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# Lecture 1 Lab CS 61A

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This 24 page Class Notes was uploaded by Scott Lee on Sunday August 28, 2016. The Class Notes belongs to CS 61A at University of California Berkeley taught by John DeNero in Fall 2016. Since its upload, it has received 6 views. For similar materials see The Structure and Interpretation of Computer Programs in Elect Engr & Computer Science at University of California Berkeley.

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Date Created: 08/28/16

61A Lecture 1 Wednesday, August 24, 2016 Welcome to CS 61A! 2 I'm John DeNero Welcome to CS 61A! 2 I'm John DeNero Welcome to CS 61A! 2 I'm John DeNero Welcome to CS 61A! 2 I'm John DeNero Welcome to CS 61A! 2 How to contact John: denero@berkeley.edu I'm John DeNero Welcome to CS 61A! 2 How to contact John: denero@berkeley.edu piazza.com/berkeley/fall2016/cs61a I'm John DeNero Welcome to CS 61A! 2 How to contact John: denero@berkeley.edu piazza.com/berkeley/fall2016/cs61a John's ofﬁce hours: 781 Soda Monday & Wednesday 11am - 12pm By appointment: denero.org/meet I'm John DeNero The 61A Community 3 The 61A Community 3 45 undergraduate student instructors / teaching assistants (TAs): The 61A Community 3 45 undergraduate student instructors / teaching assistants (TAs): • Teach lab & discussion sections The 61A Community 3 45 undergraduate student instructors / teaching assistants (TAs): • Teach lab & discussion sections • Hold ofﬁce hours The 61A Community 3 45 undergraduate student instructors / teaching assistants (TAs): • Teach lab & discussion sections • Hold ofﬁce hours • Lots of other stuff: develop assignments, grade exams, etc. The 61A Community 3 45 undergraduate student instructors / teaching assistants (TAs): • Teach lab & discussion sections • Hold ofﬁce hours • Lots of other stuff: develop assignments, grade exams, etc. 45+ tutors & mentors: The 61A Community 3 45 undergraduate student instructors / teaching assistants (TAs): • Teach lab & discussion sections • Hold ofﬁce hours • Lots of other stuff: develop assignments, grade exams, etc. 45+ tutors & mentors: • Teach mentoring sections The 61A Community 3 45 undergraduate student instructors / teaching assistants (TAs): • Teach lab & discussion sections • Hold ofﬁce hours • Lots of other stuff: develop assignments, grade exams, etc. 45+ tutors & mentors: • Teach mentoring sections • Hold ofﬁce hours The 61A Community 3 45 undergraduate student instructors / teaching assistants (TAs): • Teach lab & discussion sections • Hold ofﬁce hours • Lots of other stuff: develop assignments, grade exams, etc. 45+ tutors & mentors: • Teach mentoring sections • Hold ofﬁce hours • Lots of other stuff: homework parties, mastery sections, etc. The 61A Community 3 45 undergraduate student instructors / teaching assistants (TAs): • Teach lab & discussion sections • Hold ofﬁce hours • Lots of other stuff: develop assignments, grade exams, etc. 45+ tutors & mentors: • Teach mentoring sections • Hold ofﬁce hours • Lots of other stuff: homework parties, mastery sections, etc. 200+ lab assistants help answer your individual questions The 61A Community 3 45 undergraduate student instructors / teaching assistants (TAs): • Teach lab & discussion sections • Hold ofﬁce hours • Lots of other stuff: develop assignments, grade exams, etc. 45+ tutors & mentors: • Teach mentoring sections • Hold ofﬁce hours • Lots of other stuff: homework parties, mastery sections, etc. 200+ lab assistants help answer your individual questions 1,500+ fellow students make CS 61A unique Parts of the Course 4 Parts of the Course Lecture: Videos posted to cs61a.org before each live lecture 4 Parts of the Course Lecture: Videos posted to cs61a.org before each live lecture Lab section: The most important part of this course (next week) 4 Parts of the Course Lecture: Videos posted to cs61a.org before each live lecture Lab section: The most important part of this course (next week) Discussion section: The most important part of this course (this week) 4 Parts of the Course Lecture: Videos posted to cs61a.org before each live lecture Lab section: The most important part of this course (next week) Discussion section: The most important part of this