In this project-centered course you will build a modern software hierarchy, designed to enable the translation and execution of object-based, high-level languages on a bare-bone computer hardware platform. In particular, you will implement a virtual machine and a compiler for a simple, Java-like programming language, and you will develop a basic operating system that closes gaps between the high-level language and the underlying hardware platform. In the process, you will gain a deep, hands-on understanding of numerous topics in applied computer science, e.g. stack processing, parsing, code generation, and classical algorithms and data structures for memory management, vector graphics, input-output handling, and various other topics that lie at the very core of every modern computer system. This is a self-contained course: all the knowledge necessary to succeed in the course and build the various systems will be given as part of the learning experience. The only prerequisite is knowledge of programming at the level acquired in introduction to computer science courses. All the software tools and materials that are necessary to complete the course will be supplied freely after you enrol in the course. This course is accompanied by the textbook "The Elements of Computing Systems" (Nisan and Schocken, MIT Press). While not required for taking the course, the book provides a convenient coverage of all the course topics. The book is available in either hardcopy or ebook form, and MIT Press is offering a 30% discount off the cover price by using the discount code MNTT30 at https://mitpress.mit.edu/books/elements-computing-systems. The course consists of six modules, each comprising a series of video lectures, and a project. You will need about 2-3 hours to watch each module's lectures, and about 15 hours to complete each one of the six projects. The course can be completed in six weeks, but you are welcome to take it at your own pace. You can watch a TED talk about this course by Googling "nand2tetris TED talk". *About Project-Centered Courses: Project-centered courses are designed to help you complete a personally meaningful real-world project, with your instructor and a community of learners with similar goals providing guidance and suggestions along the way. By actively applying new concepts as you learn, you’ll master the course content more efficiently; you’ll also get a head start on using the skills you gain to make positive changes in your life and career. When you complete the course, you’ll have a finished project that you’ll be proud to use and share.
Unit 4.10: Perspective
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来自 Hebrew University of Jerusalem 的课程
Build a Modern Computer from First Principles: Nand to Tetris Part II (project-centered course)
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Hebrew University of Jerusalem
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从本节课中
Compiler I: Syntax Analysis
与讲师见面
Shimon SchockenProfessor
Computer Science
Welcome to the last unit of the first part of our two part or
two module compiler treatment, in which we discussed syntax analysis and parsing.
And as usual,
we will answer some frequently asked questions about this module.
So let's see.
Compilers don't only translate programs, they also find and report errors.
Are we going to handle errors in our Jack compiler?
Well, error diagnostics is something that
we decided to completely sidestep in this module.
In other words, we assumed, quite naively, I must say,
that the source code that we have to compile is error free.
So what should we do if we were to remove this simplifying assumption?
Well, in some cases, catching an error is a simple matter.
For example, suppose that you parse a let statement, L-E-T.
According to the Jack grammar, the keyword let must be followed by an identifier,
as in, say, let x equals something.
So x is an identifier.
So when your parser handles a let token,
it should expect that the next token should be an identifier.
And if the next token is anything but an identifier,
you can generate an error message and terminate the compilation right there.
However, normally, compilers try to be more friendly
and they don't stop dead in their tracks whenever they find an error.
Instead, a clever compiler attempts to somehow contain
the damage that was caused by the current error and proceed to catch and
report additional possible errors in your code.
Also, a clever compiler makes a best effort to try
to sort of pinpoint the exact location
in the source code where the error was conceived, so to speak.
And this location is not necessarily the same place where the error
raised its head, or was detected by the compiler.
So, as you see, error handling is an intricate art
that requires sophisticated diagnostics methods and
intricate code, none of which were discussed in NAND to Tetris.
And as I say this, I feel obliged to also qualify something
that I said when we discussed, I think, tokenizers.
If you recall, I said that once we construct a tokenizer,
an object that implements the tokenizing API, once we do it,
we no longer need the input file, which contains the original source code, because
the tokenizer is going to sort of dispense for us the next token whenever we need it.
So why do we need the source code?
However, if we wish to handle errors,
then we must preserve the original source code in order to annotate it
with all sorts of error messages, warning messages and so on.
All these details are very important when you set out to develop a full
service compiler.
And yet in NAND to Tetris, we decided to build a minimal compiler.
And we decided to treat error diagnostics as an optional feature that can
be certainly added to the basic compiler whenever you want to do it.
All right, so with that,
let us move to the next question, which is.
