RESEARCH / BENCHMARKS
Measure the engineering effect, don't assume it.
BOUND's benchmark program should measure whether explicit boundaries, contracts, independent execution, and continuous verification change observable engineering outcomes.
Evidence status: this page defines proposed measurements and experimental structure. It does not report validation results, adoption, or causal effects that have not been established by published experiments.
Candidate measurements
| Measure | Operational definition | Why it matters |
|---|---|---|
| Integration defects | Defects discovered when independently developed components are integrated. | Captures failures at coordination boundaries. |
| Contract violations | Observed deviations from a declared interface or behavioral contract. | Separates contract drift from implementation defects. |
| Coordination events | Human synchronization events required to resolve cross-boundary ambiguity. | Measures coordination load rather than implementation volume. |
| Time to integration | Elapsed time from independently executable change to verified integration. | Provides a concrete integration-cycle measure. |
| Rollback frequency | Changes reverted because integration or verification failed. | Captures downstream cost of divergence. |
| Agent scope violations | Agent actions outside the explicitly permitted execution context. | Measures bounded-agent compliance. |
| Verification failures | Required checks that fail before acceptance. | Shows where contracts or implementations diverge. |
Experimental structure
- Define the engineering task and population.
- Specify the boundary and contract artifacts before execution.
- Record baseline and BOUND conditions using the same task definition.
- Capture raw events and verification results rather than only summary metrics.
- Predefine exclusions, failure handling, and stopping conditions.
- Report limitations and alternative explanations alongside results.
Minimum benchmark record
{
"task": "...",
"condition": "baseline | bound",
"participants": [],
"boundaries": [],
"contracts": [],
"coordination_events": [],
"integration_events": [],
"verification_results": [],
"rollbacks": [],
"scope_violations": [],
"duration": "...",
"limitations": []
}
The structure is illustrative rather than a normative benchmark schema. A future benchmark implementation should version its data model before collecting comparable datasets.
What a benchmark must not claim by itself
- A reduction in one measured defect class does not establish universal superiority.
- One project or team does not establish general adoption or industry effect.
- Correlation between explicit contracts and an outcome does not by itself establish causation.
- Agent scope-violation measurements depend on the enforcement model used by the experiment.