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Fix typos (#52479)
Fix typos
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doc/src/devdocs/EscapeAnalysis.md

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## Try it out!
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You can give a try to the escape analysis by loading the `EAUtils.jl` utility script that
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define the convenience entries `code_escapes` and `@code_escapes` for testing and debugging purposes:
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defines the convenience entries `code_escapes` and `@code_escapes` for testing and debugging purposes:
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```@repl EAUtils
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let JULIA_DIR = normpath(Sys.BINDIR, "..", "share", "julia")
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# load `EscapeAnalysis` module to define the core analysis code
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end
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```
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The symbols in the side of each call argument and SSA statements represents the following meaning:
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The symbols on the side of each call argument and SSA statements represent the following meaning:
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- `` (plain): this value is not analyzed because escape information of it won't be used anyway (when the object is `isbitstype` for example)
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- `` (green or cyan): this value never escapes (`has_no_escape(result.state[x])` holds), colored blue if it has arg escape also (`has_arg_escape(result.state[x])` holds)
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- `` (blue or yellow): this value can escape to the caller via return (`has_return_escape(result.state[x])` holds), colored yellow if it has unhandled thrown escape also (`has_thrown_escape(result.state[x])` holds)

doc/src/devdocs/aot.md

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Once the methods to be compiled have been identified, they are passed to the `jl_create_system_image` function. This function sets up a number of data structures that will be used when serializing native code to a file, and then calls `jl_create_native` with the array of methods. `jl_create_native` runs codegen on the methods produces one or more LLVM modules. `jl_create_system_image` then records some useful information about what codegen produced from the module(s).
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The module(s) are then passed to `jl_dump_native`, along with the information recorded by `jl_create_system_image`. `jl_dump_native` contains the code necessary to serialize the module(s) to bitcode, object, or assembly files depending on the command-line options passed to Julia. The serialized code and information is then written to a file as an archive.
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The module(s) are then passed to `jl_dump_native`, along with the information recorded by `jl_create_system_image`. `jl_dump_native` contains the code necessary to serialize the module(s) to bitcode, object, or assembly files depending on the command-line options passed to Julia. The serialized code and information are then written to a file as an archive.
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The final step is to run a system linker on the object files in the archive produced by `jl_dump_native`. Once this step is complete, a shared library containing the compiled code is produced.
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doc/src/tutorials/creating-packages.md

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Later, we may wish to change `greet_alien` to
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```julia
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"Greet an alien by a the name of \"Zork\"."
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"Greet an alien by the name of \"Zork\"."
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greet_alien() = print("Hello Zork")
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```
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#### Using an extension while supporting older Julia versions
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In the case where one wants to use an extension (without worrying about the
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feature of the extension begin available on older Julia versions) while still
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feature of the extension being available on older Julia versions) while still
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supporting older Julia versions the packages under `[weakdeps]` should be
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duplicated into `[extras]`. This is an unfortunate duplication, but without
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doing this the project verifier under older Julia versions will throw an error

doc/src/tutorials/profile.md

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## Memory allocation analysis
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One of the most common techniques to improve performance is to reduce memory allocation. Julia
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provides several tools measure this:
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provides several tools to measure this:
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### `@time`
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