Dependency Analysis

1. Object of study

The Domain studies dependency types, direction, conditions, criticality, transitive effects, cycles, and points of concentrated fragility

The objects of study include authority dependencies, where a rule relies upon a source of legal or institutional power; semantic dependencies, where meaning relies upon definitions, classifications, or interpretive context; logical dependencies, where one proposition or decision requires another; procedural dependencies, where a step requires completion of an earlier process; and evidentiary dependencies, where action requires specified records or facts.

Further classes include data dependencies, technical dependencies, resource dependencies, organizational dependencies, temporal dependencies, jurisdictional dependencies, contractual dependencies, and external-service dependencies. A single rule may depend upon several classes simultaneously. For example, an eligibility rule may depend upon a statutory definition, an identity record, a current income dataset, an authorized reviewer, a functioning case-management system, and a notice procedure completed within a specified period.

The Domain examines directionality and condition. If Rule A depends upon Definition B, the reverse is not necessarily true. Some dependencies apply only in a jurisdiction, version, case type, operational state, or emergency. Others are optional alternatives: a rule may be satisfied through one of several evidentiary paths. Criticality also differs. Failure of one dependency may prevent lawful operation entirely, while another reduces efficiency or increases uncertainty.

Dependency Analysis extends beyond immediate links. A rule may rely on a procedure that relies on a dataset that relies on an external classification whose governing definition has changed. These transitive chains create propagation paths through which defects and changes travel. Cycles may also arise, such as two approvals that each require the other, or two classifications defined in terms of one another. The shape of the network is therefore an object of study in its own right.

2. Purpose within Rules Integrity

Dependency Analysis makes hidden prerequisites and propagation paths visible before they become operational failure

Rules often appear self-contained because their dependencies are distributed across different documents, teams, systems, contracts, and institutions. When those dependencies remain invisible, a rule may be approved without the authority, information, capacity, or infrastructure required to apply it. It may continue to appear valid after a definition is repealed, a supplier changes an interface, a responsible role disappears, or a supporting process becomes inaccessible.

The purpose of the Domain is to replace presumed self-sufficiency with an inspectable account of reliance. This supports feasibility review, architecture, validation, continuity planning, incident investigation, change impact analysis, and controlled retirement. It helps an institution distinguish a defect in the rule itself from a failure in something upon which the rule depends.

Dependency Analysis also reveals concentration and systemic risk. Many apparently unrelated rules may rely upon one authority interpretation, one dataset, one technical service, one organizational role, or one vendor. Failure or change at that point can affect a large portion of the rule system. Visibility allows institutions to establish redundancy, fallback, escalation, contractual protection, monitoring, or a deliberate acceptance of the risk.

3. Boundaries

Dependencies explain reliance; they are distinct from architecture, traceability, contradiction, impact, and mere association

Rule Architecture organizes the larger system of rule components, layers, modules, and interfaces. Dependency Analysis studies the specific reliance relationships that allow those components to function. An architectural connection is not automatically a dependency, and a dependency may cross formal architectural boundaries that the institution has not documented.

Traceability preserves evidence of where a relationship came from and how it changed. Dependency Analysis determines the nature, direction, condition, and consequence of the reliance. Change Impact Analysis uses dependency knowledge to evaluate a proposed or actual change, but dependency analysis exists even when no change is planned. Contradiction Analysis asks whether requirements are incompatible; dependency failure may create contradiction, but many dependencies fail through absence, delay, inaccuracy, or unavailability rather than normative conflict.

The Domain also distinguishes causally or operationally necessary reliance from simple correlation or co-occurrence. Two rules appearing in the same process does not prove that one depends upon the other. A valid dependency claim should state what is required, why it is required, under which conditions, and what happens if the relied-upon element changes or fails.

4. Principal questions

The recurring questions identify prerequisites, interfaces, failure behavior, alternatives, concentration, and propagation

• What must be valid, available, complete, timely, accurate, authorized, or compatible for this rule to operate as intended?
• Is each dependency explicit in the rule system, or is it inferred from practice, technology, organizational knowledge, or external conditions?
• What type of dependency exists, in which direction, and under what jurisdictional, temporal, factual, or operational conditions?
• Does the rule have one required dependency, several cumulative prerequisites, or alternative paths that can substitute for one another?
• What is the consequence of absence, delay, corruption, ambiguity, revocation, unavailability, or incompatible change?
• Which dependencies are critical, concentrated, external, weakly governed, or controlled by parties outside the rule owner’s authority?
• What transitive dependencies and cycles exist beyond the immediately visible relationship?
• How are versions synchronized, and what happens when a rule and its dependency change on different schedules?
• Which controls detect dependency degradation before decisions or rights are affected?
• What evidence supports the dependency claim, and who owns the relationship rather than only its individual endpoints?

