The source code of the Linux kernel is placed in the /usr/src/linux directory. The composition of the kernel source code: 1. The arch directory, which contains the core code related to the hardware architecture supported by the core source code; 2. The include directory, which contains most of the core include files; 3. The init directory, which contains the core startup Code; 4. mm directory, contains all memory management code; 5. drivers directory, contains all device drivers in the system; 6. Ipc directory, contains core inter-process communication code.
#The operating environment of this tutorial: linux7.3 system, Dell G3 computer.
Where is the source code of the Linux kernel?
The Linux kernel source code can be obtained from many sources. Generally speaking, under the installed Linux system, the content in the /usr/src/linux directory is the kernel source code.
For source code reading, if you want to go smoothly, it is best to have a certain understanding of the source code knowledge background in advance.
The Linux kernel source code is composed as follows (assuming it is relative to the linux directory):
arch
This subdirectory contains core code related to the hardware architecture supported by this core source code. For example, for the X86 platform, it is i386.
include
This directory contains most of the core include files. There is also a subdirectory for each supported architecture.
init
This directory contains the core startup code.
mm
This directory contains all memory management code. The memory management code related to the specific hardware architecture is located in the arch/*/mm directory. For example, the one corresponding to X86 is arch/i386/mm/fault.c.
drivers
All device drivers in the system are located in this directory. It is further divided into several types of device drivers, each of which also has a corresponding subdirectory, such as the sound card driver corresponding to drivers/sound.
Ipc
This directory contains the core inter-process communication code.
modules
This directory contains modules that have been built and can be dynamically loaded.
fs Linux
Supported file system codes. Different file systems have different corresponding subdirectories. For example, the ext2 file system corresponds to the ext2 subdirectory.
Kernel
Main core code. At the same time, the code related to the processor structure is placed in the arch/*/kernel directory.
Net
#The core network part code. Each subdirectory inside corresponds to an aspect of the network.
Lib
This directory contains the core library code. Library code related to the processor architecture is placed in the arch/*/lib/ directory.
Scripts
This directory contains script files used to configure the core.
Documentation
This directory contains some documents for reference.
If If you want to analyze Linux and delve into the essence of the operating system, reading the kernel source code is the most effective way. We all know that becoming a good programmer requires a lot of practice and code writing. Programming is important, but people who only program can easily limit themselves to their own knowledge areas. If we want to expand the breadth of our knowledge, we need to be exposed to more code written by others, especially code written by people who are more advanced than us. Through this approach, we can break out of the constraints of our own knowledge circle, enter the knowledge circle of others, and learn more about information that we generally cannot learn in the short term. The Linux kernel is carefully maintained by countless "masters" in the open source community, and these people can all be called top code masters. By reading the Linux kernel code, we not only learn kernel-related knowledge, but in my opinion, what is more valuable is learning and understanding their programming skills and understanding of computers.
I also came into contact with the analysis of Linux kernel source code through a project. I benefited a lot from the analysis of source code. In addition to acquiring relevant kernel knowledge, it also changed my past understanding of kernel code:
1. Analysis of kernel source code is not "out of reach". The difficulty of kernel source code analysis does not lie in the source code itself, but in how to use more appropriate methods and means to analyze the code. The hugeness of the kernel means that we cannot analyze it step by step starting from the main function as we do with ordinary demo programs. We need a way to intervene from the middle to "break through" the kernel source code one by one. This "request on demand" approach allows us to grasp the main line of the source code instead of getting too hung up on specific details.
2. The design of the core is beautiful. The special status of the kernel determines that the execution efficiency of the kernel must be high enough to respond to the real-time requirements of current computer applications. For this reason, the Linux kernel uses a hybrid programming of C language and assembly. But we all know that software execution efficiency and software maintainability run counter to each other in many cases. How to improve the maintainability of the kernel while ensuring the efficiency of the kernel depends on the "beautiful" design in the kernel.
3. Amazing programming skills. In the general field of application software design, the status of coding may not be overemphasized, because developers pay more attention to the good design of software, and coding is just a matter of implementation means-just like using an ax to chop wood, without too much thinking. But this is not true in the kernel. Good coding design not only improves maintainability, but also improves code performance.
Everyone’s understanding of the kernel will be different. As our understanding of the kernel continues to deepen, we will have more thoughts and experiences about its design and implementation. Therefore, this article hopes to guide more people who are wandering outside the door of the Linux kernel to enter the world of Linux and experience the magic and greatness of the kernel for themselves. And I am not an expert in kernel source code. I just hope to share my own experience and experience in analyzing source code and provide reference and help to those who need it. To put it "high-sounding", it can be regarded as for the computer industry. Especially in terms of the operating system kernel, contribute your own modest efforts. Without further ado (it’s already too long-winded, sorry~), let me share my own Linux kernel source code analysis method.
