EDN-R/CODE: A RELIABILITY RUNTIME FOR MODEL-HETEROGENEOUS SOFTWARE ENGINEERING AGENTS

Repository-level coding agents modify software through models that differ in out-put protocol, instruction sensitivity, failure modes, and provider behavior. Re-placing a model can therefore change how execution fails, not just task accu-racy. We present EDN-R/Code, a runtime that treats models as proposal pro-ducers rather than execution authorities. Adapters lower native responses into ProposalIR; each attempt runs in an isolated workspace from an immutable base snapshot. The runtime authorizes mutations, binds veriffcation evidence to candidate state, classiffes failures, retries or rebinds producers under explicit bud-gets, and persists attempt state for recovery. DeepSeek’s native JSON-schema output and GLM’s native tool calls enter the same runtime. Targeted kill tests ex-ercise malformed-output, timeout, stale-evidence, capability, critical-information, and crash/recovery boundaries. On six frozen held-out micro-repositories, ho-mogeneous DeepSeek redundancy and heterogeneous GLM-to-DeepSeek each achieve 6/6 success. All 12 runs accept candidates passing visible and hidden tests and pass replay checks; no false acceptance or unsafe execution is observed, and all eight required multi-ffle scope checks pass. Heterogeneity provides one real cross-producer rescue but no accuracy gain: it consumes 10,971 versus 5,106 tokens and 185.39 versus 60.19 seconds. These controlled ffndings position het-erogeneous producers as a recovery resource; reliability rests on stable execution semantics, not assumed stability of model behavio