5. Methods of inquiry and practice

Analysis proceeds through inventory, semantic decomposition, dependency elicitation, graph construction, criticality assessment, failure testing, and monitoring

Inventory and boundary definition identifies the rule, version, implementation, population, process, and institutional environment under review. The boundary should be wide enough to include external authorities and services that materially affect operation, while remaining explicit about what has not been examined.

Semantic and procedural decomposition separates the rule into actors, actions, conditions, definitions, data needs, approvals, time requirements, outputs, and consequences. This exposes candidate prerequisites that may be hidden in prose or assumed by experienced operators. Interviews, observation, process records, technical specifications, contracts, and incident reports supplement formal text.

Dependency elicitation and classification states each relationship as a testable proposition: the dependent element, the relied-upon element, dependency type, direction, condition, rationale, authority, owner, and failure consequence. Analysts distinguish required, optional, alternative, and probabilistic reliance and identify whether the relationship is direct or inferred.

Graph construction and traversal represents nodes and typed edges so that transitive paths, shared dependencies, orphaned elements, cycles, and high-connectivity points can be examined. Human-readable tables may be sufficient for smaller systems; larger environments may require graph-oriented data or equivalent structured representations. The method remains independent of a particular tool.

Criticality and failure-mode analysis evaluates likelihood, detectability, recoverability, consequence, and time to harm. Analysts test absence, stale versions, delayed data, contradictory interfaces, unauthorized substitution, capacity loss, and partial failure. They examine whether fallback paths are lawful and whether degraded operation changes rights, obligations, or outcomes.

Interface and version validation checks that semantic, procedural, organizational, and technical interfaces preserve the intended relationship. A technically successful exchange may still fail if a category changes meaning. Effective dates, migration periods, backward compatibility, and historical reproducibility must be considered when dependencies evolve at different times.

Monitoring and review establishes signals for availability, quality, authority, performance, contract status, organizational ownership, and known changes. Reviews should occur when incidents arise, suppliers or authorities change, related rules evolve, repeated workarounds appear, or the dependency becomes more concentrated or consequential.

6. Evidence and records

A dependency claim requires evidence of the relationship, its conditions, its current state, and the consequence of failure

Relevant evidence includes authoritative rules and definitions, delegation instruments, contracts, service descriptions, procedures, process maps, data dictionaries, schemas, interface specifications, organizational charts, role assignments, technical configurations, test results, operational records, incident reports, support histories, capacity records, and observed work practices. No single class is sufficient for every dependency.

The dependency record should identify both endpoints, relationship type, direction, applicability conditions, rationale, source evidence, owner, criticality, fallback, monitoring control, current status, version, and review date. Where the relationship is inferred rather than formally declared, the inference and uncertainty should be visible.

Evidence must remain temporal. A dependency that existed last year may no longer be valid after an authority change, system migration, contract termination, organizational restructuring, or revised definition. Historical versions are necessary to reconstruct past decisions and determine which dependency state applied at the time.

7. Expected outputs

The Domain produces dependency models, criticality findings, interface requirements, and controls for continuity and change

• a dependency register stating endpoints, type, direction, conditions, rationale, evidence, owner, version, and status;
• a typed dependency graph or equivalent map showing direct and transitive relationships across rules, authorities, data, processes, systems, roles, and external services;
• critical-dependency and concentration findings identifying single points of failure, weak governance, external control, and high propagation potential;
• cycle, orphan, missing-prerequisite, stale-version, and incompatible-interface findings supported by inspectable evidence;
• interface and service requirements defining semantics, availability, quality, timing, capacity, authority, and change notification;
• failure-mode and contingency assessments covering lawful fallback, degraded operation, recovery, escalation, and time to consequence;
• monitoring controls and review schedules linked to dependency state, incidents, contracts, authority changes, and lifecycle events;
• inputs to architecture, validation, change impact, operational continuity, incident response, and retirement planning.

