Category Archives: #CS

Detailed and basic usage of Mockito

 Mockito is a Mock framework for Java single-testing, but it can also be used with other single-testing frameworks in addition to JUnit. Mockito changes the behavior of a class or object, allowing us to focus more on testing the code logic without the effort of constructing the data.

The basic concept

Mocks can be of two types, Class and Partial，so Mockito is called spy. The behavior of changing methods on mock objects is called Stub.

A Mock process is called a Mock Session, and it records all the Stubbing. It consists of three steps:

+———-+ +——+ +——–+
| Mock/Spy | ===> | Stub | ===> | Verify |
+———-+ +——+ +——–+

Class Mock

A Class Mock changes the behavior of a Class so that the object it mocks completely loses its original behavior.

Method returns default values (null, false, 0, etc.) if it is not pegged.

The most basic usage is as follows:

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import static org.mockito.Mockito.*;

// use List.class to creat a mock subject --- mockedList


List mockedList = mock(List.class);



//operation of mockedList


mockedList.add("one");
mockedList.clear();



//validation


verify(mockedList).add("one");
verify(mockedList).clear();

Partial Mock（spy）

If we only want to change the behavior of an instance, we need to use spy:

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List list = new LinkedList();
List spy = spy(list);

// optionally, you can stub out some methods:
when(spy.size()).thenReturn(100);

// using the spy calls *real* methods
spy.add("one");
spy.add("two");

// prints "one" - the first element of a list
System.out.println(spy.get(0));

// size() method was stubbed - 100 is printed
System.out.println(spy.size());

// optionally, you can verify
verify(spy).add("one");
verify(spy).add("two");

As you can see from the code, the main difference between a Spy and a MockSettings is that the MockSettings for a Spy needs to be passed in a SpiedInstance.

The default Answer to a spy is CALLS_REAL_METHODS, which means that if a method is not stub, it performs its real behavior.

The default Answer to a mock is RETURNS_DEFAULTS. Methods that are not stub return a default value.

source：

https://www.vogella.com/tutorials/Mockito/article.html

https://howtodoinjava.com/mockito/junit-mockito-example/

From the blog haorusong by Unknown and used with permission of the author. All other rights reserved by the author.

Use the Source

 When working on an open-source project, please get in the habit of downloading the latest version of the code (preferably from their source control system), so you can review its history and track future developments. Please take a look at the codebase structure and think about why it is organized the way it is. Look at how developers manage their code modules to see if it makes sense and compare them to how they might have used them. Try to refactor the code to understand why its coders made the decisions they did, and think about what the code would look like if you were the one coding it. It will give you a better understanding of the projects; Also, make sure you can build those projects. If you’ve found a better way to do something, you’re ready to contribute code to the project. Inevitably, as you go through the code, you’ll come across decisions you completely disagree with it. Ask yourself if the developers of the project might know something you don’t or vice versa. Consider whether this is a legacy design that needs to be refactored; consider whether making a toy implementation for the relevant feature would help clarify the issue.

You end up with a toolbox filled with all sorts of quirks that you’ve collected from other people’s code. This will hone your ability to solve minor problems more quickly and quickly. You’ll be able to tackle issues that others think are impossible to solve because they don’t have access to your toolbox. Take a look at the Git distributed source control system written by Linus Torvalds or any code written by Daniel J. Bernstein (known as DJB). Programmers like Linus and DJB occasionally use data structures and algorithms that most of us have never even heard of. They’re not magicians — they’ve just spent their time building bigger and better toolboxes than most people. The great thing about open source is that you can look at their toolbox and make their tools. One of the problems in software development is the lack of teachers. But thanks to the proliferation of open-source projects on sites such as SourceForge. Net and GitHub, you can learn from relatively representative code examples from the world’s programmer community.

In ODS, Bill Gates says: “The most subtle test of programming ability is giving the programmer about 30 pages of code and seeing how quickly he can read through it and understand it.” He realized something significant. People who quickly learn directly from the source code will soon become better programmers because their teachers are the lines of code written by every programmer in the world. The best way to learn patterns, idioms, and best practices is to read the open-source. Look at how other people to code. It’s a great way to stay relevant, and it’s free. — Chris Wanstrath at Ruby 2008 [

Pick an open-source project with deep algorithms, such as Subversion, Git, or Mercurial source control system. Browse through the project’s source code and jot down any algorithms, data structures, and design ideas that seem novel to you. Then write a blog post describing the project’s construction and highlighting the new ideas you’ve learned. Can you find a situation in your daily work where the same concept can be applied?

From the blog haorusong by and used with permission of the author. All other rights reserved by the author.

