1. 1. CS152 PROGRAM PARADIGMS 1/26/2015 San Jose State University Computer Science Kaya Ota 4/14/2015
2. 2. PROGRAMING PARADIGMS Important concept of Abstraction Computational paradigms What is the language? Have a grammar rule Way to communicate Definition of language : the set of words and sign that people use to communicate each other. 4/14/2015
3. 3. PROGRAMMING LANGUAGE What is the programming language? Programing language is a notation for communicating to a computer what we want it to do. Paradigms = Or 4/14/2015
4. 4. HISTORY OF COMPUTER LANGUAGE 1940 : Hard wired Spaghetti code comes from here Late 1940 : Machine code has invented by John Von Neumann CPU Arithmetic / logic unit control unit Memory unit outputinput John Von Neumann model 4/14/2015
5. 5. HISTORY OF COMPUTER LANGUAGE Binary code has a problem Reading , debugging, tightly coupled with machine i.e. less portability Assembly language (get closer to human language) Problem of Assembly: limited instruction set Criteria Readability Debugblity Portability Abstraction 4/14/2015
6. 6. HISTORY OF COMPUTER LANGUAGE What is abstraction in computer science ? Definition of Abstraction Abstraction is the ability to separating the interface from the implementation and creating a new concept 4/14/2015 Abstraction allows programmers to consider a sequence of actions as a single action
7. 7. ASSEMBLY LANGUAGE 4/14/2015
8. 8. PROGRAMMING LANGUAGE 4/14/2015
9. 9. HIGH LEVEL LANGUAGE High Level Language is notations that are closer to human language Fortran (Formula Translation) Support Algebraic notations Floating number Not Support Control statement Array Functions Data Structures 4/14/2015
10. 10. HIGH LEVEL LANGUAGE AlGOL (Algorithmic Language) 1st Language that support Loop Array 4/14/2015
11. 11. ABSTRACTION IN PROGRAM LANGUAGE How we can categorize Abstractions in programming languages ?? 2 types of Abstractions Data To simplify behaviors and attributes for humans Control To simplify properties of the transfer of control Example: Loop, Functions, Conditional Statement 4/14/2015
12. 12. ABSTRACTION IN PROGRAM LANGUAGE Data Abstraction 3 levels of data abstractions Basic Data Abstraction Basic data = hide internal representations Variable = use symbolic name to hide location of memory We HIDE binary representations and IEEE single or double precision standard representations by using variable. Structured Data Abstraction Array Unit Data Abstraction Java class and package, module 4/14/2015 These variables are called atomic or primitive Normally can not access the component part
13. 13. ABSTRACTION IN PROGRAM LANGUAGE Basic Control Abstraction = combine a few machine instruction into an abstract statement Shorthand notation (syntactic sugar) example: x+=5 Structured Control Abstraction = selection, branching, iteration Functions are close to what it is meant to be mathematically Functions can be understood independent of Von Neumann model Functions can have higher-order functions Func1 Func2 Data FUNCTION Another function Can return function TIP Function is required return something Procedure is NOT 4/14/2015
14. 14. ABSTRACTION : UNIT CONTROL Unit Control Abstraction = combine a few machine instruction into an abstract statement. Thread is categorized here Program service class1 class2 class3 request responce 4/14/2015
15. 15. COMPUTATIONAL PARADIGMS Imitating the operations of a computer 1. Imperative paradigms (most of the programming languages) Sequential execution Use of variable Use of assignment to change the values of the variables Parallel computation: computations that can be applied to many different pieces of data simultaneously Undeterministic computation: computations that does not depend on order of process 2. Functional paradigms Based on the abstract notation of a function in lambda calculus 3. Logic paradigms Based on symbolic logic Both based on math, i.e. we can use math to see if a prog works correctly 4/14/2015
