COMP2021-1D

Name	UP Number	Grade	Percentage
Davide António Ferreira Castro	201806512	18	26%
Diogo Guimarães do Rosário	201806582	18	22%
Henrique Melo Ribeiro	201806529	18	26%
Tiago Duarte da Silva	201806516	18	26%

GLOBAL Grade of the project: 18

SUMMARY:

Our tool allows the compilation of Java-- files into a jasmin file compatible with other Java bytecode.

To run our project, we first need to create a jar file of it.
After that, we run one of the following the commands:

• java Main [-r=<num>] [-o] <input_file.jmm>
• java -jar COMP2021-1D.jar [-r=<num>] [-o] <input_file.jmm>

We start by making a syntactic analysis of the provided file to check if it respects our grammar.
During this phase, any error made in a while expression, when declaring variables, assigning variables and calling methods are reported with an error message.

The second phase is a semantic analysis. This checks if what is written in the file makes sense and is consistent.
Here we report mismatches of variable assignments, returns values and many other things. We also try to "clean" up the code a bit by, for example, deleting variables that are not being used anywhere. We also do some optimizations in this phase such as constant propagation and folding, making the code more efficient.

The third phase is generation of OLLIR code.
This is the code that makes the transition to jasmin code easier. Here we also do some optimizations, for example, using while templates that require one less goto instruction.

The last phase is the jasmin code generation phase.
In this phase, after parsing our OLLIR code with the OLLIR tool, we use its output to generate the jasmin code. We do this by selecting JVM instructions in jasmin format for each OLLIR method and their instructions so it can be translated into Java bytecode classes using the jasmin tool.

Main features

• Method overloading
• Good error recovery
• Descriptive error reports
• Constant propagation & folding
• Removal of unused variables (after all other optimizations)
• Initialization of uninitialized variables

DEALING WITH SYNTACTIC ERRORS:

Whenever the compiler detects a syntactic error, it attempts to recover, in order to find further errors in the code.
This error recovery was implemented in the statements (imports, var declarations, assignments, method calls, etc) and while loops.
These errors are added to a list called reports and later shown to the user.

These errors are detected inside a try statement and dealt with inside the catchstatement.
To deal with these errors we created a error_skipto function that receives as a parameter a token value, and skips all tokens until it reaches the one received as parameter.

SEMANTIC ANALYSIS:

The following semantic rules implemented by our tool.

Errors:

• Undefined/Undeclared variables, methods and identifiers
• Bad method arguments
• Array size or index not int
• Call of length on non array
• Duplicate method or field declarations
• Type mismatches
• Incompatible operations
• Invalid Types (takes imports into consideration)
• Method calls on literal types (int, boolean)
• Instantiation of literal types using new
• Invalid use of this inside static Main
• Conflicting method signatures
• Return type mismatch

Warnings:

• Uninitialized variables
• Unused variables

CODE GENERATION:

Ollir

Using the AST created during the semantic phase we create a string containing all OLLIR code needed to generate the JVM code.
Here we use a post order visitor, starting by generating the necessary code for the inner instructions. This way, we can create auxiliary variables with ease, without having to iterate through all the children of the current node.

It's also during this phase that we make optimizations to while expressions. This optimization consists of removing one unnecessary goto instruction from each loop, making our final jasmin code more optimized.

In our implementation, in order to facilitate the creation of JVM code, we considered every if statement to be an if not statement instead.

Jasmin

Taking the previously generated OLLIR code, parsed using the provided OLLIR tool, we take its output (ClassUnit object - ollirClass), using it to generate the JVM code in jasmin format. We make use of the variable table containing both all the registers and the list of instructions of each method to select the corresponding JVM instructions.

Lower cost instructions are selected in multiple cases, such as iinc instructions on variable increments (i = i + 1) instead of iadd and isub, the use of if\<cond\> on comparisons with 0 and also the different constant loading instructions (iconst_m1, iconst_n, bipush n, sipush n, ldc), depending on the constant value.

We also use the variable tables given by the OLLIR tool to calculate the local variable limit for each method and, throughout the generation of each method, a required stack size is calculated for each instruction, and the maximum size in a method is selected as the stack limit.

As an extra optimization to stack size and operations, some operations are replaced by their results in the generation. When generating LTH operations with both operands being literals the result is pushed into the stack, for example, a = 1 < 2 will result in iconst_1; istore_1 (assuming 1 is the register of 'a'). This is also applied to ANDB operations (cases when at least one of the operands is a False literal or both are True literals) and NOTB operations.

TASK DISTRIBUTION:

Task	Members responsible
Parser	Henrique, Diogo
Semantic	Tiago
Ollir	Henrique, Davide
Jasmin	Davide
Optimization	Tiago, Henrique
Tests	Tiago, Henrique, Diogo

PROS:

• Method calls can be called anywhere
  • Due to the lack of knowledge of external method's signatures, we only support external calls made inside internal (own class) calls
  • If the return type is known by the user, attributing the method call to a variable will make the call successful
• Method overloading with method resolution
  • Finds the closest match to the parameters and uses it if there are not conflicting signatures
  • Useful when combined with external method calls whose return type is unknown
• Good error recovery
• Descriptive error & warning reports
• Constant propagation & folding
• Removal of unused variables (after all other optimizations)
• Initialization of uninitialized variables
• Use of optimized jasmin instructions

CONS:

• No register allocation
• Some errors bypass our error recovery
  • a = 2; = 3; would stop the syntactic analysis
• Multiple useless consecutive attributions will not be removed if the variable being attributed is used elsewhere
• Does not fold constant sub-expressions such as (1 + 2) * a to 3 * a