Shulou(Shulou.com)06/03 Report--

Thinking Mode Decides Height--Starting from Popularizing Excellent Tools

In the annual excellent software/method practice inventory summary promotion project, and colleague CK discussion, we all think this matter is not cost-effective. There are three reasons:

First, we need to reconstruct some good methods/tools courseware, and we need to conduct in-depth research on the tools themselves;

Second, after research, we found that each tool is profound and far beyond our actual application intention;

Third, we try to make idiotic tutorials so that every new person can quickly get started.

The above reasons make us desperate. In this way, some good tools can be quickly learned by all people. But in turn, it is impossible to put an industry's technology pre-research, optimization, exploration work on a team. More innovation, discovery, should be in each person themselves. We hope that everyone has the spirit and courage to explore independently.

So I couldn't help but say something at the end of the project: sharing is a spirit and an idea. For example, the webmaster who makes good use of Jiaruan said something similar: sharing is to provide information, tools and methods, not to feed the mouth. I also said in the company's public training class: everyone in the school pays for dozens of hours of study for a course, and then divides the scope of the examination, the effect is not satisfactory; then, in the company training, two hours of time, it is impossible for you to specifically master a technology, its role is to tell you: there is a technology/tool/method, probably can solve what problem. If you are interested, you can study one or two. Tools and sharing, must be in their own work, there are thinking, analysis, confused teams and people, will have the initiative to try to explore and solve problems, will see some sharing, there is a sense of clearing clouds, enlightenment.

This topic leads to today's proposition, which is the mode of thinking.

I. Learning thinking

In 2012, we extracted a lot of good things, but found it very difficult to share them successfully. For example, some tools may involve linux, databases, and front-end domains. But there are very few applications in each area. This raises two questions:

1.1 Multidisciplinary solutions are rarely effective in training outreach.

A new tool or method often spans several fields. This raises a practical problem-it is unlikely to find a person within the range of people to learn and satisfy the prerequisites of familiarity in several fields of knowledge.

In fact, this is also one of the biggest difficulties in recruiting, hoping to recruit a person who will have skills in multiple fields. For example, you need to know your job, linux, shell script, TCP/IP, and database. The knowledge between different fields was connected together, forming a natural chasm.

For example, if you want to find a girlfriend who can cook, play the piano, dance, and speak French, it's basically out of the question-refer to Feng Jie's criteria. A subset, intersection, is this concept. However, if you find a girlfriend who can cook, including the four major cuisines, French cuisine, Korean kimchi, and choose specific skills in one field, it will be relatively reliable.

Therefore, a cross-disciplinary knowledge point promotion, is not to find how many people can directly learn, learn and apply. If you want to promote an interdisciplinary tool, method, must be pre-training in certain disciplines, first on a few basic courses, in order to carry out effective training for this knowledge point.

1.2 In multidisciplinary learning, depth and breadth are very difficult to judge.

Again, for example, we want to promote a new tool Easy Test. You need to know some tcp/ip, you need to know some regular expressions, you need to know some tunnels, and you need to know some basic test script methods for recording and playback.

Looks profound? However, each skill only required you to understand a little bit. For example, TCP/IP, if it is according to Cisco's recommended "TCP/IP Detailed Explanation" three-volume view, you may see two years or half-understood, but you use this tool, may only need a few thousand pages of professional information in a dozen pages, which means that you get about 1%, you can smoothly carry out daily work. Similarly, understanding some recording and playback may feel very profound to some people. If you want to thoroughly understand this stuff, you may have to start with robot. However, if you look at all kinds of primary and middle school students who are obsessed with games, they are very good at using button sprites. They certainly don't understand computer language, but it still doesn't affect their ability to control a tool.

This problem will trouble many people, there are too many things to learn, but any subject, if you want to learn small success, solid from scratch, it will take about one or two years. This obviously doesn't fit with the job demands of fast learning, fast application, and fast results.

In software development, the learning and application patterns we face are as follows:

A new technology point/new hardware/new operating system/new algorithm/new architecture, a team needs to learn. Roughly drawn, it requires knowledge points in eight disciplines, but it is definitely not to learn all eight disciplines thoroughly. It may only require about one thousandth of the knowledge in each discipline field. So, the learning model is: first look at the documentation, then immediately do it, then google all the way, copy the code all the way, try and try all the way.

Many newcomers will envy old employees when facing a profession and skills in many fields. They are really awesome and know everything. At the same time, you will also have a fear of what you have to learn-so many things, when can you learn them all? When he was young, he had learned so many skills. What if he changed careers two or three years later, would his efforts be wasted?

In fact, this is thinking too much. This job is destined to expose you to many subject areas, but you may only need to master 1% of a subject. You can understand that this is the familiar pre-exam scoping section, the difference is, this range, part of the old staff, mentor to you designated, part of their own in different application modes, their own scoping to their own. The depth and breadth of judgment mentioned above is the ability to define your own scope.