course (this week) Staff ofﬁce hours: The most important part of this course (next week) 4 Parts of the Course Lecture: Videos posted to cs61a.org before each live lecture Lab section: The most important part of this course (next week) Discussion section: The most important part of this course (this week) Staff ofﬁce hours: The most important part of this course (next week) Online textbook: http://composingprograms.com 4 Parts of the Course Lecture: Videos posted to cs61a.org before each live lecture Lab section: The most important part of this course (next week) Discussion section: The most important part of this course (this week) Staff ofﬁce hours: The most important part of this course (next week) Online textbook: http://composingprograms.com Weekly homework assignments, three exams, & four programming projects 4 Parts of the Course Lecture: Videos posted to cs61a.org before each live lecture Lab section: The most important part of this course (next week) Discussion section: The most important part of this course (this week) Staff ofﬁce hours: The most important part of this course (next week) Online textbook: http://composingprograms.com Weekly homework assignments, three exams, & four programming projects Lots of optional special events to help you complete all this work 4 An Introduction to Computer Science What is Computer Science? 6 What is Computer Science? 6 The study of What is Computer Science? 6 What problems can be solved using computation, The study of What is Computer Science? 6 What problems can be solved using computation, The study of How to solve those problems, and What is Computer Science? 6 What problems can be solved using computation, How to solve those problems, and What techniques lead to effective solutions The study of What is Computer Science? Systems 6 What problems can be solved using computation, How to solve those problems, and What techniques lead to effective solutions The study of What is Computer Science? Systems Artiﬁcial Intelligence 6 What problems can be solved using computation, How to solve those problems, and What techniques lead to effective solutions The study of What is Computer Science? Systems Artiﬁcial Intelligence Graphics 6 What problems can be solved using computation, How to solve those problems, and What techniques lead to effective solutions The study of What is Computer Science? Systems Artiﬁcial Intelligence Graphics Security 6 What problems can be solved using computation, How to solve those problems, and What techniques lead to effective solutions The study of What is Computer Science? Systems Artiﬁcial Intelligence Graphics Security Networking Programming Languages Theory Scientiﬁc Computing ... 6 What problems can be solved using computation, How to solve those problems, and What techniques lead to effective solutions The study of What is Computer Science? Systems Artiﬁcial Intelligence Graphics Security Networking Programming Languages Theory Scientiﬁc Computing ... 6 What problems can be solved using computation, How to solve those problems, and What techniques lead to effective solutions The study of What is Computer Science? Systems Artiﬁcial Intelligence Graphics Security Networking Programming Languages Theory Scientiﬁc Computing ... 6 Decision Making What problems can be solved using computation, How to solve those problems, and What techniques lead to effective solutions The study of What is Computer Science? Systems Artiﬁcial Intelligence Graphics Security Networking Programming Languages Theory Scientiﬁc Computing ... 6 Decision Making Robotics What problems can be solved using computation, How to solve those problems, and What techniques lead to effective solutions The study of What is Computer Science? Systems Artiﬁcial Intelligence Graphics Security Networking Programming Languages Theory Scientiﬁc Computing ... 6 Decision Making Robotics Natural Language Processing What problems can be solved using computation, How to solve those problems, and What techniques lead to effective solutions The study of What is Computer Science? Systems Artiﬁcial Intelligence Graphics Security Networking Programming Languages Theory Scientiﬁc Computing ... 