Essentially speaking, analyzing Linux kernel code is no different from looking at other people’s code, because what is in front of you Generally it is not the code you wrote yourself. Let’s take a simple example first. A stranger randomly gives you a program and asks you to explain the functional design of the program after reading the source code. I think many people who feel that their programming skills are okay must think this is nothing, as long as they can If you patiently read his code from beginning to end, you will definitely find the answer, and it is indeed the case. So now let's change the hypothesis. If this person is Linus, and what he gives you is the code of a module of the Linux kernel, will you still feel so relaxed? Many people may hesitate. Why does the code given to you by a stranger (of course not if Linus knows you, haha~) give us such different feelings? I think there are the following reasons:
1. The Linux kernel code is somewhat mysterious to the "outside world", and it is so huge that it may feel impossible to start when it is suddenly placed in front of you. For example, it may come from a very small reason-the main function cannot be found. For a simple demo program, we can analyze the meaning of the code from beginning to end, but the method of analyzing the kernel code is completely ineffective, because no one can read the Linux code from beginning to end (because it is really not necessary, and when used, Just look at it).
2. Many people have also come into contact with the code of large-scale software, but most of them are application projects. The form and meaning of the code are related to the business logic they often come into contact with. The kernel code is different. Most of the information it processes is closely related to the bottom layer of the computer. For example, the lack of relevant knowledge about operating systems, compilers, assembly, architecture, etc. will also make reading kernel code difficult.
3. The method of analyzing the kernel code is not reasonable enough. Faced with a large amount of complex kernel code, if you don't start from a global perspective, it's easy to get bogged down in the details of the code. Although the kernel code is huge, it also has its design principles and architecture, otherwise maintaining it would be a nightmare for anyone! If we clarify the overall design idea of the code module and then analyze the implementation of the code, analyzing the source code may be an easy and happy thing.
This is my personal understanding of these issues. If you have not been exposed to large-scale software projects, analyzing Linux kernel code may be a good opportunity to accumulate experience in large-scale projects (indeed, Linux code is the largest project I have been exposed to so far!). If you don’t understand the underlying computer thoroughly enough, then we can choose to accumulate underlying knowledge by analyzing and learning at the same time. The progress of analyzing the code may be a little slow at first, but as knowledge continues to accumulate, our "business logic" of the Linux kernel will gradually become clearer. The last point is how to grasp the source code of analysis from a global perspective. This is also the experience I want to share with you.
From the perspective of people understanding new things, before exploring the essence of things , there must be a process of understanding new things. This process allows us to have a preliminary concept of new things. For example, if we want to learn piano, we need to first understand that playing piano requires us to learn basic music theory, simplified notation, staff and other basic knowledge, and then learn piano playing techniques and fingerings, and finally we can actually start practicing piano.
The same is true for analyzing kernel code. First we need to locate the content involved in the code to be analyzed. Is it the code for process synchronization and scheduling, the code for memory management, the code for device management, the code for system startup, etc. The huge size of the kernel determines that we cannot analyze all the kernel code at once, so we need to give ourselves a reasonable division of labor. As algorithm design tells us, to solve a big problem, we must first solve the sub-problems it involves.
After locating the code range to be analyzed, we can use all the resources at hand to understand the overall structure and general functions of this part of the code as comprehensively as possible.
All the resources mentioned here refer to Baidu, Google large-scale online search engines, operating system principle textbooks and professional books , or the experience and information provided by others, or even the names of documents, comments and source code identifiers provided by the Linux source code (don't underestimate the naming of identifiers in the code, sometimes they can provide key information). In short, all the resources here refer to all the available resources you can think of. Of course, it is impossible for us to obtain all the information we want through this form of information collection. We just want to be as comprehensive as possible. Because the more comprehensive the information is collected, the more information can be used in the subsequent process of analyzing the code, and the less difficult the analysis process will be.
Here is a simple example, assuming that we want to analyze the code implemented by the Linux frequency conversion mechanism. So far we only know this term. From the literal meaning, we can roughly guess that it should be related to the frequency adjustment of the CPU. Through information collection, we should be able to obtain the following relevant information:
1. CPUFreq mechanism.
2. performance, powersave, userspace, ondemand, conservative frequency regulation strategies.
3． /driver/cpufreq/.
4． /documention/cpufreq.
5. P state and C state.
If you can collect this information when analyzing the Linux kernel code, you should be very "lucky". After all, the information about the Linux kernel is indeed not as rich as .NET and JQuery. However, compared with more than ten years ago, when there were no powerful search engines and no relevant research materials, it should be called the "Great Harvest" era! Through a simple "search" (it may take one or two days), we even found the source code file directory where this part of the code is located. I have to say that this kind of information is simply "priceless"!