16. 16. COMPUTATIONAL PARADIGMS Language Definition Benefit of math definition We can reason mathematically Prog-lang can be independent on implementation Discipline 2 Part Syntax similar to grammar of a natural language Semantic the meaning of the statement 4/14/2015
17. 17. THE POPULARITY OF PROGRAM LANGUAGE The popularity of programming language is measured by: i. Number of skilled programmer ii. Number of course in school What is the good programming language design? i.e. how do we define success or failure of programming language ? General Criteria for design language Efficiency Security 4/14/2015
18. 18. GOOD PROGRAMMING LANGUAGE We determine the goodness of programming language by the criteria below Readability Debuggability Writability Portability Having mechanisms of abstraction + alpha 4/14/2015
19. 19. SUCCESS / FAILURE LANGUAGE Determinants for success or failure programming language Achieve the goal Attains widespread use in Applications Serve as a model for the other languages 4/14/2015
20. 20. HISTORY OVERVIEW Early day, machines were SLOW and memories were EXPENSIVE Time complexity and Space complexity were primarily concerns! COBOL common business oriented language = improve readability 1970s = focus on simplicity and abstraction Mathematical definitions for languages were developed Example) Pascal, Modula2, C, Ada Last 25 years = focus on Reusability is a big concern Java 4/14/2015
21. 21. LIFE CYCLE OF SOFTWARE Life cycle of software Other includes Analyses, Design, Debug, Coding, Test Software becomes: 1. More complexity 2. Need to adapt to change 5% Other 95% Maintenance Readability 4/14/2015
22. 22. MEASUREMENT OF PROGRAMMING LANGUAGE 1. Efficiency 1. Target Code (i.e. executable code) 2. Developing 2. Readability 3. Writability 4. Portability (key success of java) 5. Deguggability 6. Reusability 7. Abstraction 8. Reliability 4/14/2015
23. 23. EFFICIENCY 1. Target Code (executable code ) Java: int x = 10 (type strict) Javascript ver x = 10 At runtime, machine check the type of x for javascript inefficient Type strict is more efficient 2. Developing Readability and Writability are important Expressiveness Conciseness of syntax 4/14/2015
24. 24. REGULARITY How well the features of languages are integrated Fewer restriction 1. Generality Ability or use of a construct Combining related constructs into a single or more general Ex) if(x == 5) is valid when x is primitive type If (obj == aobj) is not valid 4/14/2015
25. 25. REGULARITY 1. Orthogonality Allows languages construct to be combined in meaningful way. In a language that is truly orthogonal, language constructs do not behave differently in different way. Associated with simplicity, the more orthogonal design, the fewer exceptions Lack of Orthogonality: in C, we can not return Array (we deal with it as an exception) in Pascal, we cannot return Object and Array (we deal with them as an exception) So, they are lack of orthogonality in Other Languages, we can return any thing you want! No exception YES Orthogonal! 4/14/2015
26. 26. REGULARITY 1. Uniformity: Similar things look similar! Refers to the consistency of appearance and behavior of a language. Example in C++ Class Definition: class Abc { // implementation }; semicolon needed! Function Definition: int f(int x){// implementation} semicolon unneeded! Both are definition(similar things) but looks different! Therefore, this is lack of uniformity 4/14/2015
