Microsoft’s stated plan to remove “every line of C and C++” from its codebase by 2030 — and to do so by combining algorithmic source analysis with AI-driven translation into Rust — marks one of the most ambitious language-migration bets ever announced by a major platform company. The announcement, made public through a LinkedIn post from a senior Microsoft engineer and reinforced by a high-profile job advertisement, lays out a dramatic “North Star” metric — one engineer, one month, one million lines of code — and calls for senior systems-level Rust engineers to join a team building the automation and toolchain for large-scale C/C++ → Rust translation. The goal is technically sound in aspiration: Rust’s memory-safety model can neutralize entire classes of long-running security defects, and there is strong institutional pressure from governments and industry to reduce memory-safety vulnerabilities. The practical gaps between aspiration and reality, however, are vast: translating billions of lines of systems code while preserving semantics, performance, ABI compatibility, and certification guarantees is a multi-year, multi-dimensional engineering challenge that will require far more than a single algorithmic breakthrough.

Background / Overview​

Microsoft’s recent internal messaging makes three claims that change the stakes for systems engineering and platform security at the company:

• An internal engineering leader publicly framed replacing C/C++ across Microsoft as a time-boxed corporate objective, with a target year of 2030 and a productivity goal of “1 engineer, 1 month, 1 million lines of code.”
• Microsoft is recruiting senior engineers with production systems Rust experience to build the conversion and verification infrastructure that will drive that migration.
• The technical approach combines a large-scale code-processing graph, algorithmic analysis over that graph, and AI agents that perform, validate, and repair code modifications at scale.

Those messages are consistent with a broader pattern: Microsoft has steadily invested in Rust tooling and adoption over recent years. The company maintains a language projection for Windows APIs in Rust, multiple repositories and crates for Windows interoperability, sample Rust driver work, and internal pilots that place Rust in parts of the Windows and Azure stacks. Beyond Microsoft, national cybersecurity authorities and industry consortia have recommended increasing use of memory-safe languages — and Rust in particular — for new systems and for the highest-risk portions of legacy systems. That external pressure is now intersecting with internal momentum and with the emergence of AI models and program analysis techniques that could, in principle, make large-scale refactorings tractable.

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Why Microsoft wants Rust​

Memory safety as an engineering and security policy​

Rust’s principal appeal for system software lies in its compile-time ownership and lifetime system: the Rust compiler enforces rules that prevent common memory-safety bugs such as out-of-bounds reads/writes and use-after-free. These bugs have long been among the root causes of high-severity vulnerabilities in operating systems, networking stacks, and native libraries.

• For security teams, moving code to a language with stronger memory-safety guarantees is not a veneer; it changes the attack surface and eliminates entire classes of exploit primitives.
• For reliability engineers, deterministic handling of many low-level bugs reduces crash surface and undefined behavior.

The White House’s recent and widely circulated cybersecurity guidance — and parallel recommendations from national security and standards bodies in other countries — have made “memory-safe by default” a policy objective for critical software. That policy tailwind both justifies and accelerates large, risky modernization programs inside major vendors.

Organizational alignment and precedent​

Microsoft is not starting from zero. It has:

• A Rust-for-Windows effort that provides language projections and crates for calling Windows APIs from Rust.
• Internal experiments converting isolated components to Rust and tool support for driver development.
• A track record of building internal platforms that automate complex engineering tasks at scale.

These capabilities matter: a successful cross-language migration program requires firm-level investments across build systems, CI/CD, QA, security review, certification, and release disciplines — all areas where Microsoft has existing institutional capacity.

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What Microsoft says it will do (the technical take)​

The publicly stated plan centers on a three-part pipeline:

• Code graph and program-level analysis. Build a scalable graph representation of source code (ASTs, call graphs, module graphs, dependency graphs) that can be queried and manipulated across millions of lines.
• Algorithmic infrastructure. Apply deterministic, scale-oriented algorithms to find translation opportunities, infer ownership and aliasing models, and produce transformations that are syntactically and semantically consistent.
• AI-assisted code modification. Use AI agents (LLMs and specialized program models) to transform code, propose idiomatic Rust, repair compile or test failures, and generate human-readable patches; integrate those agents into automated verification loops.

That stack reflects the current research frontier: combining program analysis (ownership inference, pointer analysis, formal checks) with model-driven and search-based code transformations to yield safer idiomatic Rust rather than one-to-one syntactic transpilation. Recent academic and industry prototypes show promising building blocks: projects that translate C to Rust with varying degrees of automation, ownership reconstruction systems that lift raw pointers to Rust references, and LLM-driven peephole and function-level rewrites that reduce unsafe usage.

