Week 1
http://composingprograms.com/pages/11-getting-started.html
1.1 Getting Started
Chapter 1: Building Abstractions with Functions 1.1 Getting Started Computer science is a tremendously broad academic discipline. The areas of globally distributed systems, artificial intelligence, robotics, graphics, security, scientific computing, comp
composingprograms.com
http://composingprograms.com/pages/12-elements-of-programming.html
1.2 Elements of Programming
1.2 Elements of Programming A programming language is more than just a means for instructing a computer to perform tasks. The language also serves as a framework within which we organize our ideas about computational processes. Programs serve to communic
composingprograms.com
http://composingprograms.com/pages/13-defining-new-functions.html
1.3 Defining New Functions
1.3 Defining New Functions We have identified in Python some of the elements that must appear in any powerful programming language: Numbers and arithmetic operations are primitive built-in data values and functions. Nested function application provides a
composingprograms.com
http://composingprograms.com/pages/14-designing-functions.html
1.4 Designing Functions
1.4 Designing Functions Functions are an essential ingredient of all programs, large and small, and serve as our primary medium to express computational processes in a programming language. So far, we have discussed the formal properties of functions and
composingprograms.com
http://composingprograms.com/pages/15-control.html
1.5 Control
1.5 Control The expressive power of the functions that we can define at this point is very limited, because we have not introduced a way to make comparisons and to perform different operations depending on the result of a comparison. Control statements w
composingprograms.com
Week 2
http://composingprograms.com/pages/16-higher-order-functions.html
1.6 Higher-Order Functions
1.6 Higher-Order Functions We have seen that functions are a method of abstraction that describe compound operations independent of the particular values of their arguments. That is, in square, >>> def square(x): return x * x we are not talking about
composingprograms.com
http://composingprograms.com/pages/17-recursive-functions.html
1.7 Recursive Functions
1.7 Recursive Functions A function is called recursive if the body of the function calls the function itself, either directly or indirectly. That is, the process of executing the body of a recursive function may in turn require applying that function aga
composingprograms.com
Week 3
http://composingprograms.com/pages/21-introduction.html
2.1 Introduction
Chapter 2: Building Abstractions with Data 2.1 Introduction We concentrated in Chapter 1 on computational processes and on the role of functions in program design. We saw how to use primitive data (numbers) and primitive operations (arithmetic), how to f
composingprograms.com
http://composingprograms.com/pages/22-data-abstraction.html
2.2 Data Abstraction
2.2 Data Abstraction As we consider the wide set of things in the world that we would like to represent in our programs, we find that most of them have compound structure. For example, a geographic position has latitude and longitude coordinates. To repr
composingprograms.com
http://composingprograms.com/pages/23-sequences.html
2.3 Sequences
2.3 Sequences A sequence is an ordered collection of values. The sequence is a powerful, fundamental abstraction in computer science. Sequences are not instances of a particular built-in type or abstract data representation, but instead a collection of b
composingprograms.com
http://composingprograms.com/pages/24-mutable-data.html
2.4 Mutable Data
2.4 Mutable Data We have seen how abstraction is vital in helping us to cope with the complexity of large systems. Effective programming also requires organizational principles that can guide us in formulating the overall design of a program. In particul
composingprograms.com
Week 4
http://composingprograms.com/pages/28-efficiency.html
2.8 Efficiency
2.8 Efficiency Decisions of how to represent and process data are often influenced by the efficiency of alternatives. Efficiency refers to the computational resources used by a representation or process, such as how much time and memory are required to c
composingprograms.com
http://composingprograms.com/pages/42-implicit-sequences.html
4.2 Implicit Sequences
4.2 Implicit Sequences A sequence can be represented without each element being stored explicitly in the memory of the computer. That is, we can construct an object that provides access to all of the elements of some sequential dataset without computing
composingprograms.com
'University of California, Berkeley > ElectricalEngineering & ComputerSciences' μΉ΄ν κ³ λ¦¬μ λ€λ₯Έ κΈ
| Recursion Examples (0) | 2019.07.04 |
|---|---|
| textbook _ final (0) | 2019.07.03 |
| Recursion (0) | 2019.07.03 |
| LAB_day 2 (0) | 2019.07.02 |
| Higher-Order Functions (0) | 2019.07.02 |