27. 27. REGULARITY Uniformity: Similar things look similar Example in Pascal function f : boolean ; // function definition begin .. f : = true // assignment . end; Different things(definition vs. assignment) but looks similar. So, this is also an example of lack of Uniformity 4/14/2015 In java boolean f() {..} In java boolean f = true;
28. 28. SECURITY (I.E. RELIABILITY) Reliability Program language is reliable if it prevents the programmer to misuse the certain features If allows the errors be discovered and reported quickly Semantically Safe The language is semantically safe if it prevents a programmer from compiling and executing any statement that violate the definition of the language. Errors Caught by Compiler (checked) Errors Caught by Runtime (unchecked) Errors Caught by Nothing All Program Errors 4/14/2015
29. 29. FUNCTIONAL PROGRAMMING CH3 4/14/2015
30. 30. LAMBDA CALCULUS Mathematical formalism for expressing computation by function expression constant | variable | (exp exp) | (lambda x. exp) Define d as OR Separato r Inpure lambda = numbers are not expressed by functions Pure lambda = numbers are expressed by functions 4/14/2015
31. 31. LAMBDA CALCULUS 4/14/2015 Lambda Calculus Representation Ordinary Mathematical Representation
32. 32. LAMBDA CALCULUS Free and Bound variables x is said to be a bound variables (i.e. local variable in CS side) Otherwise, variables are said to be free Scope of x is in ( ) 4/14/2015 x is bound y is free z is bound x is free
33. 33. PASS BY VALUE AND PASS BY NAME 4/14/2015 Pass by Value Pass by Name Remark: Pass by value is NOT ALWAYS EQUAL to pass by name
34. 34. PASS BY VALUE AND PASS BY NAME 4/14/2015
35. 35. HIGHER ORDER FUNCTION Higher order function can return a function Transformation : Alpha-Conversion Changing the name of bound variables Beta-Conversion (Beta-Induction) Beta-Conversion is primary way of transforming lambda calculus 4/14/2015
36. 36. PROGRAM AS FUNCTIONS Math Function Rule f: x y X black box y 4/14/2015 Set X {x1, x2...} Set Y {y1, y2} Mapping Domain Range
37. 37. DIFFERENCE BETWEEN IMPERATIVE AND FUNCTIONAL Imperative programming A variable = memory address that store a value Functional programming No assignment So, No loop BUT Recursive call 4/14/2015 Memory 0xFFFFFF int x = 1; refer
38. 38. REMAINDER Java is ALWAYS Pass by value Pass by value The local parameters are copied of the original arguments passed in Changes made in the function to these variables do not affect originals Pass by Reference The local parameters are reference to the storage locations of the original arguments Changes to these variables in the function will affect the originals No Copy made. So, overhead of copying (time and storage) is saved 4/14/2015
39. 39. OOP AND OOD CS152 3/12/2015
40. 40. OBJECT ORIENTED PARADIGM Encapsulation contribute to SE needs: We can change implementation and be still works as long as we do not change signature
41. 41. OBJECT ORIENTED PARADIGM Encapsulation The ability of bundling data and behaviors together and control how it works. Abstraction The ability of separating the interface from implementation What we call class in java
42. 42. INHERITANCE Class A Default m3() Protected m2() Private m4() Public m1() Class B What is the visibility from B In A ??
43. 43. Class B B can have access: Public Default Protected Class A Default m3() Protected m2() Private m4() Public m1() Class D D can have access: Public Class C C can have access: Public Protected(b/c inherits A) Diff between protected and default Protected is seen by class that have inheritance relation Package X Package Y
44. 44. HOW OOD CONTRIBUTE TO SE We can reuse an existing and extends it We can change implementation of the behaviors of the existing class by overriding its method.