6 Decision Making Robotics Natural Language Processing ... What problems can be solved using computation, How to solve those problems, and What techniques lead to effective solutions The study of What is Computer Science? Systems Artiﬁcial Intelligence Graphics Security Networking Programming Languages Theory Scientiﬁc Computing ... 6 Decision Making Robotics Natural Language Processing ... What problems can be solved using computation, How to solve those problems, and What techniques lead to effective solutions The study of What is Computer Science? Systems Artiﬁcial Intelligence Graphics Security Networking Programming Languages Theory Scientiﬁc Computing ... 6 Decision Making Robotics Natural Language Processing ... What problems can be solved using computation, How to solve those problems, and What techniques lead to effective solutions The study of Answering Questions What is Computer Science? Systems Artiﬁcial Intelligence Graphics Security Networking Programming Languages Theory Scientiﬁc Computing ... 6 Decision Making Robotics Natural Language Processing ... What problems can be solved using computation, How to solve those problems, and What techniques lead to effective solutions The study of Answering Questions Translation What is Computer Science? Systems Artiﬁcial Intelligence Graphics Security Networking Programming Languages Theory Scientiﬁc Computing ... 6 Decision Making Robotics Natural Language Processing ... What problems can be solved using computation, How to solve those problems, and What techniques lead to effective solutions The study of Answering Questions Translation ... What is This Course About? 7 What is This Course About? A course about managing complexity 7 What is This Course About? A course about managing complexity Mastering abstraction 7 What is This Course About? A course about managing complexity Mastering abstraction Programming paradigms 7 What is This Course About? A course about managing complexity Mastering abstraction Programming paradigms An introduction to programming 7 What is This Course About? A course about managing complexity Mastering abstraction Programming paradigms An introduction to programming Full understanding of Python fundamentals 7 What is This Course About? A course about managing complexity Mastering abstraction Programming paradigms An introduction to programming Full understanding of Python fundamentals Combining multiple ideas in large projects 7 What is This Course About? A course about managing complexity Mastering abstraction Programming paradigms An introduction to programming Full understanding of Python fundamentals Combining multiple ideas in large projects How computers interpret programming languages 7 What is This Course About? A course about managing complexity Mastering abstraction Programming paradigms An introduction to programming Full understanding of Python fundamentals Combining multiple ideas in large projects How computers interpret programming languages Different types of languages: Scheme & SQL 7 What is This Course About? A course about managing complexity Mastering abstraction Programming paradigms An introduction to programming Full understanding of Python fundamentals Combining multiple ideas in large projects How computers interpret programming languages Different types of languages: Scheme & SQL A challenging course that will demand a lot of you 7 Alternatives to CS 61A CS 10: The Beauty and Joy of Computing 9 CS 10: The Beauty and Joy of Computing 9 CS 10: The Beauty and Joy of Computing 9 CS 10: The Beauty and Joy of Computing Designed for students without prior experience 9 CS 10: The Beauty and Joy of Computing Designed for students without prior experience A programming environment created by Berkeley, now used in courses around the world and online 9 CS 10: The Beauty and Joy of Computing Designed for students without prior experience A programming environment created by Berkeley, now used in courses around the world and online 9 CS 10: The Beauty and Joy of Computing Designed for students without prior experience A programming environment created by Berkeley, now used in courses around the world and online 9 CS 10: The Beauty and Joy of Computing Designed for students without prior experience A programming environment created by Berkeley, now used in courses around the world and online An introduction to fundamentals (& Python) that