Finite State Machines

At its core, an FSM processes inputs and transitions between these states based on a set of predefined rules. Each state represents a particular condition or phase of the system, and the FSM can only be in one state at any given time. By offering a structured approach to system behavior, FSMs ensure predictability and reliability, especially important in mission-critical applications.

Ethereum employs a smart contract model that can be visualized as a "black box" with considerable complexity. An Ethereum Smart Contract (SC) acts as a miniature computer server, running specific code on the network. To interact with these SCs, users or other apps invoke its "methods" through signed messages. While this model affords great flexibility, aligning with Ethereum's vision of a "global computer", it also brings substantial challenges:

• Internal Variables: These are integral for a SC's function. For instance, an ERC-20 SC uses internal variables to keep track of token balances for every user.
• Complex Transactions: Transactions involving multiple SCs add layers of complexity. Each SC might call methods on the others, leading to a series of internal state changes before a final outcome. Such intricate transactions can be difficult to track and ensure reliability.
• Unpredictable Outcomes: Most DeFi breaches on Ethereum arise from the intricacies associated with SCs. With each SC having the power to modify its internal state freely, unforeseen or unpredictable results can emerge, often to the detriment of users.

Such systems are integral where failures might result in dire consequences, such as loss of life or catastrophic financial repercussions. The very nature of these systems necessitates a robust and foolproof control mechanism. Here's where FSMs come into the picture:

• FSM in Embedded Systems: FSMs are widely used in mission-critical embedded systems where the predictability of outcomes is paramount. FSMs can effectively process inputs to produce expected outputs based on their current state, ensuring consistent and reliable operations.

Integrating FSMs into VMs could significantly transform the way dApps operate:

• Predictable Correctness: FSMs can provide a structured approach to dApp development, ensuring that apps behave predictably and reliably, even in complex scenarios.
• Simplified Transaction Logic: With FSMs, the transaction logic can be streamlined, reducing the cascade of internal state changes and making outcomes more understandable.
• Enhanced Security: By limiting the possible states a dApp can be in, FSMs can reduce the potential attack vectors and vulnerabilities commonly exploited in conventional smart contract models.

Radix has strategically incorporated Finite State Machines (FSM) into its architecture to address specific issues observed in traditional blockchain platforms. The FSM model, by its nature, brings structure and predictability to system interactions. In the context of Radix, this means that dApps have clearer transactional logic. For instance, when transferring assets between parties or implementing multi-step financial protocols, the use of FSM ensures that the dApp proceeds through clearly defined states, reducing the risk of unexpected behaviors. A practical example can be seen in Radix's approach to token exchanges. Instead of allowing a free-form interaction as seen in many Ethereum-based protocols, a Radix dApp built using FSM would follow a more regimented and predictable path: from initiation, to validation, to execution, and finally to completion. This structured methodology inherently reduces complexities and potential vulnerabilities, paving the way for safer and more reliable decentralized applications.