browser-automation wave 2: testcafe-0001 + webdriverio-0002
testcafe-0001: Selector filterNodes (string-filter branch) and expandSelectorResults both dedup via Array.indexOf on growing result arrays. filterNodes: O(N*M) per selector filter. expandSelectorResults: O(N^2 * K^2) worst case when derivatives unique. Fix: Set<Node> keyed by object identity. Bench: 398x at N=2000 filter, 1966x at N=K=150 expand. webdriverio-0002: MSPO aggregator dedups per-test entries via Array.find on growing bucket array. O(N^2) per test bucket, same pattern repeats in unknown-suite merger. Fix: companion Map<bucketKey, Set<selector>> for O(1) dedup. Bench: 493x at N=2000. UNDF IDs: 1290 (testcafe), 1291 (webdriverio-0002). All 17 tests pass.
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16 changed files with 827 additions and 17 deletions
67
defects/webdriverio/bench/bench-webdriverio-0002.py
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67
defects/webdriverio/bench/bench-webdriverio-0002.py
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@ -0,0 +1,67 @@
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#!/usr/bin/env python3
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# bench-webdriverio-0002.py
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# MSPO aggregator: .find(d => d.selector === data.selector) on growing bucket
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# array per entry (O(N^2)) vs Set<string> of observed selectors (O(N)).
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import sys
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import time
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def bench_defective(n, unique_frac=1.0):
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"""Array.find on growing bucket per entry."""
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# Generate N entries; unique_frac of them have unique selectors
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unique_count = int(n * unique_frac)
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entries = [{"selector": f"sel-{i}", "timestamp": i} for i in range(unique_count)]
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# Fill remaining with dup of last
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entries += [{"selector": entries[-1]["selector"], "timestamp": i} for i in range(unique_count, n)]
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t0 = time.perf_counter()
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bucket = []
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for data in entries:
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existing = None
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for d in bucket:
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if d["selector"] == data["selector"]:
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existing = d
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break
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if existing is None:
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bucket.append(data)
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return time.perf_counter() - t0
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def bench_fixed(n, unique_frac=1.0):
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"""Set<string> of observed selectors."""
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unique_count = int(n * unique_frac)
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entries = [{"selector": f"sel-{i}", "timestamp": i} for i in range(unique_count)]
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entries += [{"selector": entries[-1]["selector"], "timestamp": i} for i in range(unique_count, n)]
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t0 = time.perf_counter()
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bucket = []
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seen = set()
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for data in entries:
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if data["selector"] not in seen:
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seen.add(data["selector"])
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bucket.append(data)
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return time.perf_counter() - t0
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TRIALS = 3
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SIZES = [50, 200, 500, 1000, 2000]
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def run():
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lines = []
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header = "=== webdriverio-0002: MSPO aggregator Array.find vs Set<string> ==="
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print(header); lines.append(header)
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for n in SIZES:
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d = min(bench_defective(n) for _ in range(TRIALS))
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f = min(bench_fixed(n) for _ in range(TRIALS))
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speedup = (d / f) if f > 0 else float("inf")
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line = f"N={n:<5}: defective={d*1000:.3f}ms fixed={f*1000:.3f}ms speedup={speedup:.1f}x"
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print(line); lines.append(line); sys.stdout.flush()
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return lines
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if __name__ == "__main__":
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run()
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@ -1,7 +1,14 @@
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=== webdriverio-0001: xpath-conditions Array.find+includes vs Map<attr,Set> ===
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K=5 V=5 : defective=0.045ms fixed=0.032ms speedup=1.4x
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K=10 V=10 : defective=0.135ms fixed=0.082ms speedup=1.7x
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K=20 V=20 : defective=0.993ms fixed=0.197ms speedup=5.0x
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K=40 V=40 : defective=3.876ms fixed=0.807ms speedup=4.8x
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K=60 V=60 : defective=15.792ms fixed=2.611ms speedup=6.0x
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K=5 V=5 : defective=0.019ms fixed=0.014ms speedup=1.4x
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K=10 V=10 : defective=0.093ms fixed=0.050ms speedup=1.8x
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K=20 V=20 : defective=0.502ms fixed=0.202ms speedup=2.5x
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K=40 V=40 : defective=3.297ms fixed=0.773ms speedup=4.3x
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K=60 V=60 : defective=11.879ms fixed=1.950ms speedup=6.1x
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=== webdriverio-0002: MSPO aggregator Array.find vs Set<string> ===
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N=50 : defective=0.062ms fixed=0.006ms speedup=10.4x
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N=200 : defective=0.921ms fixed=0.023ms speedup=40.4x
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N=500 : defective=6.883ms fixed=0.063ms speedup=109.8x
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N=1000 : defective=32.553ms fixed=0.116ms speedup=280.4x
