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# Design of the Emboss Tool
This document describes the internals of Emboss. End users do not need to read
this document.
*TODO(bolms): Update this doc to include the newer passes.*
The Emboss compiler is divided into separate "front end" and "back end"
programs. The front end parses Emboss files (`.emb` files) and produces a
stable intermediate representation (IR), which is consumed by the back ends.
This IR is defined in [public/ir_pb2.py][ir_pb2_py].
[ir_pb2_py]: public/ir_pb2.py
The back ends read the IR and emit code to view and manipulate Emboss-defined
data structures. Currently, only a C++ back-end exists.
*TODO(bolms): Split the symbol resolution and validation steps in a separate
"middle" component, to allow external code generators to generate undecorated
Emboss IR instead of Emboss source text?*
## Front End
*Implemented in [front_end/...][front_end]*
[front_end]: front_end/
The front end is responsible for reading in Emboss definitions and producing a
normalized intermediate representation (IR). It is divided into several steps:
roughly, parsing, import resolution, symbol resolution, and validation.
The front end is orchestrated by [glue.py][glue_py], which runs each front end
component in the proper order to construct an IR suitable for consumption by the
back end.
[glue_py]: front_end/glue.py
The actual driver program is [emboss_front_end.py][emboss_front_end_py], which
just calls `glue.ParseEmbossFile` and prints the results.
[emboss_front_end_py]: front_end/emboss_front_end.py
### File Parsing
Per-file parsing consumes the text of a single Emboss module, and produces an
"undecorated" IR for the module, containing only syntactic-level information
from the module.
This "undecorated" IR is (almost) a subset of the final IR: later steps will add
information and perform validation, but will rarely remove anything from the IR
before it is emitted.
#### Tokenization
*Implemented in [tokenizer.py][tokenizer_py]*
[tokenizer_py]: front_end/tokenizer.py
The tokenizer is a fairly standard tokenizer, with Indent/Dedent insertion a la
Python. It divides source text into `parse_types.Symbol` objects, suitable for
feeding into the parser.
#### Syntax Tree Generation
*Implemented in [lr1.py][lr1_py] and [parser_generator.py][parser_generator_py], with a façade in [structure_parser.py][structure_parser_py]*
[lr1_py]: front_end/lr1.py
[parser_generator_py]: front_end/parser_generator.py
[structure_parser_py]: front_end/structure_parser.py
Emboss uses a pretty standard Shift-Reduce LR(1) parser. This is implemented in
three parts in Emboss:
* A generic parser generator implementing the table generation algorithms from
*[Compilers: Principles, Techniques, & Tools][dragon_book]* and the
error-marking algorithm from *[Generating LR Syntax Error Messages from
Examples][jeffery_2003]*.
* An Emboss-specific parser builder which glues the Emboss tokenizer, grammar,
and error examples to the parser generator, producing an Emboss parser.
* The Emboss grammar, which is extracted from the file normalizer
(*[module_ir.py][module_ir_py]*).
[dragon_book]: http://www.amazon.com/Compilers-Principles-Techniques-Tools-2nd/dp/0321486811
[jeffery_2003]: http://dl.acm.org/citation.cfm?id=937566
#### Normalization
*Implemented in [module_ir.py][module_ir_py]*
[module_ir_py]: front_end/module_ir.py
Once a parse tree has been generated, it is fed into a normalizer which
recursively turns the raw syntax tree into a "first stage" intermediate
representation (IR). The first stage IR serves to isolate later stages from
minor changes in the grammar, but only contains information from a single file,
and does not perform any semantic checking.
### Import Resolution
*TODO(bolms): Implement imports.*
After each file is parsed, any new imports it has are added to a work queue.
Each file in the work queue is parsed, potentially adding more imports to the
queue, until the queue is empty.
### Symbol Resolution
*Implemented in [symbol_resolver.py][symbol_resolver_py]*
[symbol_resolver_py]: front_end/symbol_resolver.py
Symbol resolution is the process of correlating names in the IR. At the end of
symbol resolution, every named entity (type definition, field definition, enum
name, etc.) has a `CanonicalName`, and every reference in the IR has a
`Reference` to the entity to which it refers.
This assignment occurs in two passes. First, the full IR is scanned, generating
scoped symbol tables (nested dictionaries of names to `CanonicalName`), and
assigning identities to each `Name` in the IR. Then the IR is fully scanned a
second time, and each `Reference` in the IR is resolved: all scopes visible to
the reference are scanned for the name, and the corresponding `CanonicalName` is
assigned to the reference.
### Validation
*TODO(bolms): other validations?*
#### Size Checking
*TODO(bolms): describe*
#### Overlap Checking
*TODO(bolms): describe*
## Back End
*Implemented in [back_end/...][back_end]*
[back_end]: back_end/
Currently, only a C++ back end is implemented.
A back end takes Emboss IR and produces code in a specific language for
manipulating the Emboss-defined data structures.
### C++
*Implemented in [header_generator.py][header_generator_py] with templates in
[generated_code_templates][generated_code_templates], support code in
[emboss_cpp_util.h][emboss_cpp_util_h], and a driver program in
[emboss_codegen_cpp.py][emboss_codegen_cpp_py]*
[header_generator_py]: back_end/cpp/header_generator.py
[generated_code_templates]: back_end/cpp/generated_code_templates
[emboss_cpp_util_h]: back_end/cpp/emboss_cpp_util.h
[emboss_codegen_cpp_py]: back_end/cpp/emboss_codegen_cpp.py
The C++ code generator is currently very minimal. `header_generator.py`
essentially inserts values from the IR into text templates.
*TODO(bolms): add more documentation once the C++ back end has more features.*