sets students up for success in CS 61A 9 CS 10: The Beauty and Joy of Computing Designed for students without prior experience A programming environment created by Berkeley, now used in courses around the world and online An introduction to fundamentals (& Python) that sets students up for success in CS 61A Taught in Fall 2016 by Dan Garcia 9 CS 10: The Beauty and Joy of Computing Designed for students without prior experience A programming environment created by Berkeley, now used in courses around the world and online An introduction to fundamentals (& Python) that sets students up for success in CS 61A Taught in Fall 2016 by Dan Garcia More info: cs10.org 9 Data Science 8: Foundations of Data Science 10 Data Science 8: Foundations of Data Science Fundamentals of computing, statistical inference, & machine learning applied to real-world data sets 10 Data Science 8: Foundations of Data Science Fundamentals of computing, statistical inference, & machine learning applied to real-world data sets 10 Data Science 8: Foundations of Data Science Fundamentals of computing, statistical inference, & machine learning applied to real-world data sets Great programming practice for CS 61A 10 Data Science 8: Foundations of Data Science Fundamentals of computing, statistical inference, & machine learning applied to real-world data sets Great programming practice for CS 61A Cross-listed as CS C8, Stat C8, & Info C8 10 Data Science 8: Foundations of Data Science Fundamentals of computing, statistical inference, & machine learning applied to real-world data sets Great programming practice for CS 61A Cross-listed as CS C8, Stat C8, & Info C8 Taught in Fall 2016 by Ani Adhikari 10 Data Science 8: Foundations of Data Science Fundamentals of computing, statistical inference, & machine learning applied to real-world data sets Great programming practice for CS 61A Cross-listed as CS C8, Stat C8, & Info C8 Taught in Fall 2016 by Ani Adhikari More info: data8.org & databears.berkeley.edu 10 Course Policies Course Policies 12 Course Policies 12 Learning Course Policies 12 Learning Community Course Policies 12 Learning Course Staff Community Course Policies 12 Learning Course Staff Details... http://cs61a.org/articles/about.html Community Collaboration 13 Collaboration 13 Asking questions is highly encouraged Collaboration • Discuss everything with each other; learn from your fellow students! 13 Asking questions is highly encouraged Collaboration • Discuss everything with each other; learn from your fellow students! • Homework can be completed with a partner 13 Asking questions is highly encouraged Collaboration • Discuss everything with each other; learn from your fellow students! • Homework can be completed with a partner • Projects should be completed with a partner 13 Asking questions is highly encouraged Collaboration • Discuss everything with each other; learn from your fellow students! • Homework can be completed with a partner • Projects should be completed with a partner • Choose a partner from your discussion section 13 Asking questions is highly encouraged Collaboration • Discuss everything with each other; learn from your fellow students! • Homework can be completed with a partner • Projects should be completed with a partner • Choose a partner from your discussion section 13 The limits of collaboration Asking questions is highly encouraged Collaboration • Discuss everything with each other; learn from your fellow students! • Homework can be completed with a partner • Projects should be completed with a partner • Choose a partner from your discussion section 13 • One simple rule: Don’t share your code, except with your partner The limits of collaboration Asking questions is highly encouraged Collaboration • Discuss everything with each other; learn from your fellow students! • Homework can be completed with a partner • Projects should be completed with a partner • Choose a partner from your discussion section 13 • One simple rule: Don’t share your code, except with your partner • Copying project solutions causes people to fail The limits of collaboration Asking questions is highly encouraged Collaboration • Discuss everything with each other; learn from your fellow students! • Homework can be completed with a partner • Projects should be