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N=2000 : defective=121.602ms fixed=0.247ms speedup=493.0x
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@ -18,7 +18,7 @@ def load_module(filename):
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all_lines = []
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for fname in ["bench-webdriverio-0001.py"]:
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for fname in ["bench-webdriverio-0001.py", "bench-webdriverio-0002.py"]:
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mod = load_module(fname)
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lines = mod.run()
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all_lines.extend(lines)
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@ -0,0 +1,64 @@
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# UNDF: UNDF-2026-000001291
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# UNDF: UNDF-2026-XXXXXXXXX
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# CWE-407: Algorithmic Complexity -- O(N^2) -> O(N) in MSPO aggregator dedup
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#
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# Defect: aggregator dedup runs .find(d => d.selector === data.selector) on
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# grouped[specFile][suiteName][testName] for every collected entry. N
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# entries per test bucket gives O(N^2). Same pattern repeats at line 369
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# in the unknown-suite merger.
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#
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# Fix: Carry a Set<string> of observed selectors per test bucket; the existing
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# array remains for output order and downstream consumers. Per-entry cost
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# drops from O(N) to O(1). For the unknown-suite merger, pre-build the Set
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# from the destination bucket once per merger pass.
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#
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# Complexity gate (tests/test-webdriverio-cwe407.py):
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# k-scaling 5x: time ratio must be <17.5x (O(k) ~=5x, not O(k^2) ~=25x)
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# N=1000 per test bucket: must complete in <5ms
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--- a/packages/wdio-appium-service/src/mobileSelectorPerformanceOptimizer/aggregator.ts
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+++ b/packages/wdio-appium-service/src/mobileSelectorPerformanceOptimizer/aggregator.ts
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@@ -330,6 +330,11 @@ export function aggregateSelectorData(
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const grouped: GroupedData = {}
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+ // Companion Map<specFile::suiteName::testName, Set<selector>> gives O(1)
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+ // dedup per entry; prior impl scanned the data array via .find per entry,
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+ // giving O(N^2) per test bucket.
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+ const seenByBucket = new Map<string, Set<string>>()
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+
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for (const data of collectedData) {
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const { specFile, suiteName, testName } = data
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@@ -340,10 +345,13 @@ export function aggregateSelectorData(
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grouped[specFile][suiteName][testName] = []
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}
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- const existing = grouped[specFile][suiteName][testName].find(d => d.selector === data.selector)
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-
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- if (!existing) {
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+ const bucketKey = `${specFile}::${suiteName}::${testName}`
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+ let seen = seenByBucket.get(bucketKey)
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+ if (!seen) {
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+ seen = new Set<string>()
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+ seenByBucket.set(bucketKey, seen)
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+ }
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+ if (!seen.has(data.selector)) {
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+ seen.add(data.selector)
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grouped[specFile][suiteName][testName].push(data)
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}
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}
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@@ -365,9 +373,12 @@ export function aggregateSelectorData(
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suites[knownSuiteName][testName] = []
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}
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+ // Pre-build a Set from the destination bucket once per
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+ // merger pass so the inner loop does O(1) dedup instead
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+ // of .find across the growing destination array.
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+ const destSeen = new Set(suites[knownSuiteName][testName].map(d => d.selector))
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for (const data of unknownSuite[testName]) {
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- const existing = suites[knownSuiteName][testName].find(d => d.selector === data.selector)
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- if (!existing) {
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+ if (!destSeen.has(data.selector)) {
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+ destSeen.add(data.selector)
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data.suiteName = knownSuiteName
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suites[knownSuiteName][testName].push(data)
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}
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#!/usr/bin/env python3
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# UNDF: UNDF-2026-000001289 (webdriverio-0001)
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# UNDF: UNDF-2026-000001289 (webdriverio-0001), UNDF-2026-000001291 (webdriverio-0002)
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#
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# CWE-407: Algorithmic Complexity
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#
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# Defect:
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# Defects:
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# webdriverio-0001: extractOrConditions scans orMatches array via .find and
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# .includes per regex match, giving O(M*K + M*V) across M
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# matches with K attrs and V values per attr.
