedures –special forms:each form has its own 61

62 Dr. G. Rößling Prof. Dr. M. Mühlhäuser RBG / Telekooperation © Introduction to Computer Science I: T1 Summary We have learned: –The simplest elements (data/procedures) of Scheme –Combination as a composing instrument of simpler elements into more complex elements –How to make combinations to use them further as elements in other combinations –How to define own procedures – process pattern – and use them as basic elements of combinations _______________________ Scheme ________________________ –Separate problems to smaller exact defined tasks –Procedures as Black-Box abstraction –Semantic of a procedure call as a substitution process 62


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