russell@unturf.com
b79fddfb51
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.
64 lines
3.1 KiB
Diff
64 lines
3.1 KiB
Diff
# 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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