salopdict — Reference Guide for Budgeting Structures

salopdict provides a neutral, structured description of how budgeting elements are defined, allocated, scheduled, reviewed, and tracked. The content is organized as a technical reference. Each section details a discrete element of budget methodology with precise terminology and traceable checkpoints for consistency validation.

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Category Definition

Formalize classification labels and attributes

Allocation Logic

Deterministic rules and constraints for distributions

Category Definition

A category represents a distinct classification unit within the budgeting framework. Each category includes a canonical identifier, human-readable label, optional hierarchical parent reference, and a defined set of permissible attributes such as cadence, allowed allocation types, and tagging constraints. The canonical identifier is immutable once recorded and used as the primary reference in allocation logs and audit records. Categories are documented with metadata fields describing applicability, typical time horizons, and validation rules. Category definitions support deterministic matching logic when incoming transactions or commitments are mapped to structural elements. The reference representation includes a JSON-like schema illustration, field descriptions, and an example mapping table to ensure consistent implementation across systems.

Schema Snapshot

{
  "id": "category.operating.utilities",
  "label": "Utilities",
  "parent": "category.operating",
  "attributes": {
    "cadence": "monthly",
    "allocationTypes": ["fixed","variable"],
    "tags": ["facility","infrastructure"]
  }
}

Reference Table

Field	Description
id	Immutable identifier used in logs
label	Human-readable name
attributes	Structured constraints for allocation and validation

Allocation Logic

Allocation logic defines deterministic operations for distributing available budget units across categories and subcategories. The logic set includes prioritization rules, constraint enforcement, rounding policies, and fallback behaviors for insufficient resources. Each rule is expressed as an ordered statement with inputs, conditional predicates, transformation functions, and output targets. Rules are composed to preserve referential integrity and avoid circular allocations. Allocation operations produce immutable records that reference source identities, applied rules, timestamp, and resulting balances. Rule execution is idempotent and designed to be replayable for auditing. Validation routines ensure that allocations conform to category attributes and do not violate authorization constraints.

Allocation Example

Identify available funds for the planning interval
Apply fixed allocations as first-priority operations
Execute proportional allocations across flexible categories
Run validation and post-adjust rounding

Planning Intervals

Planning intervals define the temporal scope for budget application and review. Each interval record includes a start date, end date, recurrence specification, and a linkage to applicable category subsets and allocation rule versions. Intervals may be nested to represent overlapping planning horizons. Interval metadata captures expectations for typical transaction volumes and the sample size required for statistical checks. The system enforces interval boundaries when reconciling allocations and ensures that interval-based constraints are applied consistently across reporting and forecasting modules. Interval definitions include a changelog to track modifications to cadence or scope.

Interval Patterns

Common patterns include monthly, quarterly, and annual intervals. Custom intervals support start-end pairs with explicit recurrence rules following ISO date formats. Each interval is validated for duration and non-overlap when used in constrained contexts.

Revision Checkpoints

Revision checkpoints define scheduled validations and optional ad-hoc reviews. Each checkpoint specifies validators, input datasets, acceptance criteria, and a record of outcomes. Checkpoints may be configured to trigger notifications to authorized reviewers and to schedule follow-up actions such as reallocation or policy adjustments. Checkpoint outcomes are stored as verifiable snapshots of balances, allocations, and applied rules. The checkpoint model supports both manual and programmatic review flows, and includes an approval ledger that records reviewer identity, decision timestamp, and rationale fields for auditability.

Checkpoint Table

Checkpoint	Trigger	Output
End-of-Month Reconciliation	Interval close	Reconciliation snapshot
Policy Compliance Review	Rule change	Approval or required adjustments

Consistency Tracking

Consistency tracking provides metrics and signals that assess alignment between planned allocations and recorded outcomes. The tracking model stores time-series of allocated amounts, applied adjustments, and realized expenditures or commitments. Statistical checks compute variance, drift, and convergence measures. Thresholds are configured to surface deviations that require checkpoints. Consistency logs are versioned and linked to the exact rule set executed during allocation. The model supports queryable interfaces for trend analysis and for reconstructing historical states for forensic inspection.

Tracking Indicators

Variance to planned allocation
Reallocation frequency
Checkpoint exception rate