Use the Source

 When working on an open-source project, please get in the habit of downloading the latest version of the code (preferably from their source control system), so you can review its history and track future developments. Please take a look at the codebase structure and think about why it is organized the way it is. Look at how developers manage their code modules to see if it makes sense and compare them to how they might have used them. Try to refactor the code to understand why its coders made the decisions they did, and think about what the code would look like if you were the one coding it. It will give you a better understanding of the projects; Also, make sure you can build those projects. If you’ve found a better way to do something, you’re ready to contribute code to the project. Inevitably, as you go through the code, you’ll come across decisions you completely disagree with it. Ask yourself if the developers of the project might know something you don’t or vice versa. Consider whether this is a legacy design that needs to be refactored; consider whether making a toy implementation for the relevant feature would help clarify the issue.

You end up with a toolbox filled with all sorts of quirks that you’ve collected from other people’s code. This will hone your ability to solve minor problems more quickly and quickly. You’ll be able to tackle issues that others think are impossible to solve because they don’t have access to your toolbox. Take a look at the Git distributed source control system written by Linus Torvalds or any code written by Daniel J. Bernstein (known as DJB). Programmers like Linus and DJB occasionally use data structures and algorithms that most of us have never even heard of. They’re not magicians — they’ve just spent their time building bigger and better toolboxes than most people. The great thing about open source is that you can look at their toolbox and make their tools. One of the problems in software development is the lack of teachers. But thanks to the proliferation of open-source projects on sites such as SourceForge. Net and GitHub, you can learn from relatively representative code examples from the world’s programmer community.

In ODS, Bill Gates says: “The most subtle test of programming ability is giving the programmer about 30 pages of code and seeing how quickly he can read through it and understand it.” He realized something significant. People who quickly learn directly from the source code will soon become better programmers because their teachers are the lines of code written by every programmer in the world. The best way to learn patterns, idioms, and best practices is to read the open-source. Look at how other people to code. It’s a great way to stay relevant, and it’s free. — Chris Wanstrath at Ruby 2008 [

Pick an open-source project with deep algorithms, such as Subversion, Git, or Mercurial source control system. Browse through the project’s source code and jot down any algorithms, data structures, and design ideas that seem novel to you. Then write a blog post describing the project’s construction and highlighting the new ideas you’ve learned. Can you find a situation in your daily work where the same concept can be applied?

From the blog haorusong by Unknown and used with permission of the author. All other rights reserved by the author.

Use the Source

 When working on an open-source project, please get in the habit of downloading the latest version of the code (preferably from their source control system), so you can review its history and track future developments. Please take a look at the codebase structure and think about why it is organized the way it is. Look at how developers manage their code modules to see if it makes sense and compare them to how they might have used them. Try to refactor the code to understand why its coders made the decisions they did, and think about what the code would look like if you were the one coding it. It will give you a better understanding of the projects; Also, make sure you can build those projects. If you’ve found a better way to do something, you’re ready to contribute code to the project. Inevitably, as you go through the code, you’ll come across decisions you completely disagree with it. Ask yourself if the developers of the project might know something you don’t or vice versa. Consider whether this is a legacy design that needs to be refactored; consider whether making a toy implementation for the relevant feature would help clarify the issue.

You end up with a toolbox filled with all sorts of quirks that you’ve collected from other people’s code. This will hone your ability to solve minor problems more quickly and quickly. You’ll be able to tackle issues that others think are impossible to solve because they don’t have access to your toolbox. Take a look at the Git distributed source control system written by Linus Torvalds or any code written by Daniel J. Bernstein (known as DJB). Programmers like Linus and DJB occasionally use data structures and algorithms that most of us have never even heard of. They’re not magicians — they’ve just spent their time building bigger and better toolboxes than most people. The great thing about open source is that you can look at their toolbox and make their tools. One of the problems in software development is the lack of teachers. But thanks to the proliferation of open-source projects on sites such as SourceForge. Net and GitHub, you can learn from relatively representative code examples from the world’s programmer community.

In ODS, Bill Gates says: “The most subtle test of programming ability is giving the programmer about 30 pages of code and seeing how quickly he can read through it and understand it.” He realized something significant. People who quickly learn directly from the source code will soon become better programmers because their teachers are the lines of code written by every programmer in the world. The best way to learn patterns, idioms, and best practices is to read the open-source. Look at how other people to code. It’s a great way to stay relevant, and it’s free. — Chris Wanstrath at Ruby 2008 [

Pick an open-source project with deep algorithms, such as Subversion, Git, or Mercurial source control system. Browse through the project’s source code and jot down any algorithms, data structures, and design ideas that seem novel to you. Then write a blog post describing the project’s construction and highlighting the new ideas you’ve learned. Can you find a situation in your daily work where the same concept can be applied?

From the blog haorusong by Unknown and used with permission of the author. All other rights reserved by the author.