From the data collection, we were "lucky" to find the source code directory related to the source code. But this does not mean that we are indeed analyzing the source code in this directory. Sometimes the directories we find may be scattered, and sometimes the directories we find contain a lot of code related to specific machines, and we are more concerned about the main mechanism of the code to be analyzed rather than the specialized code related to the machine ( This will help us understand the nature of the kernel more). Therefore, we need to carefully select the information involving code files in the information. Of course, this step is unlikely to be completed at one time, and no one can guarantee that all source code files to be analyzed can be selected at one time and none of them will be missed. But we don’t have to worry. As long as we can capture the core source files related to most modules, we can naturally find them all through detailed analysis of the code later.
Back to the above example, we carefully read the documentation under /documention/cpufreq. The current Linux source code will save the documentation related to the module in the documentation folder of the source code directory. If the module to be analyzed does not have documentation, this will somewhat increase the difficulty of locating key source code files, but it will not cause us to be unable to find them. The source code we want to analyze. By reading the documentation, we can at least pay attention to the source file /driver/cpufreq/cpufreq.c. Through this documentation of the source files, combined with the previously collected frequency modulation strategies, we can easily pay attention to the five source files: cpufreq_performance.c, cpufreq_powersave.c, cpufreq_userspace.c, cpufreq_ondemand, and cpufreq_conservative.c. Have all the documents involved been found? Don't worry, start analyzing from them and sooner or later you will find other source files. If you use sourceinsight to read the kernel source code under Windows, we can easily find other files freq_table.c, cpufreq_stats.c and /include/linux/cpufreq through functions such as function calling and symbol reference searching, combined with code analysis. h.
#When we put all the source code files involved After simple annotation, we can achieve the following results:
1. Basically understand the meaning of the code elements in the source code.
2. Basically all the key source code files involved in this module were found.
Combined with the overall or architectural description of the code to be analyzed based on the previously collected information and data, we can compare the analysis results with the data to determine and revise our understanding of the code. In this way, through a simple comment, we can grasp the main structure of the source code module as a whole. This also achieves the basic purpose of our simple annotation.
After completing the simple comments of the code, it can be considered that half of the analysis of the module is completed, and the remaining content is an in-depth analysis of the code and thorough understanding. Simple comments cannot always describe the specific meaning of code elements very accurately, so detailed comments are very necessary. In this step, we need to clarify the following:
1. When the variable definition is used.
2. When the code defined by the macro is used.
3． The meaning of function parameters and return values.
4． The execution flow and calling relationship of the function.
5. The specific meaning and usage conditions of the structure fields.
We can even call this step detailed function annotation, because the meaning of code elements outside the function is basically clear in simple comments. The execution flow and algorithm of the function itself are the main tasks of this part of annotation and analysis.
For example, how the implementation algorithm of cpufreq_ondemand policy (in function dbs_check_cpu) is implemented. We need to gradually analyze the variables used by the function and the functions called to understand the ins and outs of the algorithm. For the best results, we need the execution flow chart and function call diagram of these complex functions, which is the most intuitive way of expression.
Through this step of comments, we can basically fully grasp the overall code to be analyzed The mechanism is implemented. All analysis work can be considered 80% completed. This step is particularly critical. We must try to make the annotation information accurate enough to better understand the division of internal modules of the code to be analyzed. Although the Linux kernel uses the macro syntax "module_init" and "module_exit" to declare module files, the division of sub-functions within the module is based on a full understanding of the module's functions. Only by dividing the module correctly can we figure out what external functions and variables the module provides (using symbols exported by EXPORT_SYMBOL_GPL or EXPORT_SYMBOL). Only then can we proceed to the next step of analyzing the identifier dependencies within the module.
Through the division of code modules in the fourth step, we can "easily" analyze the modules one by one. Generally, we can start from the module entry and exit functions at the bottom of the file (the functions declared by "module_init" and "module_exit" are usually at the end of the file), based on the functions they call (functions defined by ourselves or other modules) and the functions used Key variables (global variables in this file or external variables of other modules) draw a "function-variable-function" dependency diagram - we call it an identifier dependency diagram.
Of course, the identifier dependency relationship within the module is not a simple tree structure, but in many cases is an intricate network relationship. At this time, the role of our detailed comments on the code is reflected. We divide the module into sub-functions based on the meaning of the function itself, and extract the identifier dependency tree of each sub-function.
Interdependencies between modules
Once all module internal identifier dependency diagrams are sorted out, according to the Variables or functions of other modules can easily determine the dependencies between modules.
The module dependency relationship of cpufreq code can be expressed as the following relationship.
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