perf(dataflow): solve each function once instead of three times

codeanalyzer/dataflow/builder.py

@@ -428,8 +428,13 @@ def build_program_graphs(
             for t in cs.targets:
                 call_edges.append((sig, t))
 
-    summaries = compute_summaries(infos, sorted(set(call_edges)))
-    return assemble_sdg(infos, summaries, k)
+    # The converged (facts, ddg) per function are threaded straight into the
+    # assembler rather than re-derived there (#155).
+    solutions: Dict[str, object] = {}
+    summaries = compute_summaries(
+        infos, sorted(set(call_edges)), solutions=solutions
+    )
+    return assemble_sdg(infos, summaries, k, solutions=solutions)
 
 
 def emit_l4(

codeanalyzer/dataflow/sdg.py

@@ -386,8 +386,18 @@ def assemble_sdg(
     infos: Dict[str, FunctionInfo],
     summaries: Dict[str, FunctionSummary],
     k: int,
+    *,
+    solutions: Optional[Dict[str, Tuple[Dict[int, object], List[object]]]] = None,
 ) -> ProgramGraphsIR:
-    """Stitch every function's PDG into the whole-program SDG."""
+    """Stitch every function's PDG into the whole-program SDG.
+
+    *solutions* optionally carries the converged ``(facts, ddg)`` that
+    :func:`~codeanalyzer.dataflow.summaries.compute_summaries` already
+    derived, sparing a second identical solve per function (#155). Omit it and
+    every function is re-solved, which is the historical behaviour and the
+    right posture whenever *summaries* did not come from an immediately
+    preceding run over these same *infos*.
+    """
     ir = ProgramGraphsIR(k_limit=k)
 
     # Pass 1: solve each function against the final summaries and lay out its
@@ -396,7 +406,12 @@ def assemble_sdg(
     formal_ids: Dict[str, Dict[str, int]] = {}
     for sig in sorted(infos):
         info = infos[sig]
-        summary, facts, ddg = solve_function(info, summaries)
+        cached = solutions.get(sig) if solutions is not None else None
+        if cached is None:
+            summary, facts, ddg = solve_function(info, summaries)
+        else:
+            facts, ddg = cached
+            summary = summaries[sig]
         asm = _FunctionAssembler(info, summary, facts, ddg)
         asm.build_formals()
         assemblers[sig] = asm

codeanalyzer/dataflow/summaries.py

@@ -199,19 +199,42 @@ def reach(start: Set[int]) -> Set[int]:
 def compute_summaries(
     infos: Dict[str, FunctionInfo],
     call_edges: List[Tuple[str, str]],
+    *,
+    solutions: Optional[Dict[str, Tuple[Dict[int, object], List[DDGEdge]]]] = None,
 ) -> Dict[str, FunctionSummary]:
     """Bottom-up composition over the SCC condensation DAG, monotone fixpoint
-    within each SCC."""
+    within each SCC.
+
+    A **singleton SCC with no self-edge** is solved exactly once: the
+    condensation is processed bottom-up, so every callee summary it reads is
+    already final and a second pass could only recompute the same answer to
+    observe that nothing changed. Genuinely recursive SCCs (several members,
+    or one member calling itself) still iterate to fixpoint.
+
+    When *solutions* is supplied it receives each signature's converged
+    ``(facts, ddg)`` — the by-products of the final solve, which
+    :func:`~codeanalyzer.dataflow.sdg.assemble_sdg` would otherwise recompute
+    from scratch. They are the same values that a fresh solve against the
+    final summaries produces, because a converged pass is by definition one
+    in which no member's summary changed (#155).
+    """
     order = strongly_connected_components(sorted(infos), call_edges)
+    self_calls = {src for src, dst in call_edges if src == dst}
     summaries: Dict[str, FunctionSummary] = {}
     for scc in order:
         members = [s for s in scc if s in infos]
-        changed = True
-        while changed:
+        if not members:
+            continue
+        recursive = len(members) > 1 or members[0] in self_calls
+        while True:
             changed = False
             for sig in members:
-                new, _, _ = solve_function(infos[sig], summaries)
+                new, facts, ddg = solve_function(infos[sig], summaries)
+                if solutions is not None:
+                    solutions[sig] = (facts, ddg)
                 if summaries.get(sig) != new:
                     summaries[sig] = new
                     changed = True
+            if not (recursive and changed):
+                break
     return summaries