completed with a partner • Choose a partner from your discussion section 13 • One simple rule: Don’t share your code, except with your partner • Copying project solutions causes people to fail • We really do catch people who violate the rules, because... The limits of collaboration Asking questions is highly encouraged Collaboration • Discuss everything with each other; learn from your fellow students! • Homework can be completed with a partner • Projects should be completed with a partner • Choose a partner from your discussion section 13 • One simple rule: Don’t share your code, except with your partner • Copying project solutions causes people to fail • We really do catch people who violate the rules, because... • We also know how to search the web for solutions The limits of collaboration Asking questions is highly encouraged Collaboration • Discuss everything with each other; learn from your fellow students! • Homework can be completed with a partner • Projects should be completed with a partner • Choose a partner from your discussion section 13 • One simple rule: Don’t share your code, except with your partner • Copying project solutions causes people to fail • We really do catch people who violate the rules, because... • We also know how to search the web for solutions • We use computers to check your work The limits of collaboration Asking questions is highly encouraged Collaboration • Discuss everything with each other; learn from your fellow students! • Homework can be completed with a partner • Projects should be completed with a partner • Choose a partner from your discussion section 13 • One simple rule: Don’t share your code, except with your partner • Copying project solutions causes people to fail • We really do catch people who violate the rules, because... • We also know how to search the web for solutions • We use computers to check your work The limits of collaboration Asking questions is highly encouraged Build good habits now Expressions Types of expressions 15 Types of expressions 15 An expression describes a computation and evaluates to a value 18 + 69 Types of expressions 15 An expression describes a computation and evaluates to a value 18 + 69 6 23 Types of expressions 15 An expression describes a computation and evaluates to a value 18 + 69 6 23 p 3493161 Types of expressions 15 An expression describes a computation and evaluates to a value 18 + 69 6 23 p 3493161 sin ⇡ Types of expressions 15 An expression describes a computation and evaluates to a value 18 + 69 6 23 p 3493161 sin ⇡ | ! 1869| Types of expressions 15 An expression describes a computation and evaluates to a value 18 + 69 6 23 p 3493161 sin ⇡ X 100 i=1 i | ! 1869| Types of expressions 15 An expression describes a computation and evaluates to a value 18 + 69 6 23 p 3493161 sin ⇡ X 100 i=1 i | ! 1869| ✓69 18◆ Types of expressions 15 An expression describes a computation and evaluates to a value 18 + 69 6 23 p 3493161 sin ⇡ f(x) X 100 i=1 i | ! 1869| ✓69 18◆ Types of expressions 15 An expression describes a computation and evaluates to a value 18 + 69 6 23 p 3493161 sin ⇡ f(x) X 100 i=1 i | ! 1869| ✓69 18◆ 2100 Types of expressions 15 An expression describes a computation and evaluates to a value 18 + 69 6 23 p 3493161 sin ⇡ f(x) X 100 i=1 i | ! 1869| ✓69 18◆ 2100 log2 1024 Types of expressions 15 An expression describes a computation and evaluates to a value 18 + 69 6 23 p 3493161 sin ⇡ f(x) X 100 i=1 i | ! 1869| ✓69 18◆ 2100 log2 1024 7 mod 2 Types of expressions 15 An expression describes a computation and evaluates to a value 18 + 69 6 23 p 3493161 sin ⇡ f(x) X 100 i=1 i | ! 1869| ✓69 18◆ 2100 log2 1024 7 mod 2 lim x!1 1 x Types of expressions 15 An expression describes a computation and evaluates to a value 18 + 69 6 23 p 3493161 sin ⇡ f(x) X 100 i=1 i | ! 