Category Archives: #CS

Be the Worst

There is a saying in China: Better be the tail of a lion than a fox’s head! There is another saying: Better be the head of a chicken than the tail of a phoenix.

 

Surround yourself with developers who are better than you. Find a more robust team where you can be the weakest member and have room to grow. In the beginning, you may not feel confident in your life, but the process of developing and learning in the workplace that makes you stronger is lovely. In this society, no one will care how beautiful and challenging your strategy is. The most important thing is the result. Have you grown and become stronger during this period of enduring learning?

Remember, the probability of being rejected or thought strange by a potential mentor is not high, and the potential payoff is enormous. Even if the person isn’t interested in taking you on as a full-time apprentice, asking her out to lunch can be a valuable investment of time and money, like why dinner with Warren Buffett was auctioned off at such a high price. An early-stage businessman, or an established businessman who has achieved success in a particular field, is all vying for this opportunity. Do they care about the meal? No, they need to learn something from talking to Buffett. Such as looking at the market, investment vision, and the future development trend of business. In computer learning, the principle is the same. By talking with the people above us or the successful people, we can get the information and direction beneficial to our future development. Opportunities are for those prepared, and the accumulation of experience and insight in life will make you soar when opportunities come.

Ask lots of questions.

Tasks such as maintaining build systems, product support, responding to maintenance requirements, bug fixes, code reviews, eliminating technical debt, creating project wikis, updating documentation, acting as a sounding board for other people’s ideas, and so on. Typically, you focus on the less risky edges of the system rather than the core, which often has many dependencies and a lot of complexity. Jean Lave and Etienne Wenger look at apprenticeships in different industries and find that “in the workflow, the tasks of a novitiate are often placed at the end of a branch, rather than in the middle of a series of clips of work” (Situational Learning, p. 110). These fringe tasks benefit the team and you as an apprentice, as they are often skipped in school classes and fill in the gaps. The experience still helps when you become a skilled worker because many of your mentors understand how important it is to do the tedious work. After all, if no one cleans the floor, the team can’t do the glamorous work because it is Mired in a mess.

What’s the most grubby task your team has been putting off for months? It should be the one that everyone complains about, and nobody wants to fix. You solve it. Don’t hold your nose and force yourself to do it; See if you can solve the problem creatively in a way that exceeds people’s expectations and is fun for you. Many people feel that this is a job that is not worth their time. If you don’t do well, you will help the team take the blame. If you do well, the team will take the credit. But you grow as you solve what the team can’t do.

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

Be the Worst

There is a saying in China: Better be the tail of a lion than a fox’s head! There is another saying: Better be the head of a chicken than the tail of a phoenix.

 

Surround yourself with developers who are better than you. Find a more robust team where you can be the weakest member and have room to grow. In the beginning, you may not feel confident in your life, but the process of developing and learning in the workplace that makes you stronger is lovely. In this society, no one will care how beautiful and challenging your strategy is. The most important thing is the result. Have you grown and become stronger during this period of enduring learning?

Remember, the probability of being rejected or thought strange by a potential mentor is not high, and the potential payoff is enormous. Even if the person isn’t interested in taking you on as a full-time apprentice, asking her out to lunch can be a valuable investment of time and money, like why dinner with Warren Buffett was auctioned off at such a high price. An early-stage businessman, or an established businessman who has achieved success in a particular field, is all vying for this opportunity. Do they care about the meal? No, they need to learn something from talking to Buffett. Such as looking at the market, investment vision, and the future development trend of business. In computer learning, the principle is the same. By talking with the people above us or the successful people, we can get the information and direction beneficial to our future development. Opportunities are for those prepared, and the accumulation of experience and insight in life will make you soar when opportunities come.

Ask lots of questions.

Tasks such as maintaining build systems, product support, responding to maintenance requirements, bug fixes, code reviews, eliminating technical debt, creating project wikis, updating documentation, acting as a sounding board for other people’s ideas, and so on. Typically, you focus on the less risky edges of the system rather than the core, which often has many dependencies and a lot of complexity. Jean Lave and Etienne Wenger look at apprenticeships in different industries and find that “in the workflow, the tasks of a novitiate are often placed at the end of a branch, rather than in the middle of a series of clips of work” (Situational Learning, p. 110). These fringe tasks benefit the team and you as an apprentice, as they are often skipped in school classes and fill in the gaps. The experience still helps when you become a skilled worker because many of your mentors understand how important it is to do the tedious work. After all, if no one cleans the floor, the team can’t do the glamorous work because it is Mired in a mess.

