cobol-java-v3/cobol_testgen/design_mcdc.py

"""Non-exploding path enumeration — per-decision-point coverage, O(N) paths.

Strategy:
  1. Walk the tree once to collect ALL decision points and their "access paths"
  2. For each decision point D, generate 2 paths:
     - D=True with ancestor and descendant access constraints
     - D=False with ancestor and descendant access constraints
  3. Total: 2 * N paths, where N = number of decision points

This guarantees every branch is exercised at least once, without O(2^N) explosion.
"""

import re
import logging
from .models import BrSeq, BrIf, BrEval, BrPerform, BrSearch, Assign, CallNode, CondNot, CondLeaf, ExitNode, GoTo
from .cond import parse_single_condition, parse_compound_condition, is_field, collect_leaves, mcdc_sets

logger = logging.getLogger(__name__)

_STOP = ('__STOP__', '', None, True)


def _parse_condition(condition_text, fields):
    """Parse an IF condition into (field, op, value) or None."""
    parsed = parse_single_condition(condition_text, fields)
    if parsed and is_field(parsed[0], fields):
        return parsed
    if parsed:
        return parsed
    return None


def _invert_condition(parsed):
    """Invert a parsed condition (True ↔ False)."""
    if parsed is None:
        return None
    field, op, val = parsed
    inv_op = {'=': '<>', '<>': '=', '>': '<=', '<': '>=', '>=': '<', '<=': '>'}.get(op, op)
    return (field, inv_op, val)


# ── Collect all decision points with access paths ──

def _collect_all_dps(node, fields, path_cons=None, path_assign=None, depth=0):
    """Walk tree, collect list of (decision_point, access_path) tuples.

    Returns list of dicts:
      { "node": decision_point_node,
        "kind": "IF"|"EVALUATE"|"PERFORM"|"SEARCH"|"AT_END",
        "access_constraints": [constraints to reach this point],
        "branches": list of (branch_label, body_node_children)
        "true_idx": index of "True" branch in branches,
        "false_idx": index of "False" branch (or None),
      }
    """
    path_cons = list(path_cons or [])
    path_assign = dict(path_assign or {})
    result = []

    if isinstance(node, BrIf):
        parsed = _parse_condition(node.condition, fields)
        dp = {
            "node": node, "kind": "IF",
            "condition": node.condition,
            "parsed": parsed,
            "access_constraints": list(path_cons),
            "true_idx": 0,
            "false_idx": 1 if parsed else None,
        }
        result.append(dp)

        # Recurse into both branches
        t_cons = list(path_cons)
        f_cons = list(path_cons)
        if parsed:
            field, op, val = parsed
            t_cons.append((field, op, val, True))
            f_cons.append((field, op, val, False))
        result.extend(_collect_all_dps(node.true_seq, fields, t_cons, path_assign, depth + 1))
        result.extend(_collect_all_dps(node.false_seq, fields, f_cons, path_assign, depth + 1))

    elif isinstance(node, BrEval):
        dp = {
            "node": node, "kind": "EVALUATE",
            "subject": node.subject,
            "access_constraints": list(path_cons),
        }
        result.append(dp)
        for value, seq in node.when_list:
            w_cons = list(path_cons)
            if is_field(node.subject, fields):
                w_cons.append((node.subject, '=', value, True))
            result.extend(_collect_all_dps(seq, fields, w_cons, path_assign, depth + 1))
        if node.has_other:
            result.extend(_collect_all_dps(node.other_seq, fields, list(path_cons), path_assign, depth + 1))

    elif isinstance(node, BrPerform):
        if node.perf_type in ('until', 'para_until', 'varying', 'para_varying'):
            parsed = _parse_condition(node.condition, fields)
            dp = {
                "node": node, "kind": "PERFORM",
                "condition": node.condition,
                "parsed": parsed,
                "access_constraints": list(path_cons),
            }
            result.append(dp)
            if parsed:
                field, op, val = parsed
                body_cons = list(path_cons) + [(field, op, val, False)]
            else:
                body_cons = list(path_cons)
            result.extend(_collect_all_dps(node.body_seq, fields, body_cons, path_assign, depth + 1))
        else:
            result.extend(_collect_all_dps(node.body_seq, fields, list(path_cons), path_assign, depth + 1))

