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use std::collections::BTreeMap;
use super::model::{create_cost_model, CostModel, TableCost};
use crate::ast::*;
use crate::field::proof;
// --- Per-function cost result ---
/// Cost analysis result for a single function.
#[derive(Clone, Debug)]
pub struct FunctionCost {
pub name: String,
pub cost: TableCost,
/// If this function contains a loop, per-iteration cost.
pub per_iteration: Option<(TableCost, u64)>,
}
/// Cost analysis result for the full program.
#[derive(Clone, Debug)]
pub struct ProgramCost {
pub program_name: String,
pub functions: Vec<FunctionCost>,
pub total: TableCost,
/// Table names from the CostModel (e.g. ["processor", "hash", ...]).
pub table_names: Vec<String>,
/// Short display names (e.g. ["cc", "hash", ...]).
pub table_short_names: Vec<String>,
/// Program attestation adds ceil(instruction_count / 10) * 6 hash rows.
pub attestation_hash_rows: u64,
pub padded_height: u64,
pub estimated_proving_ns: u64,
/// H0004: loops where declared bound >> actual constant end.
pub loop_bound_waste: Vec<(String, u64, u64)>, // (fn_name, end_value, bound)
}
impl ProgramCost {
/// Short names as str slice refs (for passing to TableCost methods).
pub fn short_names(&self) -> Vec<&str> {
self.table_short_names.iter().map(|s| s.as_str()).collect()
}
/// Long names as str slice refs.
pub fn long_names(&self) -> Vec<&str> {
self.table_names.iter().map(|s| s.as_str()).collect()
}
}
// --- Cost analyzer ---
/// Computes static cost by walking the AST.
///
/// The analyzer is parameterized by a `CostModel` that provides all
/// target-specific cost constants.
pub(crate) struct CostAnalyzer<'a> {
/// Target-specific cost model.
pub(crate) cost_model: &'a dyn CostModel,
/// Function bodies indexed by name (for resolving calls).
pub(crate) fn_bodies: BTreeMap<String, FnDef>,
/// Cached function costs to avoid recomputation.
fn_costs: BTreeMap<String, TableCost>,
/// Recursion guard to prevent infinite loops in cost computation.
in_progress: Vec<String>,
/// H0004: collected loop bound waste entries (fn_name, end_value, bound).
pub(crate) loop_bound_waste: Vec<(String, u64, u64)>,
}
impl Default for CostAnalyzer<'_> {
fn default() -> Self {
Self::for_target("triton")
}
}
impl<'a> CostAnalyzer<'a> {
/// Create an analyzer for the named target.
pub(crate) fn for_target(target_name: &str) -> Self {
Self::with_cost_model(create_cost_model(target_name))
}
/// Create an analyzer with a specific cost model.
pub(crate) fn with_cost_model(cost_model: &'a dyn CostModel) -> Self {
Self {
cost_model,
fn_bodies: BTreeMap::new(),
fn_costs: BTreeMap::new(),
in_progress: Vec::new(),
loop_bound_waste: Vec::new(),
}
}
/// Analyze a complete file and return the program cost.
pub(crate) fn analyze_file(&mut self, file: &File) -> ProgramCost {
// Collect all function definitions.
for item in &file.items {
if let Item::Fn(func) = &item.node {
self.fn_bodies.insert(func.name.node.clone(), func.clone());
}
}
// Compute cost for each function.
let mut functions = Vec::new();
let fn_names: Vec<String> = self.fn_bodies.keys().cloned().collect();
for name in &fn_names {
let func = self
.fn_bodies
.get(name)
.expect("name comes from fn_bodies.keys()")
.clone();
let cost = self.cost_fn(&func);
let per_iteration = self.find_loop_iteration_cost(&func);
functions.push(FunctionCost {
name: name.clone(),
cost,
per_iteration,
});
}
// Total cost: start from main if it exists, otherwise sum all.
let total = if let Some(main_cost) = self.fn_costs.get("main") {
main_cost.add(&self.cost_model.call_overhead()) // call main + halt
} else {
functions
.iter()
.fold(TableCost::ZERO, |acc, f| acc.add(&f.cost))
};
// Estimate program instruction count for attestation.
// Rough heuristic: total first-table value (processor cycles) ≈ instruction count.
let instruction_count = total.get(0).max(10);
let hash_rows = self.cost_model.hash_rows_per_permutation();
let attestation_hash_rows = instruction_count.div_ceil(10) * hash_rows;
// Padded height includes attestation.
let max_height = total.max_height().max(attestation_hash_rows);
let padded_height = proof::padded_height(max_height);
let columns = self.cost_model.trace_column_count();
let estimated_proving_ns = proof::estimate_proving_ns(padded_height, columns);
// H0004: scan for loop bound waste (bound >> constant end)
for item in &file.items {
if let Item::Fn(func) = &item.node {
if let Some(body) = &func.body {
self.scan_loop_bound_waste(&func.name.node, &body.node);
}
}
}
ProgramCost {
program_name: file.name.node.clone(),
functions,
total,
table_names: self
.cost_model
.table_names()
.iter()
.map(|s| s.to_string())
.collect(),
table_short_names: self
.cost_model
.table_short_names()
.iter()
.map(|s| s.to_string())
.collect(),
attestation_hash_rows,
padded_height,
estimated_proving_ns,
loop_bound_waste: std::mem::take(&mut self.loop_bound_waste),
}
}
pub(crate) fn cost_fn(&mut self, func: &FnDef) -> TableCost {
if let Some(cached) = self.fn_costs.get(&func.name.node) {
return *cached;
}
// Recursion guard: if this function is already being analyzed,
// return ZERO to break the cycle.
if self.in_progress.contains(&func.name.node) {
return TableCost::ZERO;
}
let depth_before = self.in_progress.len();
self.in_progress.push(func.name.node.clone());
let cost = if let Some(body) = &func.body {
self.cost_block(&body.node)
} else {
TableCost::ZERO
};
self.in_progress.pop();
// Only cache if we're at the top-level call (no recursion in flight).