What’s the most grubby task your team has been putting off for months? It should be the one that everyone complains about, and nobody wants to fix. You solve it. Don’t hold your nose and force yourself to do it; See if you can solve the problem creatively in a way that exceeds people’s expectations and is fun for you. Many people feel that this is a job that is not worth their time. If you don’t do well, you will help the team take the blame. If you do well, the team will take the credit. But you grow as you solve what the team can’t do.

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

Be the Worst

There is a saying in China: Better be the tail of a lion than a fox’s head! There is another saying: Better be the head of a chicken than the tail of a phoenix.

 

Surround yourself with developers who are better than you. Find a more robust team where you can be the weakest member and have room to grow. In the beginning, you may not feel confident in your life, but the process of developing and learning in the workplace that makes you stronger is lovely. In this society, no one will care how beautiful and challenging your strategy is. The most important thing is the result. Have you grown and become stronger during this period of enduring learning?

Remember, the probability of being rejected or thought strange by a potential mentor is not high, and the potential payoff is enormous. Even if the person isn’t interested in taking you on as a full-time apprentice, asking her out to lunch can be a valuable investment of time and money, like why dinner with Warren Buffett was auctioned off at such a high price. An early-stage businessman, or an established businessman who has achieved success in a particular field, is all vying for this opportunity. Do they care about the meal? No, they need to learn something from talking to Buffett. Such as looking at the market, investment vision, and the future development trend of business. In computer learning, the principle is the same. By talking with the people above us or the successful people, we can get the information and direction beneficial to our future development. Opportunities are for those prepared, and the accumulation of experience and insight in life will make you soar when opportunities come.

Ask lots of questions.

Tasks such as maintaining build systems, product support, responding to maintenance requirements, bug fixes, code reviews, eliminating technical debt, creating project wikis, updating documentation, acting as a sounding board for other people’s ideas, and so on. Typically, you focus on the less risky edges of the system rather than the core, which often has many dependencies and a lot of complexity. Jean Lave and Etienne Wenger look at apprenticeships in different industries and find that “in the workflow, the tasks of a novitiate are often placed at the end of a branch, rather than in the middle of a series of clips of work” (Situational Learning, p. 110). These fringe tasks benefit the team and you as an apprentice, as they are often skipped in school classes and fill in the gaps. The experience still helps when you become a skilled worker because many of your mentors understand how important it is to do the tedious work. After all, if no one cleans the floor, the team can’t do the glamorous work because it is Mired in a mess.

What’s the most grubby task your team has been putting off for months? It should be the one that everyone complains about, and nobody wants to fix. You solve it. Don’t hold your nose and force yourself to do it; See if you can solve the problem creatively in a way that exceeds people’s expectations and is fun for you. Many people feel that this is a job that is not worth their time. If you don’t do well, you will help the team take the blame. If you do well, the team will take the credit. But you grow as you solve what the team can’t do.

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

The difference between Stubs and Mocks

A mock is an object that can set an expected value, which will verify that the desired action has occurred. The stub is the object that you pass to the code under test. You can set expectations on it to work in specific ways, but those expectations are never verified. The stub’s properties will automatically behave as standard properties, and you cannot set expectations on them.

If you want to verify the code’s behavior under test, a simulation with appropriate expectations is used and validated. If you’re going to pass only values that might need to work somehow but are not the focus of the test, you can use stubs.

Important note: Stubs will never cause a test to fail. 

I believe the most significant difference is that you have written the stub with predetermined behavior. Thus, you will have a class that implements the dependencies that you have disguised for testing purposes (most likely an abstract class or interface), and a class will handle the method only through the response that is set. They don’t do anything fancy, and you’ve already written stub code for them outside of testing.

Simulations are expectations that stubs must set during testing. The simulation is not set up in a predetermined way, so you have the code to perform the simulation in your tests. The mockery is determined at run time because the code that sets expectations must be run before they do anything.

The difference between stubs and stubs

Tests written with simulation usually follow a test pattern of initialize-> set expectations -> exercise -> verify. The pre-written stub will be followed by an initialize-> exercise-> verify.

Similarities between stubs and stubs

The purpose of both is to remove all dependencies from testing a class or function so that your tests are more focused and straightforward when trying to prove it.

The most crucial difference between Stubs and Mocks is their intention. Explain this in the WHY stub and WHY simulation below

Suppose I’m writing test code for the Mac Twitter client’s public timeline controller

Here is the sample code for the test：

twitter_api.stub(:public_timeline).and_return(public_timeline_array)

client_ui.should_receive(:insert_timeline_above).with(public_timeline_array)

controller.refresh_public_timeline

Stub: The network connection to the Twitter API is very slow, which makes my tests slow. We knew it would return the timeline, so we made a stub that simulated the HTTP Twitter API so that our test could sprint, even if I were offline.


Mock: We haven’t written any UI methods yet, and I’m not sure what we need to register for UI objects. We wanted to write test code to see how my controller would work with UI objects.