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# webdriverio-0002: MSPO aggregator dedups each entry against growing
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# bucket array via Array.find, O(N^2) per test bucket.
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#
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# Fix:
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# Replace the array-of-objects + .find + .includes pattern with
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# Map<string, Set<string>>. Per-match cost becomes amortized O(1).
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# Fixes:
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# webdriverio-0001: Map<string, Set<string>>. Per-match cost amortized O(1).
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# webdriverio-0002: Companion Set<string> of observed selectors per bucket.
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# Per-entry cost drops from O(N) to O(1).
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#
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# Complexity gate (from bench/results.txt on this machine):
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# K=V=60 defective=15.8ms, fixed=2.6ms.
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# Fixed must complete in <5ms at K=V=40. k-scaling <17.5x.
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# Complexity gates (from bench/results.txt on this machine):
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# webdriverio-0001 K=V=60 defective=15.8ms, fixed=2.6ms.
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# Fixed must complete in <5ms at K=V=40. k-scaling <17.5x.
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# webdriverio-0002 N=2000 defective=121.6ms, fixed=0.25ms.
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# Fixed must complete in <5ms at N=1000. k-scaling <17.5x.
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import importlib.util
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import os
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@ -35,6 +40,7 @@ def _load(fname):
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_mod = _load("bench-webdriverio-0001.py")
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_mod_0002 = _load("bench-webdriverio-0002.py")
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# ---------------------------------------------------------------------------
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f"fixed K=40/K=10 ratio {ratio:.2f}x, expected <64x (sub-quadratic)")
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# ---------------------------------------------------------------------------
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# webdriverio-0002: MSPO aggregator Set-based dedup
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# ---------------------------------------------------------------------------
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def _dedup_defective(entries):
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bucket = []
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for data in entries:
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existing = None
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for d in bucket:
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if d["selector"] == data["selector"]:
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existing = d
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break
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if existing is None:
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bucket.append(data)
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return bucket
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def _dedup_fixed(entries):
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bucket = []
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seen = set()
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for data in entries:
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if data["selector"] not in seen:
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seen.add(data["selector"])
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bucket.append(data)
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return bucket
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class TestWebdriverio0002Correctness(unittest.TestCase):
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def test_empty(self):
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self.assertEqual(_dedup_fixed([]), _dedup_defective([]))
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def test_all_unique(self):
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entries = [{"selector": f"s{i}", "timestamp": i} for i in range(5)]
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self.assertEqual(_dedup_fixed(entries), _dedup_defective(entries))
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def test_all_duplicate(self):
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entries = [{"selector": "s0", "timestamp": i} for i in range(5)]
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# Defective keeps only first, fixed same
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self.assertEqual(
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[x["timestamp"] for x in _dedup_fixed(entries)],
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[x["timestamp"] for x in _dedup_defective(entries)])
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def test_mixed_preserves_first_seen(self):
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entries = [
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{"selector": "a", "timestamp": 1},
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{"selector": "b", "timestamp": 2},
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{"selector": "a", "timestamp": 3},
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{"selector": "c", "timestamp": 4},
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{"selector": "b", "timestamp": 5},
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]
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self.assertEqual(_dedup_fixed(entries), _dedup_defective(entries))
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class TestWebdriverio0002ComplexityGate(unittest.TestCase):
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def test_fixed_wallclock_N1000(self):
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t_s = min(_mod_0002.bench_fixed(1000) for _ in range(3))
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self.assertLess(t_s * 1000, 5.0,
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f"fixed took {t_s*1000:.3f}ms at N=1000, expected <5ms")
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def test_fixed_scaling_linear(self):
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t_200 = min(_mod_0002.bench_fixed(200) for _ in range(3))
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t_1000 = min(_mod_0002.bench_fixed(1000) for _ in range(3))
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ratio = t_1000 / t_200 if t_200 > 0 else float("inf")
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self.assertLess(ratio, 17.5,
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f"fixed N=1000/N=200 ratio {ratio:.2f}x, expected <17.5x (O(N))")
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if __name__ == "__main__":
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unittest.main(verbosity=2)
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