Protocol-Driven Development: Governing Generated Software Through Invariants and Evidence
TLDR
Protocol-Driven Development (PDD) governs generated software by using machine-enforceable protocols, invariants, and verifiable evidence chains.
Key contributions
- Introduces Protocol-Driven Development (PDD) for governing automatically generated software.
- Defines protocols using structural, behavioral, and operational invariants to specify admissible implementations.
- Requires implementations to satisfy protocols and produce verifiable "Evidence Chains" for admission.
- Combines formal methods, property-based testing, and policy-as-code for robust software governance.
Why it matters
Automated software synthesis lacks robust governance, making it hard to trust generated code. PDD solves this by using machine-enforceable protocols and verifiable evidence chains, shifting focus from code to compliance. This approach enhances reliability and trust in automated software engineering.
Original Abstract
Automated program synthesis has reduced the cost of producing candidate implementations, but it introduces a harder governance problem: determining which generated artifacts are admissible in a software system. Natural-language specifications remain semantically ambiguous, and example-based tests sample only part of the behavioral space. Used alone, neither provides a sufficient control boundary for automated software construction. We introduce Protocol-Driven Development (PDD), a development model in which the primary software artifact is a machine-enforceable protocol rather than implementation code. We define a protocol as the triplet P = (S, B, O), where S specifies structural invariants, B specifies behavioral invariants, and O specifies operational invariants. Their conjunction defines the admissible implementation space of a software component. Under PDD, implementations are treated as replaceable realizations discovered through constrained search. An implementation is admitted if and only if it satisfies the governing protocol and produces a verifiable Evidence Chain of compliance. Admission is therefore grounded not in trust in the generator, but in protocol satisfaction and recorded evidence. By combining ideas from formal methods, property-based testing, policy-as-code, and software provenance, PDD defines a governance layer for automated software engineering. Its organizing principle is simple: code is transient; protocol is sovereign.
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