    elif isinstance(node, BrSeq):
        for child in node.children:
            result.extend(_collect_all_dps(child, fields, path_cons, path_assign, depth))

    elif isinstance(node, BrSearch):
        dp = {
            "node": node, "kind": "SEARCH",
            "access_constraints": list(path_cons),
        }
        result.append(dp)
        result.extend(_collect_all_dps(node.at_end_seq, fields, list(path_cons), path_assign, depth + 1))
        for _, seq in node.when_list:
            result.extend(_collect_all_dps(seq, fields, list(path_cons), path_assign, depth + 1))

    return result


def _make_path_for_branch(dp, branch_idx, fields):
    """Create a single path (constraints, assignments) for one branch of a decision point."""
    constraints = list(dp.get("access_constraints", []))

    kind = dp["kind"]

    if kind == "IF":
        parsed = dp.get("parsed")
        if parsed is None:
            return ([], {})
        field, op, val = parsed
        want_true = (branch_idx == dp.get("true_idx", 0))
        if not want_true:
            field2, op2, val2 = _invert_condition(parsed)
            field, op, val = field2, op2, val2
        constraints.append((field, op, val, True))
        # Pick body, just take first assignment
        node = dp["node"]
        body_seq = node.true_seq if branch_idx == 0 else node.false_seq
        return (constraints, {})

    if kind == "EVALUATE":
        node = dp["node"]
        n_when = len(node.when_list)
        if branch_idx < n_when:
            value, seq = node.when_list[branch_idx]
            if is_field(node.subject, []):
                constraints.append((node.subject, '=', value, True))
            prior_cases = [v for v, _ in node.when_list[:branch_idx]]
            for prior in prior_cases:
                constraints.append((node.subject, '<>', prior, True))
        return (constraints, {})

    if kind == "PERFORM":
        parsed = dp.get("parsed")
        if parsed is None:
            return ([], {})
        field, op, val = parsed
        if branch_idx == 0:
            constraints.append((field, op, val, False))
        else:
            constraints.append((field, op, val, True))
        return (constraints, {})

    return ([], {})


# ── Public API ──

def enum_paths(node, fields):
    """Linear path enumeration: one True + one False per decision point.

    Returns list of (constraints, assignments) tuples.
    Total paths = 2 * number_of_decision_points (capped at 1000).
    """
    all_dps = _collect_all_dps(node, fields)

    MAX_PATH = 1000
    paths = []

    # Start with one neutral path (no constraints)
    paths.append(([], {}))

    for dp in all_dps:
        kind = dp["kind"]

        if kind == "IF":
            true_path = _make_path_for_branch(dp, dp.get("true_idx", 0), fields)
            false_path = _make_path_for_branch(dp, dp.get("false_idx", 1) if dp.get("false_idx") is not None else dp.get("true_idx", 0), fields)
            if true_path:
                paths.append(true_path)
            if false_path:
                paths.append(false_path)

        elif kind == "EVALUATE":
            node = dp["node"]
            for i in range(len(node.when_list)):
                bp = _make_path_for_branch(dp, i, fields)
                if bp: paths.append(bp)
            if node.has_other:
                other_cons = list(dp.get("access_constraints", []))
                for v, _ in node.when_list:
                    if is_field(node.subject, []):
                        other_cons.append((node.subject, '<>', v, True))
                paths.append((other_cons, {}))

        elif kind == "PERFORM":
            enter_path = _make_path_for_branch(dp, 0, fields)
            skip_path = _make_path_for_branch(dp, 1, fields)
            if enter_path: paths.append(enter_path)
            if skip_path: paths.append(skip_path)

        if len(paths) >= MAX_PATH:
            paths = paths[:MAX_PATH]
            break

    return paths


def _filter_stop(cons):
    return [c for c in cons if c is not _STOP]