Breakable Toys

 We can all benefit from writing random “toy” programs to push ourselves to the limit by setting artificial limits. — Donald Knuth, The Art of Computer Programming

If you can learn as much from failure as you can from success, you need a relatively private space to look for the loss. In balling acrobatics, a performer who tosses three balls will never progress if he has never tossed five. Those who spend hours picking dropped balls until their back hurts eventually get good at it. The same lesson applies to software, where software workers often need to step out of their comfort zone to try something they’re not good at it. It is by taking bold chances again and again that you improve your skills, that you learn and grow from failure after failure. Just as a three-ball-tossing performer does not throw five balls in a formal performance, software developers often make mistakes in new areas. Software developers also need a safe place to make mistakes. It’s terrible not to have such a safe place to make mistakes. The fear and unwillingness of software developers to make mistakes make them stuck in a rut, unable to learn from failure, and thus makes the entire software development industry staid and stagnant.

Other examples of the “crunchy toy” pattern include games like Tetris and Tic-Tac-Toe. One senior I know has a habit of using every new language he learns to create a game, blog software, and IRC client. The nature of the problem is to build a toy that contains learning something new and provides an opportunity to let you in a special environment to deepen the understanding of hand tools. The environment is not only safe because you are the only or most influential users, and, even to the most powerful commercial products, you still have room to serve you as a user’s needs better.

You still have to remember that they’re just toys, and that’s why they’re supposed to be fun. If they’re not interesting, then when the initial excitement is over, they’ll just become a dusty relic, and you’ll be able to focus your energy on what you enjoy building.

From the blog haorusong by Unknown and used with permission of the author. All other rights reserved by the author.

Breakable Toys

 We can all benefit from writing random “toy” programs to push ourselves to the limit by setting artificial limits. — Donald Knuth, The Art of Computer Programming

If you can learn as much from failure as you can from success, you need a relatively private space to look for the loss. In balling acrobatics, a performer who tosses three balls will never progress if he has never tossed five. Those who spend hours picking dropped balls until their back hurts eventually get good at it. The same lesson applies to software, where software workers often need to step out of their comfort zone to try something they’re not good at it. It is by taking bold chances again and again that you improve your skills, that you learn and grow from failure after failure. Just as a three-ball-tossing performer does not throw five balls in a formal performance, software developers often make mistakes in new areas. Software developers also need a safe place to make mistakes. It’s terrible not to have such a safe place to make mistakes. The fear and unwillingness of software developers to make mistakes make them stuck in a rut, unable to learn from failure, and thus makes the entire software development industry staid and stagnant.

Other examples of the “crunchy toy” pattern include games like Tetris and Tic-Tac-Toe. One senior I know has a habit of using every new language he learns to create a game, blog software, and IRC client. The nature of the problem is to build a toy that contains learning something new and provides an opportunity to let you in a special environment to deepen the understanding of hand tools. The environment is not only safe because you are the only or most influential users, and, even to the most powerful commercial products, you still have room to serve you as a user’s needs better.

You still have to remember that they’re just toys, and that’s why they’re supposed to be fun. If they’re not interesting, then when the initial excitement is over, they’ll just become a dusty relic, and you’ll be able to focus your energy on what you enjoy building.

From the blog haorusong by Unknown and used with permission of the author. All other rights reserved by the author.

Breakable Toys

 We can all benefit from writing random “toy” programs to push ourselves to the limit by setting artificial limits. — Donald Knuth, The Art of Computer Programming

If you can learn as much from failure as you can from success, you need a relatively private space to look for the loss. In balling acrobatics, a performer who tosses three balls will never progress if he has never tossed five. Those who spend hours picking dropped balls until their back hurts eventually get good at it. The same lesson applies to software, where software workers often need to step out of their comfort zone to try something they’re not good at it. It is by taking bold chances again and again that you improve your skills, that you learn and grow from failure after failure. Just as a three-ball-tossing performer does not throw five balls in a formal performance, software developers often make mistakes in new areas. Software developers also need a safe place to make mistakes. It’s terrible not to have such a safe place to make mistakes. The fear and unwillingness of software developers to make mistakes make them stuck in a rut, unable to learn from failure, and thus makes the entire software development industry staid and stagnant.

Other examples of the “crunchy toy” pattern include games like Tetris and Tic-Tac-Toe. One senior I know has a habit of using every new language he learns to create a game, blog software, and IRC client. The nature of the problem is to build a toy that contains learning something new and provides an opportunity to let you in a special environment to deepen the understanding of hand tools. The environment is not only safe because you are the only or most influential users, and, even to the most powerful commercial products, you still have room to serve you as a user’s needs better.

You still have to remember that they’re just toys, and that’s why they’re supposed to be fun. If they’re not interesting, then when the initial excitement is over, they’ll just become a dusty relic, and you’ll be able to focus your energy on what you enjoy building.

