Summary
Ripple is working with Common Prefix to specify and formally verify key components (Payment Engine and the Consensus Protocol) of the XRP Ledger. You can read the fresh specification of the Payment Engine on Github: XRP Ledger Payment Engine Specification.
In 2012, when the XRP Ledger first went live, its creators had a singular goal, to make a new, more efficient blockchain, with the limited resources available. There were no teams of researchers, formal specification nor an ecosystem of auditors and academic papers to lean on. The engineers were racing to build a functioning, reliable decentralised ledger. Since those days, XRP Ledger has become one of the longest-running blockchains, operating well over a decade without downtime, powering hundreds of millions of ledger, and transactions[1]. However, for the foundational components, the single C++ implementation, xrpld, has served as the only definitive source of truth, creating fundamental challenges:
The system does not prove that it cannot reach an invalid state. The decade-long track record is a testament to the quality of engineering, however, to prepare the ledger for the next generation of complex features, we must move beyond empirical success to mathematical certainty.
The code tells us, in very precise C++ terms, what it does. It does not always tell us why, or, in other words, the code doesn't tell us the intention, making it impossible to distinguish between deliberate and ingrained behaviour.
This "specification debt" in the ledger's core is coming due as the blockchain evolves. The XRP Ledger is a dynamic system with new, highly complex features being continuously proposed and added.
Consider the recent and upcoming features:
These are intricate amendments that must weave into the decades-old logic of the ledger, but this raises further questions. How does the new Lending Protocol interact with the rules for frozen assets or clawbacks? How do batch transactions affect the ordering and execution logic of the DEX?
Each new feature that must fit into an already complex, unspecified system creates an exponential increase in possible states and interactions. Relying on human intuition and traditional testing alone is no longer sufficient to guarantee correctness.
A Verifiable Source of Truth
Addressing these challenges requires a formal, abstract specification of XRP Ledger’s critical components, that provide a verifiable source of truth to reason about the system’s behaviour, both manually and mechanically. Two distinct, but complementary assets:
A Human-Readable Specification: A clear, unambiguous document describing the system behaviour, serving as the canonical reference for developers and researchers.
A Machine-Verifiable Model: A formal, mathematical representation of the specification enabling mechanical proofs of system properties, simulating network behaviour, and verifying that new code changes do not violate core safety guarantees.
The Benefits: A Stronger Foundation
Establishing a formal specification builds a stronger foundation that will deliver compounding benefits across the entire XRP Ledger ecosystem.
But what are formal methods? In simple terms, formal methods are a set of techniques based on applied mathematics and logic, used to specify, design, and verify complex software and hardware systems.
Instead of relying solely on traditional testing, which can only prove the presence of bugs, formal methods allow us to prove the absence of certain classes of bugs. They help us answer questions like:
"Is it ever possible for this system to enter an invalid state?"
"Does this new Lending Protocol break any of the core invariants of the payment engine?"
In a system with rising complexity, human intuition fails. Formal methods provide tools to model complex interactions, detect edge-case bugs and provide mathematical certainty about the correctness and soundness of protocol designs.
First and foremost, a formal specification provides clarity and reduces ambiguity. It acts as a single source of truth, eliminating guesswork for developers building the XRP Ledger. This clarity also leads to faster onboarding, as a structured specification significantly accelerates new developers' and researchers' understanding of the protocol's core mechanics.
This initiative will also lead to more robust testing and auditing. The specification becomes the canonical benchmark against which to measure the implementation, enabling the creation of more comprehensive test suites and allowing auditors to independently verify an implementation's correctness, not just its internal self-consistency.
Furthermore, a formal model enables safer protocol evolution. Proposed amendments can be modelled and evaluated with mathematical rigour before a single line of code is written, ensuring predictable, more secure upgrades.
Finally, this work serves as a foundation for advanced technologies. A formal specification is the essential blueprint for building complex, next-generation features like trustless ZK-bridges. It simplifies the design of cryptographic circuits and dramatically reduces the risk of introducing subtle, critical errors.
The Process: From Code to Formal Proof
It's important to understand that turning an existing C++ implementation into a verifiable model is not straightforward. It is an act of modelling and abstraction, not translation. A direct, line-by-line conversion of the C++ codebase into a formal language is not only unfeasible, but it would miss the entire point of the exercise.
This first stage requires archaeology and engineering, reviewing design documents and code and engaging with core developers to understand the system's intent. The output of this stage is a clear, structured document in plain English that describes the protocol's rules without C++-specific details.
The second stage demands precise semantics of a formal language, focusing on the areas where the most dangerous bugs hide: concurrency, distributed consensus, and complex state transitions.
Modelling a system is an iterative process: checking for flaws with tools like TLA+ and refining the specification based on the results.
A direct code conversion would inevitably fail for three key reasons:
State Explosion: The C++ code contains excessive detail. A model that included all of it would have a state space far too large for any computer to analyse effectively.
Implementation Bias: A converted model would be a model of the implementation, not the design. A bug in the code would be faithfully reproduced in the model, defeating the purpose of verification.
Loss of Abstraction: The focus shifts from verifying the high-level correctness of the protocol to checking low-level details such as memory management, losing the crucial design-level insights we aim to gain.
Thus, instead modelling the system as a state machine to express its behaviour and desired system properties, enables using model checkers to exhaustively search for logical flaws in the design exhaustively, creating a powerful feedback loop that allows finding and fixing ambiguities in the informal spec and logical errors in the formal model, refining both until they are robust.
Collaboration and Focus
To execute this critical work, Ripple is collaborating with Common Prefix, a firm with deep expertise in formal verification and protocol analysis, including a specialized focus on consensus foundations, interoperability, and mathematically proving core properties of distributed ledger protocols.
The sheer complexity of the XRP Ledger requires a focused approach. It would be prohibitively expensive and time-consuming to specify the entire system at once. Together, we have identified the two most critical and complex components as our starting point: the Payment Engine and the Consensus Protocol.
The Payment Engine is the system responsible for all value transfer, including complex operations like crossing the decentralised exchange and rippling.
The Consensus Protocol is the heart of the ledger, enabling nodes to reach consensus on a common state. Its correctness is non-negotiable and underpins the safety and liveness of the entire network. We will create a formal model of the consensus mechanism to mathematically prove its core properties of liveness (the network continues to make progress), safety (the network never reaches an invalid state), and finality (transactions are irreversible once confirmed).
This initiative marks a crucial step in maturing the XRPL into a platform ready for the next decade of institutional finance and decentralised innovation.
The shift from code-as-truth to mathematics-as-truth is underway. We invite you to read the XRP Ledger Payment Engine Specification. Building on the Payment Engine specification, we’ll begin formal verification of it, and the Consensus Protocol in 2026.
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