1869| ✓69 18◆ 2100 log2 1024 7 mod 2 lim x!1 1 x Types of expressions 15 An expression describes a computation and evaluates to a value Call Expressions in Python All expressions can use function call notation (Demo) 16 Anatomy of a Call Expression 17 Anatomy of a Call Expression 17 add ( 2 , 3 ) Anatomy of a Call Expression 17 add ( 2 , 3 ) Anatomy of a Call Expression 17 add ( 2 , 3 ) Operator Anatomy of a Call Expression 17 add ( 2 , 3 ) Operator Operand Operand Anatomy of a Call Expression 17 add ( 2 , 3 ) Operator Operand Operand Operators and operands are also expressions Anatomy of a Call Expression 17 add ( 2 , 3 ) Operator Operand Operand Operators and operands are also expressions So they evaluate to values Anatomy of a Call Expression 17 Evaluation procedure for call expressions: add ( 2 , 3 ) Operator Operand Operand Operators and operands are also expressions So they evaluate to values Anatomy of a Call Expression 17 Evaluation procedure for call expressions: add ( 2 , 3 ) Operator Operand Operand Operators and operands are also expressions 1. Evaluate the operator and then the operand subexpressions So they evaluate to values Anatomy of a Call Expression 17 Evaluation procedure for call expressions: add ( 2 , 3 ) Operator Operand Operand Operators and operands are also expressions 1. Evaluate the operator and then the operand subexpressions 2. Apply the function that is the value of the operator subexpression to the arguments that are the values of the operand subexpression So they evaluate to values mul(add(4, mul(4, 6)), add(3, 5)) Evaluating Nested Expressions 18 mul(add(4, mul(4, 6)), add(3, 5)) Evaluating Nested Expressions 18 mul(add(4, mul(4, 6)), add(3, 5)) Evaluating Nested Expressions 18 mul mul(add(4, mul(4, 6)), add(3, 5)) add(4, mul(4, 6)) Evaluating Nested Expressions 18 mul mul(add(4, mul(4, 6)), add(3, 5)) add(4, mul(4, 6)) Evaluating Nested Expressions 18 mul add mul(add(4, mul(4, 6)), add(3, 5)) add(4, mul(4, 6)) Evaluating Nested Expressions 18 mul add 4 mul(add(4, mul(4, 6)), add(3, 5)) add(4, mul(4, 6)) Evaluating Nested Expressions 18 mul add 4 mul(4, 6) mul(add(4, mul(4, 6)), add(3, 5)) add(4, mul(4, 6)) Evaluating Nested Expressions 18 mul add 4 mul(4, 6) mul 4 6 mul(add(4, mul(4, 6)), add(3, 5)) add(4, mul(4, 6)) Evaluating Nested Expressions 18 mul add 4 mul(4, 6) mul 4 6 mul(add(4, mul(4, 6)), add(3, 5)) add(4, mul(4, 6)) Evaluating Nested Expressions 18 mul add 4 mul(4, 6) mul 4 6 24 mul(add(4, mul(4, 6)), add(3, 5)) add(4, mul(4, 6)) Evaluating Nested Expressions 18 mul add 4 mul(4, 6) mul 4 6 24 mul(add(4, mul(4, 6)), add(3, 5)) add(4, mul(4, 6)) Evaluating Nested Expressions 18 mul 28 add 4 mul(4, 6) mul 4 6 24 mul(add(4, mul(4, 6)), add(3, 5)) add(4, mul(4, 6)) Evaluating Nested Expressions 18 mul 28 add 4 mul(4, 6) mul 4 6 24 add(3, 5) mul(add(4, mul(4, 6)), add(3, 5)) add(4, mul(4, 6)) Evaluating Nested Expressions 18 mul 28 add 4 mul(4, 6) mul 4 6 24 add(3, 5) add 3 5 mul(add(4, mul(4, 6)), add(3, 5)) add(4, mul(4, 6)) Evaluating Nested Expressions 18 mul 28 add 4 mul(4, 6) mul 4 6 24 add(3, 5) add 3 5 mul(add(4, mul(4, 6)), add(3, 5)) add(4, mul(4, 6)) Evaluating Nested Expressions 18 mul 28 add 4 mul(4, 6) mul 4 6 24 add(3, 5) add 3 5 8 mul(add(4, mul(4, 6)), add(3, 5)) add(4, mul(4, 6)) Evaluating Nested Expressions 18 mul 28 add 4 mul(4, 6) mul 4 6 24 add(3, 5) add 3 5 8 224 mul(add(4, mul(4, 6)), add(3, 5)) add(4, mul(4, 6)) Evaluating Nested Expressions 18 mul 28 add 4 mul(4, 6) mul 4 6 24 add(3, 5) add 3 5 8 224 mul(add(4, mul(4, 6)), add(3, 5)) add(4, mul(4, 6)) mul 28 add 4 mul(4, 6) mul 4 6 24 add(3, 5) add 3 5 8 Evaluating Nested Expressions 19 224 mul(add(4, mul(4, 6)), add(3, 5)) add(4, mul(4, 6)) mul 28 add 4 mul(4, 6) mul 4 6 24 add(3, 5) add 3 5 8 Evaluating Nested Expressions 19 Expression tree 224 mul(add(4, mul(4, 6)), add(3, 5)) add(4, mul(4, 6)) mul 28 add 4 mul(4, 6) mul 4 6 24 add(3, 5) add 3 5 8 Evaluating Nested Expressions 19 Expression tree Operand subexpression 224 mul(add(4, mul(4, 6)), add(3, 5)) add(4, mul(4, 6)) mul 28 add 4 mul(4, 6) mul 4 6 24 add(3, 5) add 3 5 8 Evaluating Nested Expressions 19 Expression tree Operand subexpression Value of subexpression 224 mul(add(4, mul(4, 6)), add(3, 5)) add(4, mul(4, 6)) mul 28 add 4 mul(4, 6) mul 4 6 24 add(3, 5) add 3 5 8 Evaluating Nested Expressions 19 Expression tree Operand subexpression Value of subexpression 1st argument to mul 224 mul(add(4, mul(4, 6)), add(3, 5)) add(4, mul(4, 6)) mul 28 add 4 mul(4, 6) mul 4 6 24 add(3, 5) add 3 5 8 Evaluating Nested Expressions 19 Expression tree Operand subexpression 1st argument to mul Value of the whole expression Value of subexpression Functions, Objects, and Interpreters (Demo)

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