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How automated C→Rust translation works (building blocks)​

1) Syntax-to-syntax transpilation (baseline)​

Tools like C→Rust transpilers produce Rust source that preserves original program structure but leaves memory management semantics intact — which often results in Rust code littered with unsafe blocks and raw pointers. That gets you compilable Rust but not the safety or idiomatic advantages.

2) Ownership and aliasing inference​

The bigger step is inferring ownership and aliasing semantics from C code to convert raw pointers into Rust-safe references and data structures. Static analyses can propose ownership models for many pointer usages, but they often fail on complex aliasing, callbacks, and lifetime patterns.

3) Semantic repair and testing loops​

Translating code requires validation: compile, run unit tests, fuzz, and verify behavior. Automated repair mechanisms — from AST-level rewrites to search-and-replace guided by tests — are essential to catch and fix translation-induced regressions.

4) Human-in-the-loop and certification​

For safety-critical components, human review, formal verification, or additional testing regimes will be required. Some classes of code will remain in C/C++ or be wrapped by narrow FFI boundaries until equivalence can be proven.

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Strengths of the approach​

• Security gains: Reducing memory-unsafe code reduces a large, well-known attack surface. For products shipped to billions of devices and cloud customers, the cumulative security benefit is significant.
• Tooling leverage: Microsoft’s scale, engineering resources, and control over its own build and QA systems make it uniquely capable of aiming for company-wide translation.
• AI and automation speed-ups: Recent advances in large language models and program-synthesis research accelerate many tedious translation steps — symbol renaming, API mapping, and even some semantic refactorings — enabling pragmatic gains that were previously impossible.
• Organizational precedent: Microsoft already exerts influence over its ecosystem; a major migration would accelerate industry uptake of Rust and memory-safe toolchains.

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Real risks and practical constraints​

1) Semantic equivalence and undefined behaviour​

C and C++ have undefined behaviors that many systems accidentally rely on. Translating code while preserving semantics — especially in low-level or performance-critical code that pursues UB-dependent optimizations — is extremely hard. Automation can produce syntactically valid Rust that changes runtime behavior.

2) Unsafe blocks and the illusion of safety​

Most automatic translators currently produce Rust that still uses unsafe heavily for low-level interactions. The generated Rust may compile and run but will not deliver Rust’s memory-safety benefits until unsafe usage is minimized through further analysis and refactoring.

3) ABI, binary compatibility, and third-party drivers​

Operating-system components, drivers, and ecosystem binaries often rely on stable ABIs. Rewriting code in Rust may change calling conventions, memory layouts, or initialization sequences. Ensuring binary compatibility with third-party hardware vendors and external ISVs is a major integration challenge, particularly for Windows Drivers, firmware, and kernel components subject to certification.

4) Build systems, CI, and developer tooling​

Microsoft’s enormous mono-repos and legacy build systems will need deep integration points for Rust toolchains, cross-compilation, and platform-specific crates. Manual and automated testing across the billions of usage combinations represented by Windows installations must be scaled up.

5) Regression risk and release velocity​

AI-driven transformations can introduce subtle regressions. At Microsoft scale, one semantic divergence can cascade into customer-visible reliability or performance regressions, damaging trust and increasing operational risk.

6) Workforce and education​

Large-scale language migration creates a demand for Rust systems engineers, compiler engineers, and verification specialists that outstrips current supply. Microsoft’s hiring requirements (production systems Rust experience, compiler or OS experience preferred) highlight the personnel bottleneck.

7) Unverifiable scope claims​

Quantitative claims such as “one engineer, one month, one million lines” are aspirational and useful as productivity targets, but their feasibility depends on how “lines of code” are counted, what classes of files are included, and how many edge-case modules require human intervention. Microsoft has not published a definitive, public inventory of its total C/C++ lines of code, so any timeline that assumes exact counts should be treated as planning parameters rather than firm guarantees.

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Technical pitfalls the automated pipeline must overcome​

• Precise pointer aliasing and lifetime recovery for C idioms such as circular structures, interior mutability, and custom allocators.
• Safe translation of concurrency primitives that in C/C++ depend on undefined behaviors or platform-specific atomics.
• Reconstructing invariants expressed implicitly via coding conventions or bugs.
• Mapping platform-specific APIs and driver entry semantics into Rust-compatible, idiomatic designs without breaking contract assumptions.
• Generating test harnesses, property-based tests, and fuzzers to exercise translated code paths at scale.

Each of these problems has active research and tooling work underway, but none are solved in a general, battle-tested way that ensures zero-regression replacements across all of Microsoft’s PRs.