In short, there is a difference between Mock and Stub objects, and RhinoMocks recognize that they allow us to write tests that better illustrate their purpose. The mock object is used to define the expectation that, in this case, I want to call the method A () with such an argument. Record and verify this expectation with ridicule. On the other hand, Stubs have a different purpose: they do not record or validate expectations but rather allow us to “replace” the behavior and state of “fake” objects to take advantage of test scenarios.

https://martinfowler.com/articles/mocksArentStubs.html

View at Medium.com

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

The difference between Stubs and Mocks

A mock is an object that can set an expected value, which will verify that the desired action has occurred. The stub is the object that you pass to the code under test. You can set expectations on it to work in specific ways, but those expectations are never verified. The stub’s properties will automatically behave as standard properties, and you cannot set expectations on them.

If you want to verify the code’s behavior under test, a simulation with appropriate expectations is used and validated. If you’re going to pass only values that might need to work somehow but are not the focus of the test, you can use stubs.

Important note: Stubs will never cause a test to fail. 

I believe the most significant difference is that you have written the stub with predetermined behavior. Thus, you will have a class that implements the dependencies that you have disguised for testing purposes (most likely an abstract class or interface), and a class will handle the method only through the response that is set. They don’t do anything fancy, and you’ve already written stub code for them outside of testing.

Simulations are expectations that stubs must set during testing. The simulation is not set up in a predetermined way, so you have the code to perform the simulation in your tests. The mockery is determined at run time because the code that sets expectations must be run before they do anything.

The difference between stubs and stubs

Tests written with simulation usually follow a test pattern of initialize-> set expectations -> exercise -> verify. The pre-written stub will be followed by an initialize-> exercise-> verify.

Similarities between stubs and stubs

The purpose of both is to remove all dependencies from testing a class or function so that your tests are more focused and straightforward when trying to prove it.

The most crucial difference between Stubs and Mocks is their intention. Explain this in the WHY stub and WHY simulation below

Suppose I’m writing test code for the Mac Twitter client’s public timeline controller

Here is the sample code for the test：

twitter_api.stub(:public_timeline).and_return(public_timeline_array)

client_ui.should_receive(:insert_timeline_above).with(public_timeline_array)

controller.refresh_public_timeline

Stub: The network connection to the Twitter API is very slow, which makes my tests slow. We knew it would return the timeline, so we made a stub that simulated the HTTP Twitter API so that our test could sprint, even if I were offline.


Mock: We haven’t written any UI methods yet, and I’m not sure what we need to register for UI objects. We wanted to write test code to see how my controller would work with UI objects.

In short, there is a difference between Mock and Stub objects, and RhinoMocks recognize that they allow us to write tests that better illustrate their purpose. The mock object is used to define the expectation that, in this case, I want to call the method A () with such an argument. Record and verify this expectation with ridicule. On the other hand, Stubs have a different purpose: they do not record or validate expectations but rather allow us to “replace” the behavior and state of “fake” objects to take advantage of test scenarios.

https://martinfowler.com/articles/mocksArentStubs.html

View at Medium.com

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

The difference between Stubs and Mocks

A mock is an object that can set an expected value, which will verify that the desired action has occurred. The stub is the object that you pass to the code under test. You can set expectations on it to work in specific ways, but those expectations are never verified. The stub’s properties will automatically behave as standard properties, and you cannot set expectations on them.

If you want to verify the code’s behavior under test, a simulation with appropriate expectations is used and validated. If you’re going to pass only values that might need to work somehow but are not the focus of the test, you can use stubs.

Important note: Stubs will never cause a test to fail. 

I believe the most significant difference is that you have written the stub with predetermined behavior. Thus, you will have a class that implements the dependencies that you have disguised for testing purposes (most likely an abstract class or interface), and a class will handle the method only through the response that is set. They don’t do anything fancy, and you’ve already written stub code for them outside of testing.

Simulations are expectations that stubs must set during testing. The simulation is not set up in a predetermined way, so you have the code to perform the simulation in your tests. The mockery is determined at run time because the code that sets expectations must be run before they do anything.

The difference between stubs and stubs

Tests written with simulation usually follow a test pattern of initialize-> set expectations -> exercise -> verify. The pre-written stub will be followed by an initialize-> exercise-> verify.

Similarities between stubs and stubs

The purpose of both is to remove all dependencies from testing a class or function so that your tests are more focused and straightforward when trying to prove it.

