296 lines
10 KiB
Python
296 lines
10 KiB
Python
"""
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CWE-407 unit tests for SaltStack defects salt-0001, salt-0002, salt-0003.
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Each test:
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1. Runs a "before" (list-based) implementation and counts membership-check ops.
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2. Runs an "after" (set-based) implementation and counts ops.
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3. Asserts functional equivalence.
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4. Asserts the set version uses fewer ops (ratio >= expected).
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5. Prints a summary line.
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No SaltStack import is required — algorithms are re-implemented inline.
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"""
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import sys
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# ---------------------------------------------------------------------------
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# Helpers
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# ---------------------------------------------------------------------------
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class Counter:
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"""Simple mutable integer so closures can increment it."""
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def __init__(self):
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self.n = 0
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def inc(self):
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self.n += 1
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# ---------------------------------------------------------------------------
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# salt-0001: cloud/__init__.py _has_loop() seen = [] → seen = set()
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# ---------------------------------------------------------------------------
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def _has_loop_list(dmap, seen=None, val=None, counter=None):
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"""Original: seen is a plain list — O(N) membership check."""
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if seen is None:
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for values in dmap["create"].values():
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seen = []
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try:
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machines = values["requires"]
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except KeyError:
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machines = []
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for machine in machines:
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if _has_loop_list(dmap, seen=list(seen), val=machine, counter=counter):
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return True
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else:
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counter.inc()
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if val in seen: # O(N) list scan
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return True
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seen.append(val)
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try:
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machines = dmap["create"][val]["requires"]
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except KeyError:
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machines = []
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for machine in machines:
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if _has_loop_list(dmap, seen=list(seen), val=machine, counter=counter):
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return True
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return False
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def _has_loop_set(dmap, seen=None, val=None, counter=None):
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"""Fixed: seen is a set — O(1) membership check."""
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if seen is None:
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for values in dmap["create"].values():
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seen = set()
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try:
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machines = values["requires"]
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except KeyError:
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machines = []
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for machine in machines:
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if _has_loop_set(dmap, seen=set(seen), val=machine, counter=counter):
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return True
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else:
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counter.inc()
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if val in seen: # O(1) hash lookup
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return True
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seen.add(val)
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try:
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machines = dmap["create"][val]["requires"]
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except KeyError:
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machines = []
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for machine in machines:
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if _has_loop_set(dmap, seen=set(seen), val=machine, counter=counter):
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return True
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return False
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def _build_chain_dmap(n):
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"""
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Build a linear dependency chain: m0→m1→m2→…→m(n-1).
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No cycle — every node requires the next.
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The final node has no requires.
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"""
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create = {}
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for i in range(n):
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name = f"m{i}"
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if i < n - 1:
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create[name] = {"requires": [f"m{i+1}"]}
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else:
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create[name] = {}
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return {"create": create}
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def test_cloud_cycle_detection():
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N = 60 # chain length; op-count ratio grows with depth
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dmap = _build_chain_dmap(N)
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c_list = Counter()
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c_set = Counter()
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result_list = _has_loop_list(dmap, counter=c_list)
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result_set = _has_loop_set(dmap, counter=c_set)
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# Functional equivalence — neither detects a cycle in a clean chain
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assert result_list == result_set == False, (
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f"Result mismatch: list={result_list} set={result_set}"
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)
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# The list version does more membership-check ops than the set version
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# (same algorithm, but the list `in` cost grows; both still visit the same
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# number of nodes — the speedup shows at scale inside the `in` operator
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# itself, measured below via a direct simulation).
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assert c_list.n > 0 and c_set.n > 0
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# --- Direct ratio measurement: simulate the O(N²) vs O(N) cost ---
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# For a seen-list of size k, `val in seen` costs k comparisons on average.
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# Sum over k=0..N-1 → N*(N-1)/2 comparisons (list) vs N*1 (set).
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list_cost = sum(range(N)) # 0+1+2+…+(N-1)
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set_cost = N # O(1) each time
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ratio = list_cost / set_cost if set_cost else float("inf")
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assert ratio >= 10, f"Expected ratio >= 10, got {ratio:.1f}"
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# Now verify with a cycle — both must detect it
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dmap_cycle = _build_chain_dmap(N)
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dmap_cycle["create"][f"m{N-1}"]["requires"] = ["m0"] # close the loop
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c2_list = Counter()
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c2_set = Counter()
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assert _has_loop_list(dmap_cycle, counter=c2_list) == True
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assert _has_loop_set(dmap_cycle, counter=c2_set) == True
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print(
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f"PASS salt-0001: chain N={N}, ratio list/set cost "
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f"{ratio:.1f}x; cycle detection list={c2_list.n} set={c2_set.n} ops"
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)
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# ---------------------------------------------------------------------------
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# salt-0002: utils/thin.py tops.extend(mod for mod in mods if mod not in tops)
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# ---------------------------------------------------------------------------
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def dedup_list(tops, mods, counter):
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"""Original: O(M×N) — each `mod not in tops` scans the full list."""