Can we use the techniques that we learned in this module
to develop parsers for other programming languages?
Let me start by saying that parsers are quite useful,
not only for parsing programs, but also for
parsing any syntax-based text, which happens a lot
in the careers of many application programmers.
There are numerous applications out there,
ranging from bioinformatics to email to financial services in
which you have to handle, analyze, and render structured text.
And the techniques that we learned in this module are directly
applicable to any of these applications.
Specifically, throughout the module, we covered and
developed the two most important elements of syntax analysis.
And they are tokenizing and parsing.
So in that respect, you now have a solid hands-on understanding
of the essence of what it takes to do syntax analysis.
However, compared to other programming languages that you are familiar with,
the language that we handled, Jack, is deliberately simple.
It has neither operator priority nor inheritance nor
many other features that can be found in industrial strength programming languages.
Now, this limited design was obviously done on purpose,
because our goal was to be able to develop a Jack compiler using simple and
elegant parsing algorithms.
In particular, the parsing algorithm that we discussed in this module
builds the parse tree from the top down.
It reads as few tokens as possible, and it tries to determine
which language construct we are parsing as soon as it can make this determination.
Parsers that employ this top-down greedy parsing
strategy are quite suitable for languages that have a simple syntax.
And yet, when compiler developers have to parse languages that have
a more elaborate syntax, they typically resort to using
something known as bottom-up parsing, which is quite different.
This parsing strategy starts bottom-up by first building the terminal
leaves of the parse tree, and they defer the decision of which
language construct we are dealing with to a later stage in the parsing process.
This way,
they can entertain simultaneously several parsing possibilities.
But in order to do this, these algorithms have to use backtracking.
And the result is parsing logic which is harder to develop
than the simple top-down parsing that we used in this module.
Which, once again, is applicable to numerous applications and
to simple languages, but not necessarily for languages like Java and C++.
As usual, there are numerous topics, in this case in compilation and formal
languages, which are simply outside the highly focused scope of NAND to Tetris.
Now, if you find compilation and computational linguistics interesting,
then by now, I think that we gave you a solid foundation to build on.
And you're obviously welcome to consider taking either
a compilation course or buying some decent book about it.
So with that, let's move to the next question.
Why didn't we use lex and yacc?
So, for those of you who are not familiar with these buzzwords, lex and
yacc are two software tools that come from the world of Unix.
And by now, there are numerous versions
of these two tools that have different names and flavors, and
they are implemented in many different programming languages.
Lex stands for Lexical Analyzer, which actually refers
to a tool which is capable of generating tokenizing code automatically.
And yacc stands for the whimsical, Yet
Another Compiler Compiler, which actually refers to a tool
which is capable of generating parsing code automatically.
Typically, lex and yacc go together and are quite inseparable.
So where do these tools come from?
Well, many good programmers are lazy, they're lazy in the positive
sense of the word, and they seek to automate whatever can be automated.
Now, as you may have noticed, and I'm sure you did,
the parsing logic that we outlined throughout this module,
which by the way, was given as a recipe for developing your parser,
well, this parsing logic was highly structured.
In particular, we advised that for each production rule in the Jack grammar,
you guys should develop a corresponding parsing method In your syntax analyzer.
And taken, together all these parsing methods comprise this analyzer.
Now, it turns out that this software development strategy that we
exposed in this module is so structured that indeed
it can be generalized to other grammars and automated.
In other words, if you have a well-defined grammar of some language, or
some file format or whatever, and you can specify this grammar using
some agreed upon machine readable format, then indeed,
you can write a program that takes this grammar specification as input and
produces from it automatically a syntax analyzer
which is written in some language like C or Java or whatnot.
Now, of course, you will have to get into the generated code and
make all sorts of changes here and there.
But most of the logic can be generated
automatically by lex and yacc kind of tools.
And so that's what these tools are all about.
They generate syntax analysis code that can be customized and
developed into a full scale syntax analysis tool.
So let's go back to the question.
Why did we insist on developing the tokenizer and
the parser from scratch, where in fact,
we could have used these automatic tools and make our life much simpler?
Well, I suspect that you know the answer.
NAND to Tetris is about doing everything from scratch from the ground up
in your bare hands in order to explore and understand.
Using black box tools like lex and yacc go against the NAND to Tetris spirit.
And that's why we decided not to use them.
So that's the end of our perspective unit on parsing.
And we now turn to the next module in the course, module five.
In which we will continue to develop our compiler, and in particular,
we're going to deal with code generation.