// Costs computed during active recursion are underestimates because
// recursive calls are costed as ZERO.
if depth_before == 0 {
self.fn_costs.insert(func.name.node.clone(), cost);
}
cost
}
pub(crate) fn cost_block(&mut self, block: &Block) -> TableCost {
let mut cost = TableCost::ZERO;
for stmt in &block.stmts {
cost = cost.add(&self.cost_stmt(&stmt.node));
}
if let Some(tail) = &block.tail_expr {
cost = cost.add(&self.cost_expr(&tail.node));
}
cost
}
pub(crate) fn cost_stmt(&mut self, stmt: &Stmt) -> TableCost {
let stack_op = self.cost_model.stack_op();
match stmt {
Stmt::Let { init, .. } => {
// Cost of evaluating the init expression + stack placement.
self.cost_expr(&init.node).add(&stack_op)
}
Stmt::Assign { value, .. } => {
// Cost of evaluating value + swap to replace old value.
self.cost_expr(&value.node).add(&stack_op).add(&stack_op)
}
Stmt::TupleAssign { names, value } => {
let mut cost = self.cost_expr(&value.node);
// One swap+pop per element.
for _ in names {
cost = cost.add(&stack_op).add(&stack_op);
}
cost
}
Stmt::If {
cond,
then_block,
else_block,
} => {
let cond_cost = self.cost_expr(&cond.node);
let then_cost = self.cost_block(&then_block.node);
let else_cost = if let Some(eb) = else_block {
self.cost_block(&eb.node)
} else {
TableCost::ZERO
};
// Worst case: max of then/else branches.
cond_cost
.add(&then_cost.max(&else_cost))
.add(&self.cost_model.if_overhead())
}
Stmt::For {
end, bound, body, ..
} => {
let end_cost = self.cost_expr(&end.node);
let body_cost = self.cost_block(&body.node);
// Use declared bound if available, otherwise use end expr as literal.
let iterations = if let Some(b) = bound {
*b
} else if let Expr::Literal(Literal::Integer(n)) = &end.node {
*n
} else {
// Non-constant loop bound with no `bounded` annotation.
// Default to 1 iteration but record as a warning so
// report.rs can flag it via H0004.
self.loop_bound_waste.push((
self.in_progress.last().cloned().unwrap_or_default(),
1, // assumed iterations
0, // no declared bound (0 signals "unknown")
));
1
};
// Per-iteration: body + loop overhead (dup, check, decrement, recurse).
let per_iter = body_cost.add(&self.cost_model.loop_overhead());
end_cost.add(&per_iter.scale(iterations))
}
Stmt::Expr(expr) => self.cost_expr(&expr.node),
Stmt::Return(val) => {
if let Some(v) = val {
self.cost_expr(&v.node)
} else {
TableCost::ZERO
}
}
Stmt::Reveal { fields, .. } => {
// push tag + write_io 1 + (field expr + write_io 1) per field
let io_cost = self.cost_model.builtin_cost("pub_write");
let mut cost = stack_op.clone(); // push tag
cost = cost.add(&io_cost); // write_io 1 for tag
for (_name, val) in fields {
cost = cost.add(&self.cost_expr(&val.node));
cost = cost.add(&io_cost); // write_io 1
}
cost
}
Stmt::Asm { body, .. } => {
// Conservative estimate: count non-empty, non-comment lines as stack ops
let line_count = body
.lines()
.filter(|l| {
let t = l.trim();
!t.is_empty() && !t.starts_with("//")
})
.count() as u64;
stack_op.scale(line_count)
}
Stmt::Match { expr, arms } => {
let scrutinee_cost = self.cost_expr(&expr.node);
// Per arm: dup + push + eq + skiz/call overhead = ~5 rows
let arm_overhead = stack_op.scale(3).add(&self.cost_model.if_overhead());
// All non-wildcard arms need comparison overhead
let num_checked_arms = arms
.iter()
.filter(|a| !matches!(a.pattern.node, MatchPattern::Wildcard))
.count() as u64;
let check_cost = arm_overhead.scale(num_checked_arms);
// Worst-case body: max across all arms
let max_body = arms
.iter()
.map(|a| self.cost_block(&a.body.node))
.fold(TableCost::ZERO, |acc, c| acc.max(&c));
scrutinee_cost.add(&check_cost).add(&max_body)
}
Stmt::Seal { fields, .. } => {
// push tag + field exprs + padding pushes + hash + write_io 5
// Hash rate is 10 (tag + up to 9 fields); excess fields need extra hashes.
let mut cost = stack_op.clone(); // push tag
for (_name, val) in fields {
cost = cost.add(&self.cost_expr(&val.node));
}
let padding = 9usize.saturating_sub(fields.len());
for _ in 0..padding {
cost = cost.add(&stack_op); // push 0 padding
}
// hash (one per 10 elements; extra hashes if >9 fields)
let hash_count = (1 + fields.len()).div_ceil(10);
for _ in 0..hash_count {
cost = cost.add(&self.cost_model.builtin_cost("hash"));
}
// write_io 5
cost = cost.add(&self.cost_model.builtin_cost("pub_write5"));
cost
}
}
}
}