45. 45. CS152 PROGRAM PARADIGM 3/17/2015 San Jose State University Computer Science Kaya Ota 4/14/2015
46. 46. INLINE CODE If a method is called frequently, then java (and also C++) compiler may replace the method call by the actual code of the method. Inline code: the code for the function body that is inserted directly at the point where the function would be called. 4/14/2015
47. 47. GOLDEN RULES OF PROGRAMMING When you program, you should pay attention them! 4/14/2015
48. 48. GENERAL GOLDEN RULES No magic constant Document clearly every thing before starting coding Choose meaningful name DRY (Do not repeat yourself) Efficiency is not current the top of priority => maintainability is more important Not be more then 20+-5 statements Atomic method: a method must do just one responsibility IN Detail. 4/14/2015
49. 49. ATOMIC METHOD Method1() { } Connect to DB Retrieve-the data Package Data One method do more then one in detail. 4/14/2015
50. 50. ATOMIC METHOD Method1() { Call Functions } Connect to DB() Retrieve-the data() Package Data() Functionality splied in to methods This is better to debug 4/14/2015
51. 51. DEMETER LAW A method M of an Object O may only use the following members: Instance variable of O Ms formal parameters Any object created /instantiated within M Method1( type param1, type param2.) { new O1 ; O1.method#(int x, int y); O1.data } 4/14/2015
52. 52. GOLDEN RULE FOR CLASS DESIGN A class does not have more then one higher-level responsibility! Encapsulate related data and behavior in one and only one place Give the minimum access Minimize the dependency between the classes! Loose Coupling. if class A knows whatever B exposed via its interface, then they re loosely-coupled, otherwise, they are tightly- coupled. High Cohesion put everything related in one class Bound of class should be crystal clear 4/14/2015
53. 53. LOGIC PROGRAMMING Logical programming with Prolog 4/14/2015
54. 54. HISTORY OF LOGIC Logic is the science of reasoning and proof, has existed since ancient Greek philosopher. ARISTOTLE is famous Math is a language of Science. And logic is a language of math. 4/14/2015
55. 55. REVIEW OF PROPOSITIONAL LOGIC Proposition Propositions are the basic building blocks of logic Definition A proposition is declarative sentence that is either true or false Propositional Calculus The area of logic that deals with propositions is called propositional calculus 4/14/2015
56. 56. Logical Operation P Q P and Q P or Q If P then Q P xor Q P iff Q T T T T T F T T F F T F T F F T F T T T F F F F F T F T 4/14/2015
57. 57. LOGICAL OPERATION In implication (conditional statement) p q, p is called the hypothesis (or premise) and q is called conclusion. 4/14/2015
58. 58. LOGICAL QUIZ Let P be I have access to CS network Let Q be I am CS major If P then Q = PQ if I have access to Cs network, then I am CS major If Q then P = PQ if I am CS major, then I have access to CS network To be bidirectional(if and only if), Both directions ( and ) have to be true. I have access to CS network only if I am CS major (PQ ) This sentence is direction with PQ b/c Q is in if-sentence 4/14/2015
59. 59. LOGICAL QUIZ If Q then P means Q is sufficient condition, and P is necessary condition P only if Q means Q is necessary condition and P is sufficient condition Arrow Always indicates the direction Sufficient condition Necessary condition 4/14/2015
60. 60. CS152 PROGRAM PARADIGM 3/19/2015 San Jose State University Computer Science Kaya Ota 4/14/2015
61. 61. REVIEW OF PROPOSITIONAL LOGIC PQ == not Q not P BUT, PQ != QP and not P not Q Tautology: A compound proposition that is always true, not matter what the truth value of the propositional variable that occur in it, is tautology. 4/14/2015
62. 62. IMPORTANT DEFINITION Tautology: A compound proposition that is always true, not matter what the truth value of the propositional variable that occur in it, is tautology. Contradiction: A compound proposition that is always false ,no matter what the truth value of the propositional variable that occur in it, is contradiction. Contingent: A compound proposition that is neither a tautology nor a contradiction is called a contingency 4/14/2015