8. Relationship to the rule lifecycle

Dependencies arise in design, are made explicit through engineering, and must remain controlled through operation, change, and retirement

9. Relationship to other Domains

Dependency Analysis supplies the connective knowledge required by architecture, traceability, contradiction, impact, analytics, and assurance

Rule Semantics establishes the meanings upon which semantic dependencies rely. Rule Architecture provides system structure, while dependency analysis reveals actual reliance within and across that structure. Rule Taxonomy supplies classifications for dependency types, rule components, and affected elements.

Traceability preserves the evidence and history of dependency claims. Contradiction Analysis uses dependencies to find indirect conflicts and implementation divergence. Exception Engineering identifies the authorities, evidence, workflows, and systems required to operate departures. Change Impact Analysis traverses dependency paths to determine what a proposed change may affect.

Rule Analytics investigates patterns such as concentration, repeated failure, and operational consequence. Rule Integrity Metrics can measure selected dependency conditions, such as coverage or stale interfaces, without equating connectivity with integrity. Rule Assurance relies upon validated dependency evidence to judge whether the system has been examined beyond isolated documents.

10. Failure patterns

Dependency failure appears as hidden prerequisites, single points of failure, unsynchronized versions, unlawful fallback, and cascading consequence

• a rule is adopted before the required authority, data, capacity, process, role, or technical service exists;
• dependencies remain in the knowledge of a few experienced people and disappear when roles change;
• a shared definition or dataset changes, but dependent rules and implementations continue using the prior meaning;
• many rules rely upon one external service or organizational unit without redundancy, notice rights, or continuity planning;
• fallback procedures restore technical operation but produce outcomes not authorized by the governing rule;
• direct dependencies are documented while transitive chains and cycles remain invisible;
• ownership is assigned to each endpoint, but no one owns the interface or the consequences of relationship failure;
• technical monitoring reports availability while semantic accuracy, authority, timeliness, or completeness has degraded;
• a rule is retired without identifying downstream policies, forms, contracts, decisions, reports, and software that still rely upon it;
• dependency maps become stale inventories because they are not connected to change, incidents, versions, and review obligations.

11. Institutional responsibilities

Dependency responsibility belongs at the relationship, not only with the separate owners of its endpoints

Rule owners identify substantive prerequisites and remain accountable for operating assumptions. Architects and engineers represent interfaces and implementation reliance. Legal, policy, regulatory, data, security, operational, procurement, and subject-matter experts evaluate authority, meaning, feasibility, quality, external control, and continuity within their fields.

Data and service owners maintain definitions, quality, availability, version notice, and support commitments. Contract and procurement functions ensure that external dependencies include appropriate obligations for change notification, continuity, audit, transition, and termination. Operational teams report workarounds and near failures that formal specifications may not reveal.

Governance bodies assign ownership of critical relationships, determine risk acceptance, require redundancy or fallback, and coordinate changes across organizational boundaries. Independent reviewers challenge completeness, criticality, stale evidence, and unsupported assumptions. Records stewards preserve dependency versions so that past decisions can be reconstructed accurately.

12. Open research questions

The Domain requires research on semantic dependency discovery, dynamic graphs, concentration, cascading failure, and governance across institutions

• Which methods can discover implicit dependencies in natural language, workflows, software, and organizational practice while preserving explainability?
• How should dependency types and criticality be represented across legal, governmental, commercial, technical, and social rule systems?
• What measures best identify concentration and propagation risk without treating every highly connected element as defective?
• How can dynamic dependency models remain current as rules, data, systems, contracts, personnel, and external authorities change?
• What methods distinguish true prerequisite relationships from correlation, sequence, convenience, or historical habit?
• How should probabilistic, alternative, and partially substitutable dependencies be evaluated under uncertainty?
• What governance arrangements work when critical dependencies cross organizations that do not share ownership, incentives, or disclosure duties?
• How can dependency evidence support simulation of cascading effects without overstating predicted consequence?

Related Education

Foundational chapters supporting the Dependency Analysis Domain

The Education series introduces semantics, context, authority, lifecycle, traceability, contradiction, and governance. Dependency Analysis develops those foundations into a systematic study of reliance and propagation.

Related Scope stages

The Domain exposes prerequisites and propagation paths from conception through retirement

Concluding principle

A rule is only as dependable as the prerequisites and interfaces upon which its authority, meaning, and operation rely