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Smart Contracts

categories: reading

tags: blockchain smartcontract


Description/Summary

Smart contract engineering and papers

Content

A Languge-Based Approach to Smart Contract Engineering

Writing Contracts as Finite State Machines

A Quartz contract definition adheres to a widely used structure for describing and analyzing computer programs known as a finite state machine. Under this organization, a contract is in one of a fixed number of explicitly listed possible states, including a designated starting state.

Insights on Language Design

Quartz: A Framework for Engineering Secure Smart Contracts

The Quartz language contains several contract-specific features. Many distributed ledgers, most notably Ethereum, have first-class support for virtual currency that may be bound to contracts and exchanged among them. State machines in Quartz use keywords to check their balance or disburse tokens to an external contract. If we wish to produce contracts for a ledger without first-class tokens, we can emulate this functionality by adding an extra field and the necessary operations to the generated implementations. Transition authorization is treated as a first-class primitive in Quartz, unlike in Solidity and other contract languages. Quartz allows contract authors to express rich authorization constraints such as restricting an operation to any member of a particular group or requiring approval from all members of a group before it is executed. Finally, Quartz restricts communication between state machines. A state machine may send tokens to another state machine, but it cannot invoke another machine’s transitions directly. This simplifies the expression and verification of contract logic. Note that Quartz makes no assumptions about the behavior of the recipient, which may or may not be another Quartz state machine, for model checking.

Here, we formally define a subset of the operational semantics of the Quartz DSL. Evaluation rules for expressions, which are generally routine, are omitted for brevity. A Quartz state machine is formally defined as a 4-tuple ⟨𝑄, 𝑞0, 𝑇 , 𝐹 ⟩ where 𝑄 is a set of states, 𝑞0 is the initial state, 𝑇 is a set of transitions, and 𝐹 is a set of fields, each with a specific name and type.

Why Model Checking and TLA+?

We chose bounded model checking as Quartz’s core verification technique because it does not require significant intervention from the end user, i.e., the contract author. Although a contract author must write the invariants she would like to have verified, Quartz fully automates the more difficult task of writing a formal specification of the contract’s behavior and its execution environment that is suitable as input to a model checker. Model checking also offers immediately useful feedback to the user as output — an execution trace that produces a violation of one or more of the desired properties. This feedback helps guide a contract author in making refinements to her state machine.

TLA+ serves as Quartz’s target specification language and its verification backend. TLA+ and its model checker, TLC, are relatively mature, well-documented, and have been successfully applied in developing and testing significant systems [40]. More modern model checkers have since emerged, but they tend to be inherently tied to the semantics of particular implementation languages such as C [26] or operate at the low level of bytecode [24]. The flexibility of TLA+ ’s specification language simplifies Quartz’s task of generating a formal contract specification. This becomes especially important when describing the execution semantics of Solidity, which have important differences from the semantics of traditional programming languages. Moreover, there are ongoing efforts to modernize verification in TLA+ , such as symbolic model checking with SMT solvers [32], that Quartz may be able to use in the future.

Specification Generation

Quartz’s specification generator targets PlusCal, an intermediate language built on top of the original TLA+ specification language.

Quartz is able to translate state machine descriptions to Solidity implementations, enabling seamless deployment once a contract has been sufficiently validated by its developer. Quartz targets Solidity rather than EVM bytecode for several reasons. Solidity is more human readable than EVM bytecode, which means a contract author may easily inspect and audit a generated implementation if necessary. Moreover, there is an ongoing effort within the Ethereum community to replace the original EVM with a new virtual machine based on WebAssembly [20]. By targeting Solidity, Quartz remains agnostic to this potential change.

Core Concepts, Challenges, and Future Directions in Blockchain: A Centralized Tutorial

Contract Security Concerns

Solidity’s syntax and basic execution semantics are, by design, very similar to those of traditional imperative programming languages, but writing a correct and secure smart contract can be challenging. This is because Ethereum’s contract execution model and mining process introduce subtleties to Solidity’s behavior, many of which have no analogues in other programming languages and platforms. Contract developers rely on their prior experiences and intuitions regarding the execution of imperative code, and Solidity’s efforts to present familiar syntax can obscure the underlying blockchain’s true execution semantics. Writing a correct and secure smart contract is particularly important, because smart contracts are immutable. When a new contract is instantiated, its code is stored on the blockchain’s ledger and cannot be changed. In Section 8, we will summarize some of the ongoing efforts to help developers avoid introducing bugs in their smart contracts and to defend their contracts from potential attacks.

TOWARD ROBUST SMART CONTRACTS

Because smart contracts are intended to handle management of data and enforcement of rules in high-stakes situations, and because they are both difficult to implement correctly and impossible to modify once deployed, there is significant interest in applying techniques from formal methods and programming languages research to the domain of smart contracts. The general goal of these efforts is to allow developers to reason about and establish guarantees for the behavior of contracts before they are deployed. This interest further intensified after the theft of funds from TheDAO, a famous contract on the main Ethereum blockchain. Here, we summarize approaches belonging to three categories: formal analysis of existing contract code, translation of contract code into alternative languages that facilitate formal analysis, and alternative languages to express contract logic. We close with a brief discussion of a slightly different approach to contract defense involving bug bounties.

Obsidian: A safer blockchain programming language

Obsidian is a new programming language for writing smart contracts, which are programs for blockchain platforms.

Written in Scala and Java

Ethereum Foundation. The solidity contract-oriented programming language

Ethereum Foundation. The serpent contract-oriented programming language

Pythonic Smart Contract Language for the EVM

Hawk: The Blockchain Model of Cryptography and Privacy-Preserving Smart Contracts

Stand alone compiler for the Sophia smart contract language

Serpent

Serpent is an assembly language that compiles to EVM code that is extended with various high-level features. It can be useful for writing code that requires low-level opcode manipulation as well as access to high-level primitives like the ABI.

Being a low-level language, Serpent is NOT RECOMMENDED for building applications unless you really really know what you’re doing. The creator recommends Solidity as a default choice, LLL if you want close-to-the-metal optimizations, or Viper if you like its features though it is still experimental.

Building Better Systems Podcast: Episode #6 Dan Guido - What the hell are the blockchain people doing & why isn’t it a dumpster fire?


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