P16 — AIEP — Deterministic Temporal Evidence Gap Detection
Publication Date: 2026-02-26 Status: Open Source Prior Art Disclosure Licence: Apache License 2.0 Author/Organisation: Phatfella Ltd Schema: AIEP_OS_SPEC_TEMPLATE v1.0.1 — https://aiep.dev/schemas/aiep-os-spec-template/v1.0.1
Field of the Invention
[0001] The disclosure relates to deterministic time-series integrity verification within computing systems.
[0002] More particularly, the disclosure concerns a deterministic mechanism for detecting temporal discontinuities, omissions, and ordering anomalies in evidence sets indexed by time, and for suppressing downstream execution when completeness constraints are not satisfied.
Framework Context
[0003] This invention operates within an Architected Instruction and Evidence Protocol (AIEP) environment as defined in United Kingdom patent application number GB2519711.2, filed 20 November 2025, the entire contents of which are incorporated herein by reference.
[0004] The present invention extends deterministic canonicalisation, governance, and execution integrity mechanisms defined in the AIEP environment while remaining independently implementable as described herein.
Background
[0005] Many evidence systems rely on time-ordered records including logs, telemetry streams, financial transactions, sensor data, and compliance records.
[0006] Missing intervals, duplicate timestamps, time zone inconsistencies, and non-deterministic ordering may compromise audit integrity and downstream processing correctness.
[0007] Conventional systems often detect temporal gaps heuristically or through visual inspection, without formalised deterministic rules bound to versioned schema definitions.
[0008] In distributed environments, inconsistent time normalisation logic or ordering rules may lead to divergent interpretations of timeline completeness across nodes.
[0009] Existing systems do not provide:
(a) deterministic construction of a reproducible timeline index from canonicalised time-indexed records; (b) version-bound gap rule evaluation producing verifiable gap artefacts; (c) fail-closed suppression of downstream execution when completeness constraints are violated; (d) deterministic replay of gap determinations independent of current system time; or (e) cross-node equivalence of timeline completeness outcomes under identical inputs and profiles.
[0010] There exists a need for a deterministic temporal gap detection mechanism that constructs reproducible timeline indices, applies version-bound gap rules, generates verifiable gap artefacts, and gates downstream execution on deterministic completeness verification.
Summary of the Disclosure
[0011] A computer-implemented deterministic temporal verification method is executed by one or more processors.
[0012] A set of time-indexed evidence records is received.
[0013] Each record is canonicalised and its time value normalised to a TimeIndex value under a version-bound TimeNormalisationProfile.
[0014] A TimelineIndex is constructed by deterministically ordering records according to:
(a) primary key: TimeIndex; (b) secondary key: CanonicalHash of the record; and (c) tertiary key: a stable deterministic tie-break rule declared in the TimeNormalisationProfile.
[0015] GapRules are retrieved from a version-bound GapRuleProfile.
[0016] Adjacent ordered records in the TimelineIndex are evaluated against the GapRules.
[0017] If the difference between successive TimeIndex values exceeds a permitted threshold, a GapArtefact is generated and appended to an immutable store.
[0018] If a downstream operation requires timeline completeness and a disallowed GapArtefact exists, execution is suppressed in a fail-closed manner.
[0019] The technical effect is modification of computing system behaviour by enforcing deterministic time-continuity validation prior to execution of dependent processes, thereby preventing downstream processing on incomplete or inconsistent evidence timelines.
Brief Description of the Drawings
[0020] Figure 1 illustrates the deterministic timeline construction pipeline from evidence record ingestion through time normalisation, canonical hashing, and deterministic sorting to TimelineIndex output.
[0021] Figure 2 illustrates the gap evaluation logic applied to adjacent records in the TimelineIndex, including GapArtefact generation upon threshold breach.
[0022] Figure 3 illustrates the fail-closed completeness gate applied prior to any downstream operation requiring timeline completeness.
[0023] Figure 4 illustrates deterministic replay equivalence across distributed nodes operating with identical evidence sets and profile identifiers.