The most crucial difference between Stubs and Mocks is their intention. Explain this in the WHY stub and WHY simulation below

Suppose I’m writing test code for the Mac Twitter client’s public timeline controller

Here is the sample code for the test：

twitter_api.stub(:public_timeline).and_return(public_timeline_array)

client_ui.should_receive(:insert_timeline_above).with(public_timeline_array)

controller.refresh_public_timeline

Stub: The network connection to the Twitter API is very slow, which makes my tests slow. We knew it would return the timeline, so we made a stub that simulated the HTTP Twitter API so that our test could sprint, even if I were offline.


Mock: We haven’t written any UI methods yet, and I’m not sure what we need to register for UI objects. We wanted to write test code to see how my controller would work with UI objects.

In short, there is a difference between Mock and Stub objects, and RhinoMocks recognize that they allow us to write tests that better illustrate their purpose. The mock object is used to define the expectation that, in this case, I want to call the method A () with such an argument. Record and verify this expectation with ridicule. On the other hand, Stubs have a different purpose: they do not record or validate expectations but rather allow us to “replace” the behavior and state of “fake” objects to take advantage of test scenarios.

https://martinfowler.com/articles/mocksArentStubs.html

View at Medium.com

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

The Long Road

 When working on an open-source project, 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. Take a look at the structure of the codebase and think about why the code is organized the way it is. Take a look at the way developers organize their code modules to see if it makes sense, and compare it to the way they might have used it. 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. Not only will it 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. Ask yourself if the developers of the project might know something you don’t or vice versa. Consider the possibility that this is a legacy design that needs to be refactored; And 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 small problems more quickly and quickly. You’ll be able to tackle problems that others think are impossible to solve because they don’t have access to your toolbox. Take a look at the code for 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 make use of 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 your own. 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 very important. 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 structure of the project and highlighting the new ideas you’ve learned. Can you find a situation in your daily work where the same idea can be applied?

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

The Long Road

 When working on an open-source project, 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. Take a look at the structure of the codebase and think about why the code is organized the way it is. Take a look at the way developers organize their code modules to see if it makes sense, and compare it to the way they might have used it. 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. Not only will it 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. Ask yourself if the developers of the project might know something you don’t or vice versa. Consider the possibility that this is a legacy design that needs to be refactored; And 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 small problems more quickly and quickly. You’ll be able to tackle problems that others think are impossible to solve because they don’t have access to your toolbox. Take a look at the code for 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 make use of 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 your own. 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 very important. 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 structure of the project and highlighting the new ideas you’ve learned. Can you find a situation in your daily work where the same idea can be applied?

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

The Long Road

 When working on an open-source project, 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. Take a look at the structure of the codebase and think about why the code is organized the way it is. Take a look at the way developers organize their code modules to see if it makes sense, and compare it to the way they might have used it. 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. Not only will it 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. Ask yourself if the developers of the project might know something you don’t or vice versa. Consider the possibility that this is a legacy design that needs to be refactored; And 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 small problems more quickly and quickly. You’ll be able to tackle problems that others think are impossible to solve because they don’t have access to your toolbox. Take a look at the code for 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 make use of 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 your own. 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 very important. 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 structure of the project and highlighting the new ideas you’ve learned. Can you find a situation in your daily work where the same idea can be applied?

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

Transpiler

 Transpilers, or source-to-source compilers, are tools that read source code written in one programming language and generate equivalent code in another language with a similar level of abstraction. A good example of a translator is the TypeScript translator, which translates TypeScript code into JavaScript. The Babel compiler can also be used for ES6 JS code to ES5 JS code.

Compilers also translate code from one language to another, but the level of abstraction is very different between the two languages. For example, compile from .java to .class files.

ES6 and ES5

To understand the translator, you must first understand the difference between ES6 and ES5 JavaScript. ES6 (ECMAScript 6) is the specification for the next version of JavaScript. Some of its major enhancements include modules, class declarations, lexical block scopes, iterators and generators, a commitment to asynchronous programming, deconstructing patterns, and appropriate tail calls.

The features are great, but most browsers do not support the specification until now. As a result, any UI application specification written in ES6 will not work in most browsers. To run these applications, you must convert this ES6 source code to the supported JavaScript version ES5. ES5 is supported by almost all browsers and is by far the most stable version.

ES6 – Brings “types” to JavaScript. Make it closer to strongly typed languages such as Java and C#. So far, most browsers don’t support it. It must be converted to ES5 to execute in the browser.

ES5 – Over the years, we’ve been writing plain JavaScript.

Translation unit

A compiler is a program-like compiler that converts ES6 JavaScript code into ES5 JavaScript code to run in a browser. When the compiler sees an expression that uses the language functionality that needs to be translated, it generates a logically equivalent expression. The resulting expression can be very similar to or very different from the source expression.

What does a translator do?

ES6 code => ES5 code (even ES4, ES3)

Sources

https://scotch.io/tutorials/javascript-transpilers-what-they-are-why-we-need-them

https://devopedia.org/transpiler

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