SpecOps vs. BDD/ATDD: Key Distinctions

[mheadd]

The Question

How does SpecOps differ from established specification-driven approaches like Behavior-Driven Development (BDD) and Acceptance Test-Driven Development (ATDD)?

This is an important question because SpecOps shares DNA with these approaches—all center on specifications guiding implementation. But the context, purpose, and application are fundamentally different.

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Quick Overview of BDD/ATDD

Behavior-Driven Development (BDD)

• Focuses on describing system behavior in business language
• Uses Given-When-Then format for scenarios
• Tests are written as executable specifications
• Collaboration between developers, QA, and business stakeholders
• Primary goal: Ensure software meets business requirements through shared understanding

Acceptance Test-Driven Development (ATDD)

• Write acceptance tests before implementation
• Tests define "done" for a feature
• Collaboration between customer, developer, and tester
• Focus on acceptance criteria
• Primary goal: Build exactly what the customer wants, no more, no less

Both approaches are about building new systems correctly.

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How SpecOps Is Different

1. Context: Legacy vs. Greenfield

BDD/ATDD: Applied when building new features or new systems

• You're defining behavior that doesn't exist yet
• Stakeholders decide what they want
• Tests drive new development
• No existing implementation to understand

SpecOps: Applied to existing legacy systems being modernized

• You're documenting behavior that already exists (and must be preserved)
• The legacy system is the source material
• Specifications capture what already works (and what people depend on)
• There's decades of implementation to understand

Key Insight: BDD/ATDD is forward-looking (what should we build?). SpecOps is backward-looking first (what does this already do?), then forward-looking (how do we preserve/improve it?).

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2. Primary Goal: Knowledge Preservation vs. Requirement Clarity

BDD/ATDD: Achieve shared understanding of new requirements

• Bridge gap between business and technical teams
• Prevent miscommunication about new features
• Ensure new code meets expectations

SpecOps: Preserve institutional knowledge about existing systems

• Capture knowledge before experts retire
• Document complex business rules embedded in old code
• Create specifications that outlast any particular implementation
• Bridge decades of accumulated understanding into modern context

Key Insight: BDD/ATDD prevents misunderstanding of future needs. SpecOps prevents loss of past knowledge.

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3. Specification Source: Stakeholder Intent vs. Legacy Code Analysis

BDD/ATDD: Specifications come from stakeholders

• Business people describe desired behavior
• Product owners define acceptance criteria
• Team collaborates to define scenarios
• Human intent drives specification

SpecOps: Specifications extracted from legacy code (with AI assistance)

• AI agents analyze existing code to understand behavior
• Specifications document what code actually does
• Domain experts verify AI understanding is correct
• Legacy implementation drives initial specification

Key Insight: BDD/ATDD specifications capture what people want. SpecOps specifications capture what systems do (which may differ from what anyone remembers wanting).

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4. The Role of AI: Optional Tool vs. Essential Enabler

BDD/ATDD: AI is optional, not central to the methodology

• Can use AI to help write scenarios
• Can use AI to generate test code
• But methodology predates AI and works without it
• Human collaboration is the core

SpecOps: AI is essential to the methodology

• Analyzing legacy code at scale requires AI
• Generating initial specifications from code requires AI
• Generating modern implementations requires AI
• SpecOps wouldn't be practical without AI

Key Insight: BDD/ATDD can be done with or without AI. SpecOps is fundamentally enabled by AI capabilities.

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5. Verification By: Team Collaboration vs. Domain Expert Authority

BDD/ATDD: Whole team collaborates on specifications

• Developers, QA, and business representatives work together
• Real-time collaboration during specification writing
• Iterative refinement as features develop
• Team consensus on behavior

SpecOps: Domain experts are arbiters of correctness

• Specifications generated by AI, not written collaboratively
• Domain experts verify specifications match their understanding
• Policy experts confirm regulatory compliance
• May involve stakeholders who don't code and aren't on the team

Key Insight: BDD/ATDD is collaborative specification writing. SpecOps is expert verification of AI-generated specifications.

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6. Temporal Focus: Active Development vs. Long-Term Preservation

BDD/ATDD: Focus on current development cycle

• Specifications written for features being built now
• May become outdated as system evolves
• Primary value during active development
• Tests may be maintained, but specifications often aren't

SpecOps: Focus on enduring knowledge preservation

• Specifications are permanent artifacts
• Version-controlled as source of truth
• Updated before code changes (like GitOps)
• Value persists long after modernization completes
• Foundation for future modernizations

Key Insight: BDD/ATDD specifications serve the immediate project. SpecOps specifications serve decades of system lifecycle.

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7. Scale and Scope: Feature-Level vs. System-Level

BDD/ATDD: Typically applied at feature or user story level

• Individual scenarios for specific behaviors
• Incremental specification of new functionality
• Focused on discrete features or epics

SpecOps: Applied at entire system or major component level

• Comprehensive documentation of complete systems
• Capturing years of accumulated functionality
• Documenting complex interdependencies
• System-wide knowledge preservation

Key Insight: BDD/ATDD works feature by feature. SpecOps tackles entire legacy systems.