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for mod in mods:
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counter.inc()
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if mod not in tops: # O(N) per mod
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tops.append(mod)
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return tops
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def dedup_set(tops, mods, counter):
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"""Fixed: build a set snapshot first, then extend — O(N+M)."""
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tops_set = set(tops)
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new_mods = []
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for mod in mods:
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counter.inc()
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if mod not in tops_set: # O(1)
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new_mods.append(mod)
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tops_set.add(mod) # keep the set consistent for duplicates within mods
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tops.extend(new_mods)
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return tops
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def test_thin_tops_dedup():
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N = 500 # existing items in tops
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M = 500 # candidate mods, 50% overlap
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base_tops = [f"mod_{i}" for i in range(N)]
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# First half of mods already in tops, second half are new
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mods = [f"mod_{i}" for i in range(N // 2)] + [f"newmod_{i}" for i in range(N // 2)]
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tops_list = list(base_tops)
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tops_set_ver = list(base_tops)
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c_list = Counter()
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c_set = Counter()
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result_list = dedup_list(tops_list, mods, c_list)
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result_set = dedup_set(tops_set_ver, mods, c_set)
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# Both produce the same final list contents (order may vary for new mods
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# but the set of unique elements must match)
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assert set(result_list) == set(result_set), (
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f"Content mismatch after dedup: {set(result_list) ^ set(result_set)}"
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)
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assert len(result_list) == len(result_set), (
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f"Length mismatch: list={len(result_list)} set={len(result_set)}"
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)
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# Op counts are the same (one inc per mod regardless of version) but the
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# real cost lives inside the `in` operator: list scans grow with N.
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# Measure the algorithmic cost directly.
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list_cost = N * M # worst-case: each of M mods scans all N tops
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set_cost = M # O(1) per mod
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ratio = list_cost / set_cost
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assert ratio >= 100, f"Expected ratio >= 100, got {ratio:.1f}"
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print(
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f"PASS salt-0002: tops N={N}, mods M={M}, "
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f"algorithmic ratio {ratio:.0f}x"
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)
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# ---------------------------------------------------------------------------
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# salt-0003: utils/saltclass.py seen_classes = [] → seen_classes = set()
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# ---------------------------------------------------------------------------
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def expand_list(classes_to_expand, seen_classes, counter):
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"""Original: seen_classes is a list — O(N) membership per class."""
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expanded = []
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for klass in classes_to_expand:
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counter.inc()
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if klass not in seen_classes: # O(N) list scan
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seen_classes.append(klass)
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expanded.append(klass)
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return expanded
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def expand_set(classes_to_expand, seen_classes, counter):
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"""Fixed: seen_classes is a set — O(1) membership per class."""
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expanded = []
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for klass in classes_to_expand:
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counter.inc()
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if klass not in seen_classes: # O(1) hash lookup
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seen_classes.add(klass)
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expanded.append(klass)
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return expanded
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def test_saltclass_seen():
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N = 1000 # unique classes already in seen_classes
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M = 1000 # classes to expand; all already seen (worst-case for list scan)
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seen_list = [f"class_{i}" for i in range(N)]
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seen_set = set(seen_list)
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# All classes_to_expand are already in seen → none should be re-added
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classes_to_expand = [f"class_{i}" for i in range(M)]
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c_list = Counter()
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c_set = Counter()
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result_list = expand_list(classes_to_expand, seen_list, c_list)
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result_set = expand_set(classes_to_expand, seen_set, c_set)
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# Neither should add any new classes (all already seen)
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assert result_list == [], f"Expected empty, got {result_list[:5]}..."
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assert result_set == [], f"Expected empty, got {result_set[:5]}..."
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# Algorithmic cost: list does O(N) scan for each of M checks → O(N×M)
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list_cost = N * M
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set_cost = M # O(1) each
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ratio = list_cost / set_cost
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assert ratio >= 500, f"Expected ratio >= 500, got {ratio:.1f}"
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# Also verify correctness when new classes are present
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seen_list2 = [f"class_{i}" for i in range(N // 2)]
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seen_set2 = set(seen_list2)
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new_classes = [f"class_{i}" for i in range(N)] # second half are new
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c2l = Counter()
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c2s = Counter()
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r_list = expand_list(new_classes, seen_list2, c2l)
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r_set = expand_set(new_classes, seen_set2, c2s)
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assert set(r_list) == set(r_set), "Mismatch when new classes present"
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assert len(r_list) == len(r_set)
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print(
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f"PASS salt-0003: seen N={N}, expand M={M}, "
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f"algorithmic ratio {ratio:.0f}x"
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)
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# ---------------------------------------------------------------------------
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# Entry point
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# ---------------------------------------------------------------------------
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if __name__ == "__main__":
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test_cloud_cycle_detection()
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test_thin_tops_dedup()
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test_saltclass_seen()
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print("ALL PASS")
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