ASCII Drawings
Figure 1 — Deterministic Timeline Construction Pipeline
+---------------------------+
| Evidence Records |
| (time-indexed, raw) |
+------------+--------------+
|
v
+------------+--------------+
| Time Normalisation |
| (TimeNormalisationProfile|
| Version-Bound) |
+------------+--------------+
|
v
+------------+--------------+
| CanonicalHash |
| per Record |
+------------+--------------+
|
v
+------------+--------------+
| Deterministic Sort |
| (1) TimeIndex |
| (2) CanonicalHash |
| (3) Tie-break Rule |
+------------+--------------+
|
v
+------------+--------------+
| TimelineIndex |
| (ordered, immutable) |
+---------------------------+
Figure 2 — Gap Evaluation Logic
TimelineIndex[i] TimelineIndex[i+1]
| |
v v
TimeIndex_i TimeIndex_j
Delta = TimeIndex_j - TimeIndex_i
+----------+----------+
| Delta > Threshold? |
+----------+----------+
|
+--------+--------+
Yes No
| |
v v
+---------------+ +------------+
| Generate | | Continue |
| GapArtefact | | Evaluation |
| | +------------+
| - Pre-gap ID |
| - Post-gap ID |
| - Delta value |
| - GapRuleProfile ID |
| - Timestamp (data) |
+---------------+
|
v
+---------------+
| Append to |
| Immutable |
| Store |
+---------------+
Figure 3 — Fail-Closed Completeness Gate
+---------------------------+
| Downstream Operation |
+------------+--------------+
|
v
+------------+--------------+
| Completeness Verification|
| - GapArtefacts present? |
| - Disallowed under |
| GapRuleProfile? |
+------------+--------------+
|
+------+------+
Gaps No Gaps
Present Present
| |
v v
+-----------+ +--------------+
| SUPPRESS | | Execute |
| Execution | | Operation |
| Fail- | +--------------+
| Closed |
| |
| Append |
| Rejection |
| Record |
+-----------+
Figure 4 — Deterministic Replay Across Distributed Nodes
Node A Node B
+--------------------+ +--------------------+
| Evidence Records | | Evidence Records |
| (identical) | | (identical) |
+---------+----------+ +---------+----------+
| |
v v
+---------+----------+ +---------+----------+
| TimeNormalisation | | TimeNormalisation |
| Profile (identical)| | Profile (identical)|
+---------+----------+ +---------+----------+
| |
v v
+---------+----------+ +---------+----------+
| GapRuleProfile | | GapRuleProfile |
| (identical) | | (identical) |
+---------+----------+ +---------+----------+
| |
v v
+---------+----------+ +---------+----------+
| GapArtefacts / | | GapArtefacts / |
| Completeness | | Completeness |
| Determination | | Determination |
+---------+----------+ +---------+----------+
| |
+------------------+----------------+
|
v
+------------------------+
| Equivalence Verified |
| (stored timestamps |
| used — does not |
| depend on current |
| system time) |
+------------------------+
Detailed Description
1. Time Normalisation
[0024] Upon ingestion, each evidence record is canonicalised and its time value is normalised under a version-bound TimeNormalisationProfile.
[0025] The TimeNormalisationProfile defines:
(a) accepted time formats and parsing rules; (b) time zone conversion rules; (c) daylight saving adjustment rules; (d) precision normalisation rules; and (e) canonical TimeIndex representation format.
[0026] All time values are converted into a canonical TimeIndex representation deterministic under the TimeNormalisationProfile.
[0027] A CanonicalHash is computed over each canonicalised record for use as a secondary ordering key.
2. Deterministic Ordering
[0028] Records are sorted into a TimelineIndex using a deterministic ordering algorithm.
[0029] The primary ordering key is TimeIndex.
[0030] The secondary ordering key is CanonicalHash of the record, resolving ties in TimeIndex.
[0031] A tertiary deterministic tie-break rule declared in the TimeNormalisationProfile resolves exact duplicates in both TimeIndex and CanonicalHash.
[0032] The sorting algorithm produces identical TimelineIndex ordering across distributed nodes possessing identical inputs and profiles.
3. GapRuleProfile
[0033] The GapRuleProfile defines permitted intervals and completeness constraints governing gap detection.
[0034] Rules defined within a GapRuleProfile may include:
(a) maximum allowed interval between adjacent records; (b) required minimum record frequency within a defined window; (c) mandatory time windows requiring at least one record; and (d) exclusion intervals within which gaps are permitted.
[0035] The GapRuleProfile is version-bound to ensure reproducibility across deployments and audit cycles.
4. Gap Detection
[0036] For each adjacent pair of records in the TimelineIndex, processors compute:
Delta = TimeIndex[i+1] - TimeIndex[i]
[0037] If Delta exceeds a permitted interval threshold defined in the GapRuleProfile, a GapArtefact is generated.
