Advanced Software Design and Domain-Driven Design Standard
Domain boundaries, invariant-rich models, typed contracts, and architecture that keeps frameworks subordinate to business meaning.
Standards / Software, Platform, and Reliability / MYTHOS-SWE
Software engineering, platform engineering, distributed systems, database and storage, and reliability engineering. Visual language: Dependency graphs, pipelines, state machines, event streams, service topology, failure propagation, SLOs, and recovery paths.
MYTHOS-SWE
Domain boundaries, invariant-rich models, typed contracts, and architecture that keeps frameworks subordinate to business meaning.
Memory-safe systems engineering, explicit ownership, controlled unsafe code, concurrency correctness, and production Rust governance.
Simple service boundaries, goroutine lifecycle discipline, backpressure, cancellation, observability, and operable Go systems.
Typed Python, deterministic automation, dependency control, testability, packaging, and maintainable scripting at enterprise scale.
Explicit language boundaries, schema-governed messages, compatibility policy, local IPC, remote RPC, and failure containment.
Secure desktop runtimes, Rust-native command boundaries, Svelte application state, capability control, and update integrity.
Executable specifications, invariant verification, deterministic transitions, model checking, and traceable implementation refinement.
Semantic intent payloads, typed renderers, deterministic presentation, accessibility, and model-independent interface contracts.
Debuggability by design, fault injection, property testing, reproducible failure analysis, and resilient recovery behavior.
Companions
Field guides, living guides, and portfolio editions that decompose or consolidate the MYTHOS-SWE standards.
A requirements-engineering guide covering stakeholder needs, system and software requirements, product discovery, domain language, functional and quality requirements, constraints, interfaces, use cases, scenarios, normative specifications, acceptance criteria, traceability, change control, validation, and specification-driven development with human and AI implementers.
A software-architecture guide covering architectural drivers, views and viewpoints, modularity, coupling and cohesion, domain-driven design, bounded contexts, dependency direction, monoliths, services, events, plugins, data ownership, architecture decisions, evolutionary design, governance, fitness functions, and architecture recovery.
An API-engineering guide covering HTTP and message semantics, resource and operation design, typed contracts, OpenAPI 3.2, AsyncAPI 3.1, JSON Schema, Protocol Buffers, GraphQL, errors, identity, pagination, idempotency, compatibility, versioning, testing, gateways, observability, governance, and AI-consumable tool interfaces.
A reliability guide covering error taxonomies, typed failures, exceptions and results, fault containment, timeouts, retries, backpressure, overload, circuit breakers, idempotency, partial failure, degradation, recovery, observability, error budgets, resilience testing, and failure-safe API and workflow semantics.
A language-spanning guide to asynchronous programming, futures, tasks, event loops, reactors, goroutines, channels, async Rust, Python asyncio, structured concurrency, cancellation, deadlines, backpressure, synchronization, testing, observability, performance, and safe shutdown.
A distributed-systems guide covering time, ordering, partial failure, replication, partitioning, consistency models, consensus, coordination, transactions, events, messaging, idempotency, sagas, compensation, reconciliation, observability, testing, multi-region design, and emerging verifiable or autonomous coordination.
A quality-engineering guide covering test strategy, quality models, risk, levels and types, unit and component tests, integration, contract, system, acceptance, property, model-based, fuzz, mutation, performance, security, usability, accessibility, test data, environments, automation, flakiness, CI/CD, metrics, and AI-assisted testing.
A debugging and diagnostics guide covering scientific troubleshooting, reproduction, state inspection, debuggers, traces, logs, metrics, dumps, memory and concurrency bugs, distributed debugging, production diagnostics, causal analysis, bisecting, incident timelines, postmortems, automation, and evidence-driven root-cause analysis.
A performance-engineering guide covering workload models, latency and throughput, queues, capacity, benchmarking, profiling, CPU, memory, I/O, databases, networks, concurrency, tail latency, load testing, optimization, regression prevention, hardware counters, energy, and cross-language toolchains for Rust, Python, Go, and systems software.
An implementation-centered secure-coding guide covering threat-informed design, trust boundaries, input and output handling, authentication and authorization, data protection, secrets, dependencies, concurrency, memory safety, error handling, secure defaults, testing, review, telemetry, incident readiness, and governed AI-assisted development.
A production observability guide covering telemetry strategy, structured logs, metrics, traces, events, context propagation, semantic conventions, instrumentation, collectors, sampling, cardinality, storage, dashboards, SLOs, diagnostics, privacy, cost, resilience, testing, and profiling.
A production delivery guide covering source and dependency control, build systems, hermeticity, caching, packaging, artifacts, container images, CI, testing gates, deployment, release strategies, provenance, signing, SBOMs, reproducibility, rollback, update security, and supply-chain incident response.
A maintainability engineering guide covering review objectives, change comprehension, correctness and security review, refactoring, characterization tests, technical-debt economics, architecture erosion, dependencies, readability, documentation, metrics, modernization, AI-generated code review, and sustainable improvement.
An advanced Rust concurrency guide covering futures, pinning, ownership across await points, Send and Sync, Tokio runtimes, tasks, structured task ownership, select, cancellation safety, channels, backpressure, locks, time, I/O, graceful shutdown, tracing, testing, debugging, profiling, and service architecture.
A low-level Rust guide covering unsafe contracts, raw pointers, aliasing, validity, initialization, layout, provenance, Send and Sync, atomics, FFI, callbacks, ownership transfer, panics, allocators, safe wrappers, testing with Miri and sanitizers, code review, documentation, supply-chain risk, and governance.
A production Python guide covering project structure, pyproject.toml, environments, builds, distributions, type hints, protocols, generics, dataclasses, validation, dependency injection, configuration, errors, logging, testing, performance, native extensions, deployment, and maintainable application architecture.
An advanced Python concurrency and automation guide covering event loops, coroutines, tasks, TaskGroup, cancellation, timeouts, queues, semaphores, streams, subprocesses, thread and process bridges, automation workflows, retries, idempotency, rate limits, structured logging, testing, debugging, profiling, and graceful shutdown.
An advanced Go guide covering goroutines, channels, ownership, the memory model, mutexes, atomics, contexts, deadlines, cancellation, services, HTTP, queues, worker pools, backpressure, retries, graceful shutdown, testing with race detection and synctest, profiling, observability, and production reliability.
A secure desktop application guide covering Tauri 2 architecture, Rust core, webview threat model, commands and IPC, capabilities and permissions, CSP, plugins, file and shell access, Svelte 5 reactivity, TypeScript 6 contracts, state, accessibility, testing, packaging, signing, updates, observability, performance, multi-window and multi-monitor behavior, and incident-ready desktop operations.
An implementation-grade guide to using coding models and agents across requirements, planning, repository understanding, implementation, review, testing, debugging, documentation, release, provenance, and verified completion.
Integrated engineering guide connecting the relevant Mythos standards, implementation patterns, operating procedures, architecture decisions, evidence expectations, and maturity path for enterprise software and platform engineering.
Portfolio Edition in the Standards Portfolios collection of the MYTHOS Engineering Standards Library.
Candidate status describes publication review state. It does not establish certification, legal compliance, implementation conformance, benchmark reproduction, or product readiness.