Introduces new builders, mainly `SectionTable` and `StringTable`, and a
final `build_elf_image` to merge everything into a single memory image.
Each of the builders are fully detached from one another, although
StringTable provides an extra API to remove steps when using it with a
SectionTable.
This automates the part of figuring out and properly writing offsets to
headers, and making sure all required data is properly copied and
referenced in the final image.
The new JIT::GDB namespace enables registering JITted objects into GDB
dynamically.
Its clients just have to ensure the memory they give to
`register_into_gdb` is in a format that GDB can understand, either by
generating an object file in memory with debug info + symbols or by
registering a custom debug info parser.
None of these are implemented by this API; it only implements the
registering part and lets the client to choose the data format.
GDB JIT Interface:
https://sourceware.org/gdb/current/onlinedocs/gdb.html/JIT-Interface.html#JIT-Interface
Things to take into account from v8's docs, some of which we may
improve: https://v8.dev/docs/gdb-jit#known-limitations
When iterating over an iterable, we get back a JS object with the fields
"value" and "done".
Before this change, we've had two dedicated instructions for retrieving
the two fields: IteratorResultValue and IteratorResultDone. These had no
fast path whatsoever and just did a generic [[Get]] access to fetch the
corresponding property values.
By replacing the instructions with GetById("value") and GetById("done"),
they instantly get caching and JIT fast paths for free, making iterating
over iterables much faster. :^)
26% speed-up on this microbenchmark:
function go(a) {
for (const p of a) {
}
}
const a = [];
a.length = 1_000_000;
go(a);
This patch makes IteratorRecord an Object. Although it's not exposed to
author code, this does allow us to store it in a VM register.
Now that we can store it in a VM register, we don't need to convert it
back and forth between IteratorRecord and Object when accessing it from
bytecode.
The big win here is avoiding 3 [[Get]] accesses on every iteration step
of for..of loops. There are also a bunch of smaller efficiencies gained.
20% speed-up on this microbenchmark:
function go(a) {
for (const p of a) {
}
}
const a = [];
a.length = 1_000_000;
go(a);
When the `TIFF_DEBUG` flag is set, the TIFF decoder logs every tag and
their values. This is already useful but require the developer to have
the spec handy in order to decrypt each value to its signification. None
of this information is available at runtime, but this is known by the
Python generator. So by generating these debug logs, we drastically
increase their value.
As a bonus point, most of these functions should be useful when we will
display image's metadata in Serenity.
The `TIFFType` enum is exported with a different name to C++. This
change of behavior was handled by manually setting the parameter of a
function. However, we will soon need the exported name in more places,
so let's make it a property of the Enum itself.
It was a bit short-sighted to combine the tag and attribute names into
one string when the Inspector requests a context menu. We will want both
values for some context menu actions. Send both names, as well as the
attribute value, when requesting the context menu.
When all the variables in a for..in/of block's lexical scope have been
turned into locals, we don't need to create and immediately abandon an
empty environment for them.
This avoid environment allocation in cases like this:
function foo(a) {
for (const x of a) {
}
}
This change fixes a problem that we should not call `to_px()` to
resolve any length or percentage values during paintables traversal
because that is supposed to happen while performing layout.
Also it improves performance because before we were resolving border
radii during each painting phase but now it happens only once during
layout.
Only some specific number of values should be allowed, but let's accept
everything for now and add these checks when the generator will be more
mature.
Let's make the "read a sample" part independent of the decoder. That
will soon allow us to read samples based on the image's parameter
without duplicating the code for every decoder.
Fixes these errors from `Meta/test_pdf.py path/to/0000`, with
0000 being 0000.zip from the PDF/A corpus in unzipped:
Malformed PDF file: Indexed color space lookup table doesn't
match size, in 4 files, on 8 pages, 73 times
path/to/0000/0000206.pdf 2 4 (2x) 5 (3x) 6 (4x)
path/to/0000/0000364.pdf 5 6
path/to/0000/0000918.pdf 5
path/to/0000/0000683.pdf 8
