What's even funnier is how much they attack anyone who points this out.
It's against the HN guidelines (https://news.ycombinator.com/newsguidelines.html), boring, unenlightening, not intellectually gratifying, degrades the quality of the site, and takes far less intelligence than the "mental equivalent of scurvy" that you name. Don't do it.
> Please respond to the strongest plausible interpretation of what someone says, not a weaker one that's easier to criticize. Assume good faith.
I think most people's amazement with lsp relates to the practical benefits of such a project _not_ being thrown away but taken that last 10% (which is 90% of the work) to make it suitable for so many use cases and selling people on the idea of doing so.
Only having exposure to the algol family of languages does for your mental capabilities what a sugar only diet does for your physical capabilities. It used to be the case that all programmers had exposure to assembly/machine code which broke them out of the worst habits algols instill. No longer.
Pointing out that the majority of programmers today have the mental equivalent of scurvy is somehow condescending but the corp selling false teeth along with their sugar buckets is somehow commendable.
And yeah, I am definitely coming for Lisp.
Which is irrelevant, because you can visualize code however you want via editor extensions.
> And yeah, I am definitely coming for Lisp.
An endeavor which is simultaneously hopeless and pointless.
I do miss the "wrap" command when using other editors, but it could be implemented reasonably easily without a parse tree. I found that a lot of the structural edits correspond to indentation levels anyway, but the parse tree definitely helps.
Google just recently figured this out (That Documents need to be Hierarchical):
https://lifehacker.com/tech/how-to-use-google-docs-tabs
Also interestingly both Documents and Code will some day be combined. Imagine a big tree structure that contains not only computer code but associated documentation. Again probably Jupyter Notebooks is the closest thing to this we have today, because it does incorporate code and text, but afaik it's not fully "Hierarchical" which is the key.
I've had a tree-based block-editor CMS (as my side project) for well over a decade and when Jupyter came out they copied most of my design, except for the tree part, because trees are just hard. That was good, because now when people ask me what my app "is" or "does" I can just say it's mostly like Jupyter, which is easier than starting from scratch with "Imagine if a paragraph was an actual standalone thing...yadda yadda."
#define FOO }
int main() {
FOO
"No one writes code like that!" Actually, they do, and mature C code-bases are full of such preprocessing magic.I'm curious about this unnamed ongoing work (that is unaware of incremental parsing).
Anyone know what he is referring to?
Heck, incremental lexing is even easy to explain. For each token, track where the lexer actually looked in the input stream to make decisions. Any time that part of the input stream changes, every token to actually look at the changed portion of the input stream is re-lexed, and if the result changes, keep re-lexing until the before/after tokenstreams sync up again or you run out of input. That's it.
You can also make a dumber version that statically calculates the maximum lookahead (lookbehind if you support that too) of the entire grammer, or the maximum possible lookahead per token, and uses that instead of tracking the actual lookahead used. In practice, this is often harder than just tracking the actual lookahead used.
In an LL system like ANTLR, incremental parsing is very similar - since it generates top-down parsers, it's the same basic theory - track what token ranges were looked at as you parse. During incremental update, only descend into portions of the parse tree where the token ranges looked at contain modified tokens.
Bottom up is trickier. Error recovery is the meaningfully tricky part in all of this.
Before tree-sitter, I was constantly explaining this stuff to people (I followed the projects that these algorithms came out of - ENSEMBLE, HARMONIA, etc). After more people get that there are ways of doing this, but you still run into people who are re-creating things we solved in pretty great ways many years ago.
It works fine in handwritten recursive-descent parsers, which 99% of the time pass around a state object.
Assume (to simplify enough to write this out quickly for HN) you have the following:
1. A token stream with markings of which tokens changed on the last lex.
2. A handwritten recursive descent parser with a state object passed along.
3. A copy of the last AST generated, with tokens linked into the stream, and the AST being built from pieces by the RD parser as it goes.
4. A function called LA(N) that does lookahead, and a function called LB(N) that does lookbehind
5. We assume that each RD function returns the portion of the AST it built and they get linked together bottom up.
6. We further assume that semantic decisions of whether to descend and of generating portions of the AST are deterministic, and depend only on the tokens in some fashion, and that they use the LA/LB interface to check tokens. None of this is required to make it work, it just makes the HN version simpler[1])
We'll now separate this into the "first parse" and "every other parse" to make it simpler to describe, but it is easy enough to combine.
On first parse, every time LA(n) or LB(n) is called, we mark in the state object that our particular recursive descent function looked at that token (in practice this gets done by tracking the range of tokens looked at).