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How Microsoft can make this realistic (recommended strategy)​

• Prioritize ruthlessly: focus automated migration on the highest-risk modules (networking, parsers, font stacks, media codecs) where memory-safety bugs produce the most severe CVEs.
• Hybrid automation: apply fast transpilation for low-risk modules and incrementally add ownership inference and repair steps for medium-risk code; reserve manual rewrites and formal verification for the top-tier critical modules.
• Human-in-the-loop validation: integrate developer review, compiler-assisted proofs, and targeted fuzz testing into an automated pipeline so that each generated patch carries provenance, test signals, and human signoff.
• Compatibility layers: where ABI stability or vendor contracts matter, create narrow, well-audited FFI layers that allow the core logic to move to Rust while preserving binary compatibility in the short term.
• Investment in tooling and telemetry: robust static analyses, mutation testing, and rollout telemetry will reveal translation failure modes early and help tune automated agents.
• Workforce scaling: invest in dedicated Rust training, internal certification tracks, and transfer programs for C/C++ engineers to learn the idioms and safety patterns of Rust.
• Phased timelines and public reality checks: avoid firm, public drop-dead dates for full replacement; publish intermediate milestones, tooling evaluations, and measured outcomes to sustain credibility.

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Broader industry implications​

If Microsoft succeeds at scale — even partially — the ripple effects would be significant:

• Vendor expectations could shift, making Rust more common in vendor-supplied drivers and hardware stacks.
• Security standards and compliance regimes may begin to incorporate memory-safety metrics or require migration roadmaps for critical code.
• Tooling ecosystems (fuzzers, static analyzers, supply-chain code scanners) will adapt to Rust-first workflows and invest in cross-language verification.
• The commercial market for automated code-transformation platforms — including both proprietary and open-source tools — will expand rapidly.

However, successful partial migration — moving only the highest-risk or most tractable components — may be the more likely and immediate outcome. Rewriting every line of C/C++ across an organization with Microsoft’s scale, legacy, and hardware dependencies is not simply a software engineering problem; it’s a program-management and ecosystem orchestration problem.

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A reality check on timelines and productivity targets​

The headline metric (“1 engineer, 1 month, 1 million lines”) functions as a productivity North Star rather than an operational guarantee. Even if an automated pipeline can syntactically convert a million lines per engineer-month, the true cost comes from:

• The fraction of files that need manual review and redesign.
• Time to write or adapt tests, reproducible harnesses, and CI rules.
• Rework and debugging for semantic divergences and performance regressions.
• Vendor coordination for binary compatibility and driver signing requirements.

Given the unknown total of C/C++ lines that matter (kernel/driver surface area, core libraries, tooling, and third-party components), 2030 is an aggressive target. A prudent programme will treat that date as a planning horizon for strategic completion of high value components rather than literal eradication of every instance of C/C++ across all repositories.

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What to watch for next (short-term signals)​

• Releases of open-source tooling or Microsoft-published research demonstrating robust pointer ownership inference, large-scale test harness generation, or LLM-based repair at repository scale.
• Public case studies showing full migration of non-trivial Windows subsystems or Azure components without customer-visible regressions.
• Expanded recruiting and team creation, including hiring of compiler and formal-methods engineers.
• Documentation of rollout processes for Rust-written drivers and the toolchain for submitting and certifying those drivers for Windows Hardware Compatibility Programs.
• External adoption signals from hardware vendors and ISVs indicating willingness to accept Rust-based drivers or components.

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Conclusion​

Microsoft’s public commitment to eliminate C and C++ from its codebase and replace them with Rust is a bold, security-driven strategic pivot that aligns with modern memory-safety objectives and leverages advances in AI and program analysis. The potential benefits are real: fewer memory-safety vulnerabilities, cleaner safety guarantees, and a long-term reduction in exploit surface. But the program is also one of the most challenging engineering transformations imaginable: it requires preserving semantics and ABI compatibility across massive, decades-old codebases; it demands industrial-strength tooling, testing, and verification; and it depends on a sustained investment in people and process. Realistic success will come from a pragmatic, staged approach: focus first on the riskiest subsystems, combine automation with human expertise, and expose intermediate results so that external partners and the broader ecosystem can adapt. The “North Star” productivity metric is useful as an inspiration, but the true metric of success will be measured in fewer high-severity vulnerabilities, maintained performance and compatibility, and stable, auditable rollouts — not only raw lines of code translated. Companies contemplating similar transitions should treat Microsoft’s effort as a landmark experiment: one that, even if it falls short of total replacement by 2030, will still produce lasting improvements in tooling, process, and the case for memory-safe system software.

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Source: theregister.com Microsoft wants to replace its entire C and C++ codebase