63. 63. LOGICAL EQUIVALENCE Identify: P and T = P Domination : P and F = F Idempotent : P and P = P Double Neg: Not(Not P) = P Commutative: P and Q = Q and P Negation: P and not P = F Absorption: P and (P or Q) = P Associative: (P and Q) and R = P and (Q and R) Distributive: P and (Q or R) = (P and Q) or (P and R) 4/14/2015
64. 64. LOGICAL EQUIVALENCES De Morgan Not(P and Q) = Not P or Not Q P implies Q = not P or Q P implied Q = not Q implied not P P if and only if Q = (P implies Q ) and (Q implies P) P if and only if Q = not P if and only if not Q P implies (Q implies R) = (P and Q) implies R (P or Q) implies R = (Q implies R) and (Q implies R) 4/14/2015
65. 65. INTUITIVE UNDERSTAND P implies Q == Not Q implies Not P 4/14/2015 P = not Q Q = not P not Q Not P IDENTICAL If an element in not in Q, Then the element is not in P too
66. 66. DUALITY RULE Dual of a logical equivalence that only contains not, and or, T, F, can be constructed by the following exchanges P and not Q = F P or not P = T And or Or and T F F T The constructed formula is also a valid logical equivalence. Duel of S, noted S* 4/14/2015
67. 67. SATISFIABILITY Definition A compound proposition is Satisfiable if there is at least an assignment of truth value to its variables that makes it true. If the proposition is false for all assignments, then it is called unsatisfiable Each assignment that makes it satisfiable is called a solution 4/14/2015
68. 68. FUNCTIONAL COMPLETE Definition A set of logical operators is called functionally complete if every compound proposition can be re-written using the operators of this set. Note: we already know that every compound proposition can be written by (not, and, or) set TRY: show that the set of logical operators (not, and) are functionally complete. 4/14/2015
69. 69. CS152 PROGRAM PARADIGM 4/2/2015 San Jose State University Computer Science Department Kaya Ota 4/14/2015
70. 70. REVIEW OF PROPOSITIONAL LOGIC 4/14/2015 If (x > 5) { if(y > 10) { // r = do something } } P (q r) = Not p or (not q or r) = (not p or not q) or r = Not(p and q) or r = (p and q) r If (x > 5 and y > 10) { // r = do something } o u t Example 1
71. 71. REVIEW OF PROPOSITIONAL LOGIC 4/14/2015 If (x > 5 || !(y > 10 || x 5 ) { // r = do something } o u t Example 2
72. 72. PREDICATE CALCULUS Quantifiers Using quantifiers is another way to convert a propositional function to proposition. Universal Quantifier The notation denotes the universal quantification of P(x). Here is called the universal quantifier. For all x we mean for all elements of a specified set of values that is called domain discourse or just as domain If all p(xi) for i = 1,2,3,,n are true, then P(x) is true. 4/14/2015
73. 73. Existential Quantifier There exists x in the domain, P(x) = P(x1) P(x2) P(xn) What if the domain is an empty set ? False! There does not exists such x. 4/14/2015
74. 74. RULE OF INFERENCE 4/14/2015 P1 P2 P3 ---------------------- - So, q Premises or hypothesis Conclusion Prove is to shows (P1P2 P3 Pn) q Tautology
75. 75. PROOF OF RESOLUTION IN Construction 4/14/2015
76. 76. QUERY WITH PROLOG Query: A query is a question that we ask from prolog KB 4/14/2015 Woman(sally) Man(jack) .. ?- Woman(mia) // is mia woman? ?-Man(jack) // is jack man? ?- Woman(mia),Man(jack) // is mia woman and is jack man? QueriesKnowledge Based ASK Tell All 3 questions are fail b/c info is not in KB.
77. 77. QUERY WITH PROLOG 4/14/2015 *Woman(Sally) Man(jack) **Woman(Mia) Sally .. ?- Woman(x) // is there woman x? Sally ; //i.e. any other solution? Mia QueriesKnowledge Based ASK for woman x TELL (Sally is woman) ASK for other solution TELL (Mia is woman)
78. 78. QUERY WITH PROLOG 4/14/2015 Woman(A) *Woman(Mia) Woman(B) Loves(B, Mia) Loves(pumpkin, honey) *Loves(Marcellus, Mia) . ?- Loves(Marcellus, x ), Woman(x) // is there Marcellus loves x and woman x? x = Mia //instantiate Result True! QueriesKnowledge Based ASK for Loves(Marcellus, X) TELL Loves(Marcellus, mia) ASK for Woman(Mia) TELL (Mia is woman)
79. 79. UNIFICATION Unification is a process of matching two terms. 4/14/2015
80. 80. SEARCH TREE Will add later. 4/14/2015