Similarly, what you learn piecemeal doesn't necessarily help you directly in your next career. Just like the mathematics and physics you have learned all the way, now you may only use it to buy things, even the addition and subtraction of hundreds of digits need to use a calculator, but it still does not affect your science and engineering model for more than ten years, bringing you rigorous and comprehensive thinking mode. Yes, through practice, the mode of thinking acquired is the greatest gain. Learning is a kind of practice, you only through this time and again learning, in order to cultivate a systematic learning ideas and learning methods.

An example can be given in another field. For example, sales to face customers, you may have seen a lot of communication methods and skills in books, but you must go face-to-face and many customers to communicate, in order to achieve a more smooth and transparent realm. You can't ask the question: what impact will it have on me three years from now if this client doesn't work out? What benefits will it have? But you must know that when you communicate with hundreds of customers, talk about some projects, talk about some projects…you will have confidence in your own communication and conduct, and then believe that no matter what kind of customer you face, you can communicate well and get the project done. This is to achieve the goal of sublimation of one's own personality and EQ through repeated, unapproachable fine communication. Turning it over, learning various fragmentary knowledge points in the technical field is also the same, which may not be directly applied to your job position three years later, but the exploration of learning itself, the logic of thinking, the systematic refinement, and even the affirmation of self (Lao Zi is awesome, learning XX language is also a matter of three months, now these new things, count as a ball ah), this is the essence behind fragmentary learning.

Therefore, for newcomers to learn technical knowledge, three suggestions are given:

1. Learn only one subject to be very profound. Truth is interlinked, one law is common, all laws are clear.

In the face of a huge knowledge system, do not try to learn every subject very solid, which does not conform to the laws of the workplace itself. In your favorite and best field, study a science very deeply, and then you will find that other fields, in logic and methodology, can learn from each other and verify each other. So find your own method, learn it thoroughly, and then verify other fields. This is the fastest way to learn.

2. In the face of other knowledge that needs to be mastered, it is necessary to cultivate the ability to focus.

If you need it on a project, then take a subject, delineate the scope of 30 pages, learn while using it, and do the project first after you get it done, without seeking deep understanding. In the course of the project, some questions will naturally understand, some questions when the project is over, you may not understand, but there is no further in-depth study, to understand the value and significance.

3. Adapt to this learning mode and refine a kind of learning thinking.

A new thing, roughly what framework, should be to obtain those relevant knowledge points, and then follow the map, step by step to get it.

If you can't cultivate this kind of learning thinking, just hope to have a person/course, can let oneself do not use the brain, all the way next, all the way to see the operation, can solve a technology, then, no matter how excellent the tool, can not be promoted successfully.

Look around you at the big books, from C++ to Python, which we call reference books. Therefore, it is not destined to let you memorize English dictionary, eat raw hard, understand word by word line, before you can work. Reference books, that is, when you are coding code, you will open them from time to time to consult and learn.

Learning to apply what you have learned at work requires a core technology that is close to your body, and then you can actively learn to define your own scope.

Second, the test of thinking

Similarly, over the years in the testing field, I have tried to teach a lot of testing methods, testing concepts, from black box testing to scenario analysis, but with little success. A lot of soft knowledge cannot be copied from books, or similar to learning a process of an assembly line, which can train most people. It was only after thinking about the pain that he realized that this was actually a kind of cultivation of thinking logic, just like mathematics and physics. Through repeated exercises, the final result was a relatively rigorous and meticulous thinking mode of science and engineering.

The ultimate philosophical question is: Who are you? Where are you from? Where are you going?

So the ultimate question for testing is: What is this? How do you test this? How do you verify the results?

All thinking and design about testing can be reduced to these three questions.

For example, the proposition "how to test seismic testing equipment", there is no doubt that the laboratory is impossible to simulate the parameters of earthquakes. So how do you design it? If you have money, set up a test environment at the active points of abnormal movements in each plate, or simply, where earthquakes occur, bring equipment, take advantage of aftershocks, and carry out some instrument tests when the environment on the spot exists?

Therefore, the thinking of testing should be a kind of thinking of stripping silk and cocoon, setting up various verification methods and checkpoints, and then confirming the verification results. If this thinking mode is not developed, then no matter how much training in test design is useless. One is the initiative of self-examination, and the other is the passivity of imitating cats and tigers.

There are many typical displays of thinking on the Internet, such as "How did I find Wang Luodan's address?" Or Zhou Hongyi's telephone leak incident, etc. On the whole, this is a systematic way of thinking:

1. Selected targets

2. Try to construct several ways to obtain resources

3. Traverse acquisition

4. Continuous summary and reflection, bringing in new logic and clues

5. Find the answer or get close to it.

Only after this habit of thinking has been established can the test design we are talking about be successful. It was as if a person was naturally humorous and could naturally come up with one joke at a time. And if it is the other way around, we must let everyone memorize several routines, presumably with twice the effort.

Each area has its own core skills. In technology, there is no doubt that your systematic thinking determines the speed at which you learn new things, determines the speed at which you solve problems, determines the completeness and robustness of your system architecture, and determines your height within your own system.

Please pay attention to my Sina Weibo @ Sanshi Erli

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