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8. Testing Philosophy: Tests as Specifications vs. Specifications for Testing

BDD/ATDD: The tests are the specifications

• Given-When-Then scenarios are executable
• Specifications run as tests
• Tests prove implementation matches specification
• Direct coupling between spec and test

SpecOps: Specifications inform tests (but aren't tests themselves)

• Specifications written in natural language for human verification
• Tests generated from specifications
• Tests verify implementation matches specification
• Separation between specification and test implementation

Key Insight: BDD/ATDD: specification = test. SpecOps: specification → tests.

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When to Use Which Approach

Use BDD/ATDD When:

• Building new features or systems
• Need shared understanding among team
• Want to prevent miscommunication about requirements
• Team can collaborate on specification development
• Building in short cycles with fast feedback

Use SpecOps When:

• Modernizing existing legacy systems
• Institutional knowledge is at risk
• Need to preserve understanding of complex business rules
• Legacy code is the source material
• Domain experts can't write specifications but can verify them
• Long-term knowledge preservation is critical
• System will be maintained/modernized over decades

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Can They Work Together?

Yes, in hybrid scenarios:

SpecOps First, Then BDD/ATDD:

1. Use SpecOps to document existing legacy system behavior
2. Verify specifications with domain experts
3. Use specifications as baseline requirements for new system
4. Apply BDD/ATDD for new features being added during modernization

Example: Modernizing a benefits system

• SpecOps: Document existing eligibility rules from COBOL code
• Verify with policy experts
• BDD/ATDD: Define new online application features being added
• New features use BDD, legacy preservation uses SpecOps

SpecOps for Legacy, BDD/ATDD for Greenfield Components:

• SpecOps handles components being modernized from legacy
• BDD/ATDD handles net-new capabilities
• Both approaches coexist in the same project

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Similarities Worth Noting

Despite differences, SpecOps shares important principles with BDD/ATDD:

Specification-Driven: All three put specifications before/alongside code
Human-Readable: All emphasize accessible language over technical jargon
Verification Focus: All make it easier to verify correctness
Collaboration: All involve non-developers in defining system behavior
Living Documentation: All treat specifications as maintained artifacts

SpecOps builds on the wisdom of BDD/ATDD but adapts it for the unique challenges of legacy modernization with AI assistance.

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The Unique SpecOps Contribution

What SpecOps adds to the conversation:

1. AI-Assisted Knowledge Extraction: Using AI to extract behavior from legacy code at scale

2. Domain Expert Verification Model: Clear process for non-technical experts to verify specifications they didn't write

3. GitOps-Style Specification Management: Treating specifications as source of truth with version control and change management

4. Strangler Fig Integration: Connecting specifications to incremental modernization patterns

5. Cross-Government Collaboration: Framework for sharing instruction sets and specifications across agencies

6. Long-Term Knowledge Preservation: Explicit focus on specifications as enduring artifacts beyond any single modernization

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Addressing the "But Isn't This Just BDD?" Question

When people say "Isn't SpecOps just BDD for legacy systems?", here's the nuanced answer:

Superficially similar: Both use specifications to guide development

Fundamentally different in:

• Context: New development vs. legacy modernization
• Specification source: Stakeholder intent vs. existing code analysis
• AI role: Optional tool vs. essential enabler
• Primary goal: Requirement clarity vs. knowledge preservation
• Timeline: Project-focused vs. decades-long system lifecycle
• Verification: Team collaboration vs. expert authority

Better analogy: "SpecOps is to legacy modernization what BDD/ATDD are to greenfield development—specification-driven approaches adapted to their specific context."

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For Further Discussion

Interesting questions for the community:

1. Can BDD tools (Cucumber, SpecFlow) be adapted for SpecOps?

   • The Given-When-Then format might work for some specifications
   • But many SpecOps specifications need more narrative structure

2. Should SpecOps specifications be executable?

   • BDD makes specs executable
   • SpecOps prioritizes human readability for domain expert verification
   • Trade-offs between executable precision and accessible language

3. What can SpecOps learn from decades of BDD/ATDD practice?

   • Patterns for clear specification writing
   • Collaboration techniques between technical and non-technical stakeholders
   • Tools and workflows for specification management

4. What can BDD/ATDD learn from SpecOps?

   • Using AI to accelerate specification development
   • Treating specifications as long-term knowledge artifacts
   • GitOps-style specification governance

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Conclusion

SpecOps is not BDD/ATDD rebranded. It's a related but distinct approach that:

• Addresses the specific challenges of legacy system modernization
• Leverages AI capabilities that didn't exist when BDD/ATDD were developed
• Prioritizes institutional knowledge preservation over requirement clarity for new features
• Treats specifications as enduring source of truth like GitOps treats Git repositories

SpecOps stands on the shoulders of BDD/ATDD and other specification-driven approaches, adapting their wisdom to the unique context of AI-assisted legacy modernization in government.

Both have their place. Both are valuable. The key is using the right approach for your context.