Overall, We track the min/max range of tokens looked at by a given function the same way you'd do dfs in/out numbers:
fun parse_this_part(state):
starting_min = current_token_index
do some LA/LB/recursive calls/work/whatever
for any recursive call,
update child_min to minimum of any child call, and child_max to max of any child call.
state[parse_this_part].max = max(current_token_index, child_max)
state[parse_tihs_part].min = min(starting_min, child_min)
return ast portion we have built up from our calls/work.
On every additional parse, we do that work plus the following:As we descend, before making a recursive call, check if the tokens in the min/max range of the function about to be called changed. If so, keep descending, and re-parse that portion. If not, return the cached ast, as it cannot have changed.
You will now re-parse only the portions that could have possibly been affected by a change, and since we check before any descent, we will reparse as small a portion as we can for the level of granularity we have on change detection (IE if we track ranges, we will reparse as small a portion as possible that are within those ranges. If we track individual token changes, we will reparse as small a portion as possible, period)
In practice, the vast majority of grammars don't get above n=3 lookahead when doing anything real. most are n=1, some are n=2, n=3 or above is very rare.
You can do better than this in a number of ways: 1. You don't have to keep before/after AST's explicitly
2. If you want explicit per-token tracking, you can make sets of the tokens that got looked at instead of ranges. You can use sparse bitsets and token ids to speed up checking (reducing the problem to whether the sparse bitmap intersection of all_changed_tokens and this_functions_looked_at_tokens is empty)
This is generally not worth the overhead in practice, but it is optimal.
3. Usually things like epoch numbers are added so you can tell which parts of the AST/tree came from which parses for debugging.
4. If you store the min/max ranges in the obvious way (in the parser state, and using the absolute token position), you have to update them on each parse if anything before you added/removed tokens. So in this naive implementation, you still have to do min/max updates as you recurse, but none of the other work. In less naive implementations, you can store the min/max ranges as relative so that you don't have to do this. It usually requires modifying the LA/LB functions to take more state, etc.
If you want to see how it looks in something like ANTLR 4 typescript (there is a regular ANTLR impl too, but i think the typescript version is easier to read), see https://github.com/dberlin/antlr4ts/blob/incremental/src/Inc... and the surrounding files.
I did not try to optimize it really, it was being used in a vscode extension to parse gcode files, which are often very very large for complex designs, but only small portions are usually changed in an editor. For that case, range/etc tracking was fine.
It should be pretty easy to read and see how you would apply this to a hand-written parser. In fact, I would guess you could reuse the vast majority of it pretty directly.
[1] To relax this restriction, you just need to similarly track whatever data the decisions you use to make a call or not (or generate a certain ast or not) that your call and your called children were based on, and a way to tell if it changed. You then check it before descending the same as you check whether the token is changed above.
Seems like "annoying" refers to a user interface annoyance.
I'm guessing the following since I couldn't tell what structured editing is like from the article:
Keyboard entry is immediate, but prone to breaking the program structure. Structured editing through specific commands is an abstraction on top of key entry (or mouse), both of which add a layer of resistance. Another layer might come from having to recall the commands, or if recognizing them, having to peruse a list of them, at least while learning it.
What does the developer's experience with incremental parsing feel like?
It's essentially the experience most of us already have when using Visual Studio, IntelliJ, or any modern IDE on a daily basis.
The term "incremental parsing" might be a bit misleading. A more accurate (though wordier) term would be a "stateful parser capable of reparsing the text in parts". The core idea is that you can write text seamlessly while the editor dynamically updates local fragments of its internal representation (usually a syntax tree) in real time around the characters you're typing.
An incremental parser is one of the key components that enable modern code editors to stay responsive. It allows the editor to keep its internal syntax tree synchronized with the user's edits without needing to reparse the entire project on every keystroke. This stateful approach contrasts with stateless compilers that reparse the entire project from scratch.
This continuous (or incremental) patching of the syntax tree is what enables modern IDEs to provide features like real-time code completion, semantic highlighting, and error detection. Essentially, while you focus on writing code, the editor is constantly maintaining and updating a structural representation of your program behind the scenes.
The article's author suggests an alternative idea: instead of reparsing the syntax tree incrementally, the programmer would directly edit the syntax tree itself. In other words, you would be working with the program's structure rather than its raw textual representation.
This approach could simplify the development of code editors. The editor would primarily need to offer a GUI for tree structure editing, which might still appear as flat text for usability but would fundamentally involve structural interactions.
Whether this approach improves the end-user experience is hard to say. It feels akin to graphical programming languages, which already have a niche (e.g., visual scripting in game engines). However, the challenge lies in the interface.
The input device (keyboard) designed for natural text input and have limitations when it comes to efficiently interacting with structural data. In theory, these hurdles could be overcome with time, but for now, the bottleneck is mostly a question of UI/UX design. And as of today, we lack a clear, efficient approach to tackle this problem.