Abstraction IS 101 YCMSC 101 Computational Thinking and

Abstraction IS 101 Y/CMSC 101 Computational Thinking and Design Tuesday, September 17, 2013 Carolyn Seaman University of Maryland, Baltimore County

Freebie Quiz No right answers, everyone gets 100% (but you have to turn it in to get credit) Please be HONEST!!! We want to know how the class is going for you No time limit Individual only

Processing Assignment #2 Download from the online schedule Read it through right away, so you can start thinking about it Understand the basics first – make sure you’ve successfully completed the code tracing exercises and tutorials from last week, and today’s exercises Use the steps in the assignment – read the directions carefully and follow them! Start early – the TFs took 10 -12 hours to complete this assignment Ask for help

Big Idea: Abstraction is the process of generalizing away from the details of a problem to simplify and focus on its key aspects We use abstraction for problem solving, design, organization, and simplification Examples from everyday life: Smart thermostats Steering wheels Email folders and labels Schedules and calendars Language!!

Abstraction in Computing Abstraction is ubiquitous in all computing disciplines “It’s All Just Bits” The interpretation (meaning) of data depends on how it is used The same bit sequence can represent an integer, a decimal number, a sequence of characters, or anything else you might decide it means Layers of computing hardware, including gates, chips, and components Programming languages are abstractions of machine language Functional decomposition == layers of abstraction Models and simulations: abstractions of real-world phenomena We can study, analyze, and experiment with models more easily than experimenting on the real world

Programming Enables Problem Solving, Expression, and Knowledge Creation Programs are written to execute algorithms Requires an understanding of how instructions are processed Programs are executed to automate processes A single program can be run multiple times, on many machines Executable programs increase the scale of solvable problems Programming is facilitated by appropriate abstractions Functions are re-usable programming abstractions Parameterization can be used to generalize a specific solution Data abstraction can separate behavior from implementation APIs and libraries simplify complex programming tasks Programs are developed and used by people Developing programs is an iterative process Finding and eliminating errors is part of the process Documentation is needed for maintainable programs

Big Idea: Design Problem solving often produces multiple possible solutions Or multiple ways to implement the solution Design is the process of making those decisions and choices Design at a high level Is it cost-effective to automate kidney exchange? Should we use a relational or object-oriented database? Design at a low level How do I structure this function? What do I call this variable?

Design Process for Programs First, understand the problem clearly Second, write the solution in English Test its correctness by manually applying it to some simple – and then more complex -- examples Optionally, “translate” the solution into pseudocode Advanced programmers will use this step as an abstraction to avoid the syntactic details of a particular programming language Next, translate the solution into a programming language Finally, implement (type) and test (carefully!) your solution

Example: Counting Print the numbers from one to N N is a variable that can change each time the program is called For example, “print. Numbers (7)” should print: 1 2 3 4 5 6 7

Counting in English: Attempt #1 First attempt at English: Count from one to N Print out each number Not really an algorithm – just a restatement (what is the primitive action “count”? ? )

Counting in English: Attempt #2 Next attempt: Set the variable “current” to 1 Print the value of “current” Add one to “current” If “current” is greater than N, stop Otherwise, go back to “print” step Turns out that “go to” statements are bad design (for reasons we’ll talk about later) Let’s try it again, using something that looks more like a loop with a condition

Counting in English: Attempt #3 (almost right!) Set the variable “current” to 1 While “current” is less than N: Print the value of “current” Add one to “current” Test by hand: what if N = 3? Boundary cases: what if N = 0? N = -4? Possible error cases: what if N = 8. 73? what if N = “this isn’t a number”?

Counting in English: Processing Version void print. Number (int N) { int current = 1; while (current <= N) { println (current); current = current + 1; } }

Exercise #1: Multiplication Work in your team – OK to split into smaller groups of 2 or 3 when you’re at the implementation step How would you multiply two numbers, using only the addition operator? Understand the problem – state some examples Write the solution in English Test the English solution! Write the solution in Processing Test the program! Concepts: iterations, efficiency

Exercise #2: Guessing With your team, write Processing code to guess a number between 1 and 100 Remember the algorithmic design process: Understand the problem – work through some examples by hand! Write a solution in English and test it – then get a TF or instructor to OK your solution before moving on! Translate your solution into Processing Implement, test, and show a TF or instructor! Be prepared to explain why your approach is a good way to solve the problem