Separation of Concerns

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来自 Duke University 的课程

Java 程序设计：使用软件解题

1835 个评分

Duke University

Java 程序设计：使用软件解题

1835 个评分

课程 1（共 4 门，Specialization Object Oriented Programming in Java）

Building upon Duke’s “Programming and the Web for Beginners” course, you will grow in your ability to be a problem-solver and programmer by writing Java programs. We are excited that you've chosen to learn Java with us! You will soon be able to solve problems that you find interesting and useful by practicing a design process you will learn in this course. Java concepts presented in this course include basic control flow; object-oriented concepts including classes and methods; custom, open-source classes; and a design-implement-debug process that you can continue to leverage as you build your experience and knowledge of programming principles. The custom, open-source classes will provide a consistent application programming interface (API) so that you can write programs that access and transform images, websites, comma separated value (CSV) files and other data files using simple and accessible coding idioms built on the Java Iterable interface. You will learn to design, test, and debug programs and to find and read Java documentation that can serve as the basis for continued study of Java and programming. After completing this course you will be able to: 1. Edit, compile, and run a Java program; 2. Use conditionals and for loops appropriately in a Java program; 3. Use Java API documentation in writing programs. 4. Debug a Java program using the scientific method; 5. Develop a Java method to solve a specific problem; 6. Develop a set of test cases as part of developing a program; 7. Create a class with multiple methods that work together to solve a problem; and 8. Use divide-and-conquer design techniques for a program that uses more than one method.

从本节课中

Strings in Java

This module begins with a short presentation from Raluca Gordân, an assistant professor in Duke University’s Center for Genomic and Computational Biology, about an important problem genomics scientists encounter regularly: how to identify genes in a strand of DNA. To tackle this problem, you will need to understand strings: series of characters such as letters, digits, punctuation, etc. After learning about Java methods that work with strings, you will be able to find genes within a DNA string as well as tackle other string related problems, such as finding all of the links in a web page. By the end of this module, you will be able to: (1) Use important methods for the Java String class; (2) Use conditionals, for loops, and while loops appropriately in a Java program; (3) Find patterns in the data represented by strings to help develop the algorithm for your program; (4) Understand the importance of designing programs that keep different data processing steps separate; (5) Use the StorageResource iterable for this course to store some data for further processing; and (6) Rely on Java documentation to better understand how to use different Java packages and classes.

Separation of Concerns5:07

StorageResource Class3:54

Coding StorageResource Class4:27

与讲师见面

Owen Astrachan
Professor of the Practice
Computer Science
Robert Duvall
Lecturer
Computer Science
Andrew D. Hilton
Assistant Professor of the Practice
Electrical and Computer Engineering
Susan H. Rodger
Professor of the Practice
Computer Science

Now, you can iterate over all the genes in the DNA string and print them out.

If you wanted to iterate over the genes in the DNA string and

do something else to them, the algorithm would be pretty similar.

In fact, for whatever you want to do with each gene,

it would look pretty much like this.

The line in blue is the only thing you would change to do whatever you might

want to.

Maybe printing only those genes that meet some condition, counting genes.

Saving them to a file.

Building a web page with all of them or anything else you can think of.

So if you wanted to do these other things,

you might copy the algorithm you have pasted.

Paste it into a new method and edit that line to make small changes.

This approach works, but it's generally a bad idea.

Why?

Well, for one thing, copy and paste is error prone.

You might forget to change some things that you need to.

Even worse, if you find a bug in your original implementation after

you have made copies, you need to go fix every copy you made.

It is also tedious.

You have to go find the method, copy and paste it and change it.

This may not be so bad, if you want one variation.

But if you want to do five different things, then it's pretty boring.

And finally, it indicates bad programming design choices.

Whenever you find yourself wanting to copy and

paste, there's almost always a better approach.

Let's take a moment to see something that we could improve about this algorithm.

Why it would make a lot of work if we leave it as is and copy,

paste, change and then we'll understand the motivation for how to make to fix it.

This is our algorithm to print all the genes in a string.

We're going to condense it down to a small description at the bottom and

then copy and paste, it and change line five to print only the genes with

a high CG ratio, and then we'll condense that down to a short description.

Now we're going to copy, paste and edit to make several other algorithms to do

various things with the genes from our DNA string like printing genes in HTML.

Writing genes to an output file.

Counting genes with the codon CGA or whatever else you want to do.

All these algorithms are the same, except for

the details of what they do to the DNA string.

So at first, copy and pasting does not seem like a big deal.

Later, we end up with some other DNA data,

which list all the genes in a file, one gene per line.

We need to do the same sorts of operations on this data too or

the algorithm will be slightly different.

It will have a for

each line in the file loop, then do the same operation for the genes.

With our copy and paste approach, we now need to write and test six algorithms.

They're pretty similar to each other, so

it may not be so hard, but it's tedious error prone work.

Then if we end of with some other source of data,

we're going to have to go make all six algorithms again for that data source.

Likewise, if we end up with a new operation that we need to do.

We're going to have to write three copies of it, one for each data source.

Ick, what a mess.

What we would really like to do is redesign out algorithm to use

separation of concerns.

Our initial algorithm does two tasks.

One is getting all the genes from some source of data and

the other is printing them or whatever else we want to do to each of them.

We would like to split these up.

By having the algorithms that find the genes,

put them into some structure that can hold a list of all of the genes.

Then having the algorithms that print the genes, count the genes or

whatever else we want to do to the genes.

They should operate on that list.

Now if you need to add some new source of data,

you just write a way to get its genes into our list and

it automatically works with every processing algorithm you already wrote.

Likewise, if you need to write a new processing algorithm,

it automatically works with every source of data that you already wrote.

No copying and pasting is ever needed.

So, what is this thing that can hold all the genes your algorithms find?

We're going to start by using a class from the edu.duke package

called StorageResource, which is a simplified way of doing this.

Later on, once you have learned a few more concepts,

you will transition to using the standard Java.util.ArrayList class,

which has similar functionality, but it's a lot more complex.

Thank you.

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