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Programming Abstractions
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Programming Abstractions

Author: Julie Zelenski

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This course is the natural successor to Programming Methodology and covers such advanced programming topics as recursion, algorithmic analysis, and data abstraction using the C++ programming language, which is similar to both C and Java. If you've taken the Computer Science AP exam and done well (scored 4 or 5) or earned a good grade in a college course, Programming Abstractions may be an appropriate course for you to start with, but often Programming Abstractions (Accelerated) is a better choice. Programming Abstractions assumes that you already have familiarity with good programming style and software engineering issues (at the level of Programming Methodology), and that you can use this understanding as a foundation on which to tackle new topics in programming and data abstraction.

Topics: Abstraction and its relation to programming. Software engineering principles of data abstraction and modularity. Object-oriented programming, fundamental data structures (such as stacks, queues, sets) and data-directed design. Recursion and recursive data structures (linked lists, trees, graphs). Introduction to time and space complexity analysis. Uses the programming language C++ covering its basic facilities.
27 Episodes
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Julie goes over recursion and the proper ways to solve problems recursively. She continues with the example of a program that draws a fractal image and explains a Mandarin code to illustrate the different possibilities of drawing different pictures.
Julie explains procedural recursion and introduces permute code. She goes through another example of recursive code line by line, explaining each component. Recursive backtracking and it's usefulness are discussed.
Julie continues with recursive backtracking and introduces pointers and recursive data. Following, she focuses on solving the problems rather than the exact code and later uses the example of a program that will solve a Sudoku puzzle.
Julie continues to go over pointers and moves on to recursive data and linked lists. She explains the basics of pointers with two variables pointing to the same address.
Julie introduces linked lists and continues to discuss recursive data. She goes line by line through an example code she writes during the lecture. She then inserts variables in an order; she uses the example of an address book to explain this.
Julie starts off with algorithm analysis, the big-O notation and introduces sorting. She begins off with a brief overview of what algorithm analysis is and how to utilize it. Later, she continues to go through recursive algorithms and their uses.
Julie continues to cover sorting. She begins with an example of a selection sorting code and a graphic demo of the code in progress. Thereafter, she explains the different methods available to sort different kinds of data.
Julie continues with sorting, specifically quadratic and linearithmic sorting methods, and then explains how to reasonably partition data sets for quicksort. Thereafter, she proceeds to go over different functional templates for sorting algorithms.
Julie continues to go over sort templates and callback functions, then shows a final version of the sort template, one that will be extremely useful in the next homework assignment.
Julie introduces the 'implement vector' and discusses ADTs (abstract data types) in more detail. She then develops a Vector from the ground up, explaining each step as she goes.
Julie reiterates the rules for template implementers and continues by coding live with the class explaining each line of code in detail after writing it. Throughout the process of writing the code, she encounters several errors and has to debug it.
Julie continues discussing Vector and moves on to stack and queue, covering chapter ten in the course textbook. She goes over several rules for templates again to reinforce how important they are.
Julie talks about the buffer version of vector vs. stack and follows this with an example of cursor design. She also talks about linked list insertion and deletion. Cursor movement is the next topic covered.
Julie discusses map as a vector and describes a different, possibly better, strategy. The basics of trees and their usefulness and how they can be used with binary search is then introduced.
Julie shows a YouTube video of Barack Obama answering a question about what kind of sorting algorithm he would use to sort a list of data. She also gives several examples of problems that are capable of being solved with sorting.
Julie introduces hashing and it's uses in search and retrieval; map implementations and the different kinds of search algorithms are then discussed. Thereafter she explains that logarithmic searches are relatively fast and often finish the search.
Julie examines a case study and opening up the lexicon file, which is complicated; she walks the students through the code and explains why she wrote it as she did as opposed to a sorted vector or binary search tree.
Julie ties up the "loose ends" of the course: after a general review of the concepts covered in the course, she asks which of two examples is the better. She then covers manipulation of dynamic data structures (lists, trees, graphs).
In the final lecture, Keith talks about the C++ programming language. He starts of with C++ history, C++ without CS 106 and what comes next.
Julie Zelenski gives an introduction to the course, recursion, algorithms, dynamic data structures and data abstraction; she also introduced the significance of programming and gives her opinion of what makes 106B "great;" C++ is introduced, too.
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