Bounty Platform: Rewards for Validated Solutions

A decentralized platform to fund development through open competition, where funds are released only when a specific problem is solved. It integrates automated cryptographic proofs (via Celaut Services) and/or human arbitration.

General Workflow

Bounty Creation

A creator defines a problem (e.g., "Develop library X for Ergo") and configures:

• A Test Service: Specification of a service to validate solutions (e.g., obfuscated unit tests).
• Arbitration Mechanism (optional): Addresses of judges (n/m multisig) or integration with a reputation panel.

A smart contract is deployed on Ergo with the initial reward (if any).

Contributions

Anyone can add funds (ERG/tokens) to the contract to increase the reward. In return, contributors may receive CATs if a developer successfully implements a valid solution.

• No maximum limit: The reward grows as long as no valid solution exists. (Technically, a solution must eventually be submitted.)

Solution Submission

1. Developer A runs the Test Service locally.
2. If the test passes, they generate a cryptographic proof (e.g., a secret key unlocked by the service).
3. They submit a transaction to Ergo with this proof, partially spending the contract and creating a pending validation box.
4. Developer B can attempt the same, but if their proof is invalid, the transaction will be rejected.

Final Validation

• If there are judges:
  • The pending validation box requires signatures from n/m judges (e.g., 3 out of 5).
  • Judges review the solution (code, documentation, etc.) and sign off if it's correct.
  • The Sigma Reputation Panel can be used to prevent collusion (public reputation for judges).
• If fully automated:
  • The cryptographic proof alone is sufficient to release the funds.

Reward

• Once validated, the funds are sent to the successful developer (minus a dev_fee for the contract creator, as in Bene).
• If no one solves the problem before the block limit, contributors can claim refunds.

Use Cases

Library Development

• Contributors fund a reward for implementing a specific function.
• The Test Service automatically verifies performance and compatibility.
• Judges validate code quality before releasing funds.

Security Audits

• A DAO offers rewards for discovering vulnerabilities in a contract.
• The Test Service attempts to exploit flaws; whoever succeeds generates a proof and claims the reward.

Advantages

• Efficient Incentives: Funds are released only for verifiable results.
• Total Transparency: Proofs and arbitration occur on-chain.
• Flexibility: From automated tests to reputation-based juries.
• No Intermediaries: Logic is implemented in Ergo contracts.

Challenges and Solutions

Test Service Obfuscation

• The test service must be opaque to prevent developers from reverse-engineering validation criteria.

Fair Arbitration

• Integration with the Sigma Reputation Panel to penalize malicious judges.

Overcompetition

• Multiple developers may submit solutions almost simultaneously. Resolved by a "first-to-validate" approach (?).

Automated Verification vs. Human Judges

Automated Verification

• Pros:
  • Removes human subjectivity.
  • Relies on unit tests or formal proofs.
• Cons:
  • Can be cheated if tests are not comprehensive.
  • Writing good tests can be as hard as solving the task itself.

Human Judges

• Pros:
  • More flexible for complex tasks.
• Cons:
  • Requires trust or a decentralized reputation system.
  • Takes time for proper evaluation.

Hybrid Approach

• Combine automated verification with judge oversight.
• Use automated tests as a first filter, with judges making final approvals.

Future Extensions

• Partial Bounties: Tiered rewards for intermediate milestones.

Conclusion

The Bounty Platform transforms development funding into a transparent and competitive process where technical merit is directly rewarded. By combining Celaut for automated testing and Ergo for ensuring transparency, it eliminates distrust in project execution, focusing on results rather than promises. The system provides flexibility, allowing both automated and human verification mechanisms to coexist and complement each other, ensuring a robust and fair bounty system.

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Criticisms to Consider

1. Cost of Unit Tests/Formal Proofs

• Writing unit tests can be as difficult as solving the task itself.
• Defining formal properties to ensure solution correctness is complex and prone to omissions.
• It may be possible to "cheat" by implementing something that passes the tests without truly solving the problem.

2. Cost of Evaluation by Judges

• Reviewing solutions requires significant time and effort.
• Trust in judges or a reputation system is needed to prevent corruption or arbitrariness.
• There may be delays in validation if judges do not act quickly.

Both approaches have associated costs, so a hybrid system could help mitigate these issues by combining automation with human review when necessary.