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CRASH Methodology for Correct-by-construction Attack-tolerant Systems

Background

Our method uses formal proofs of high-level system requirements then synthesizes code from the proofs. Within our method we use the following concepts:

The main tool we use is EventML which is a programming and specification language. EventML, built by Vinvent Rahli, cooperates with the Nuprl interactive theorem prover at every stage of program development to help programmers ensure correctness, document the code, and support modifications and improvements. It generates an Inductive Logical Form that proves the specification and can also automatically synthesize code.

Code diversity is created during the process. We can introduce variants at: EventML specification, and code synthesis.

For more details about the example below see Mark's presentation at the May 2012 CRASH meeting.

Methodology

To create correct-by-construction code we:

  1. Write the specification in EventML
  2. Automatically generate and prove an Inductive Logical Form of the specification
  3. Synthesize code
  4. Diversify and deploy code

Example with Consensus

In this example we will look at Paxos consensus, focusing on specifying the Scout protocol.

Step 1 - We write the Scout specification in EventML

Step 2 - Generate the Inductive Logical Form (ILF)from the Scout specification

Using EventML's interface with Nuprl, we generate the ILF. If there are any issues with the proof we revise the specification and reiterate the process with the ILF.

Step 3 - Synthesize Consensus Code

Using EventML's correct-by-construction synthesizer we generate code from the specification.

Step 4 - Diversify & Deploy

Engaging our diversity in classes and state machines we generate multiple verified versions of the code. Then the final step before deployment is to test the code in the EventML simulator.

Example Deployment: ShadowDB

ShadowDB is a replicated database we created on top of a synthesized consensus core. The primary defines the order in which transaction updates are applied. When crashes occur, consensus is used to reconfigure the set of replicas and agree on a prefix of executed transactions.

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