From the blog haorusong by and used with permission of the author. All other rights reserved by the author.

DD path graphs

Structural testing is based on the source code of the program under test, rather than the definition. This is known as white box testing, while functional testing is known as black-box testing.

Program diagram: For a program written in an imperative programming language, the program diagram is a directed graph with nodes representing statement fragments and edges representing control flow.

DD – path

DD path: Decision-to-decision path (Miller). Begin with the “exit” of the decision statement and end with the “path” of the next decision statement.

DD chain: A path of starting and ending nodes at different points in a directed graph.

Consisting of a node, the internality =0;

Consisting of a node, externality =0;

Consisting of a node, the inner degree > =2 or the outer degree > =2;

Consisting of a node, the degree inside =1 and the degree outside =1;

Length > =1 for maximum drill

DD – path graph

A DD-path graph is a labeled directed graph in which nodes represent the DD Path of a program graph and edges represent the control flow of the Path.

For a given program, many different program diagrams can be constructed, all of which can be reduced to a unique DD-path diagram.

It is possible to generate DD paths for programs up to 100 lines, and above that size, analysis tools are generally required.

The simplest control flow diagram is the DD path. DD can be thought of as belonging to the control flow diagram.

DD path definition:

Given a program written in an imperative language, its DD path graph is a directed graph, where nodes represent the DD paths of its program graph and edges represent the control flow between successive DD paths.

In fact, the DD path graph is a compressed graph in which 2-connected components are compressed into a single node corresponding to the 5DD path.

source：

Click to access 08-PathTestingCoverage.pdf

From the blog haorusong by and used with permission of the author. All other rights reserved by the author.

DD path graphs

Structural testing is based on the source code of the program under test, rather than the definition. This is known as white box testing, while functional testing is known as black-box testing.

Program diagram: For a program written in an imperative programming language, the program diagram is a directed graph with nodes representing statement fragments and edges representing control flow.

DD – path

DD path: Decision-to-decision path (Miller). Begin with the “exit” of the decision statement and end with the “path” of the next decision statement.

DD chain: A path of starting and ending nodes at different points in a directed graph.

Consisting of a node, the internality =0;

Consisting of a node, externality =0;

Consisting of a node, the inner degree > =2 or the outer degree > =2;

Consisting of a node, the degree inside =1 and the degree outside =1;

Length > =1 for maximum drill

DD – path graph

A DD-path graph is a labeled directed graph in which nodes represent the DD Path of a program graph and edges represent the control flow of the Path.

For a given program, many different program diagrams can be constructed, all of which can be reduced to a unique DD-path diagram.

It is possible to generate DD paths for programs up to 100 lines, and above that size, analysis tools are generally required.

The simplest control flow diagram is the DD path. DD can be thought of as belonging to the control flow diagram.

DD path definition:

Given a program written in an imperative language, its DD path graph is a directed graph, where nodes represent the DD paths of its program graph and edges represent the control flow between successive DD paths.

In fact, the DD path graph is a compressed graph in which 2-connected components are compressed into a single node corresponding to the 5DD path.

source：

Click to access 08-PathTestingCoverage.pdf

From the blog haorusong by Unknown and used with permission of the author. All other rights reserved by the author.

DD path graphs

Structural testing is based on the source code of the program under test, rather than the definition. This is known as white box testing, while functional testing is known as black-box testing.

Program diagram: For a program written in an imperative programming language, the program diagram is a directed graph with nodes representing statement fragments and edges representing control flow.

DD – path

DD path: Decision-to-decision path (Miller). Begin with the “exit” of the decision statement and end with the “path” of the next decision statement.

DD chain: A path of starting and ending nodes at different points in a directed graph.

Consisting of a node, the internality =0;

Consisting of a node, externality =0;

Consisting of a node, the inner degree > =2 or the outer degree > =2;

Consisting of a node, the degree inside =1 and the degree outside =1;

Length > =1 for maximum drill

DD – path graph

A DD-path graph is a labeled directed graph in which nodes represent the DD Path of a program graph and edges represent the control flow of the Path.

For a given program, many different program diagrams can be constructed, all of which can be reduced to a unique DD-path diagram.

It is possible to generate DD paths for programs up to 100 lines, and above that size, analysis tools are generally required.

The simplest control flow diagram is the DD path. DD can be thought of as belonging to the control flow diagram.

DD path definition:

Given a program written in an imperative language, its DD path graph is a directed graph, where nodes represent the DD paths of its program graph and edges represent the control flow between successive DD paths.

In fact, the DD path graph is a compressed graph in which 2-connected components are compressed into a single node corresponding to the 5DD path.

source：

Click to access 08-PathTestingCoverage.pdf

From the blog haorusong by Unknown and used with permission of the author. All other rights reserved by the author.