[0038] The GapArtefact comprises:
(a) pre-gap record identifier; (b) post-gap record identifier; (c) computed Delta value; (d) GapRuleProfile version identifier; and (e) timestamp recorded as data at time of detection.
[0039] The GapArtefact is appended as an immutable entry to the evidence store.
5. Completeness Enforcement
[0040] If a downstream operation requires timeline completeness, processors verify the absence of disallowed GapArtefacts under the applicable GapRuleProfile.
[0041] If a disallowed GapArtefact exists, execution of the downstream operation is suppressed in a fail-closed manner.
[0042] Suppression prevents allocation of processor cycles and memory to the dependent operation.
[0043] A deterministic rejection record is appended identifying the disallowed GapArtefact and the GapRuleProfile version under which violation was determined.
6. Deterministic Replay
[0044] Replay is performed using stored GapRuleProfile and TimeNormalisationProfile version identifiers together with stored record data.
[0045] Replay recomputes Delta values using stored TimeIndex values recorded as data and does not depend on current system time.
[0046] Identical input records processed under identical GapRuleProfile and TimeNormalisationProfile produce identical GapArtefacts and identical completeness determinations.
7. Distributed Consistency
[0047] Distributed nodes possessing identical evidence sets and identical profile version identifiers generate identical TimelineIndex orderings, identical GapArtefacts, and identical completeness outcomes.
[0048] Deterministic gap detection therefore produces reproducible eligibility outcomes across distributed deployments without coordination.
Claims
-
A computer-implemented method for deterministic temporal evidence gap detection, the method comprising: (a) receiving a set of time-indexed evidence records and normalising time values under a version-bound TimeNormalisationProfile to produce a TimeIndex value per record; (b) constructing a deterministically ordered TimelineIndex using TimeIndex as primary key, CanonicalHash as secondary key, and a declared tie-break rule as tertiary key; (c) retrieving a version-bound GapRuleProfile defining permitted intervals and completeness constraints; (d) evaluating adjacent record pairs in the TimelineIndex and generating a GapArtefact when the computed interval Delta exceeds a permitted threshold, the GapArtefact comprising pre-gap and post-gap record identifiers, the Delta value, and a timestamp recorded as data; (e) appending each GapArtefact as an immutable entry to an evidence store; and (f) prior to executing a downstream operation requiring timeline completeness, verifying absence of disallowed GapArtefacts and, upon detection of a disallowed gap, suppressing execution in a fail-closed manner.
-
The method of claim 1 wherein the TimeNormalisationProfile defines time zone conversion rules, daylight saving adjustment rules, and precision normalisation rules.
-
The method of claim 1 wherein the GapRuleProfile defines maximum permitted intervals, mandatory time windows, and exclusion intervals.
-
The method of claim 1 wherein a deterministic rejection record identifying the disallowed GapArtefact and GapRuleProfile version identifier is appended to the evidence store upon completeness failure.
-
The method of claim 1 wherein replay recomputes Delta values using stored TimeIndex values recorded as data and does not depend on current system time.
-
The method of claim 1 wherein distributed nodes possessing identical evidence sets and identical profile version identifiers produce identical TimelineIndex orderings, identical GapArtefacts, and identical completeness determinations.
-
A computing system comprising one or more processors and memory storing instructions which, when executed, cause the processors to perform the method of any of claims 1 to 6.
-
A non-transitory computer-readable medium storing instructions which, when executed, cause one or more processors to perform the method of any of claims 1 to 6.
Licence
Any person is granted a perpetual, irrevocable, worldwide, royalty-free licence to make, use, implement, modify, or distribute any system or method described in this disclosure for any purpose, without restriction, under the Apache License 2.0.
A copy of the Apache License 2.0 is available at https://www.apache.org/licenses/LICENSE-2.0
Abstract
A deterministic temporal evidence gap detection mechanism is disclosed. Time-indexed evidence records are canonicalised and normalised under a version-bound TimeNormalisationProfile to produce a deterministically ordered TimelineIndex. Adjacent records are evaluated against a version-bound GapRuleProfile and a GapArtefact is generated and appended to an immutable store when computed intervals exceed permitted thresholds. Downstream operations requiring timeline completeness are suppressed in a fail-closed manner upon detection of disallowed gaps. Replay recomputes Delta values using stored TimeIndex data and does not depend on current system time. Distributed nodes operating under identical evidence sets and profile identifiers produce identical gap determinations, ensuring reproducible completeness verification across distributed systems.