During the development of Timeline Social, one significant hurdle we encountered was ensuring data consistency and synchronization across a decentralized network. Traditional social media platforms rely on centralized databases to manage and synchronize user data, but in a decentralized system, achieving this is more complex due to the distributed nature of the data.

Specific Bug:

We faced a bug where user posts and interactions were not updating consistently across all nodes. This led to discrepancies where some users could see posts that others could not, or interactions (likes, comments) appeared delayed or out of order.

Solution:

1. Consensus Mechanism: We implemented a robust consensus mechanism using a combination of Proof of Stake (PoS) and Byzantine Fault Tolerance (BFT) algorithms. This ensured that all nodes agreed on the state of the network before any updates were confirmed.

2. Conflict Resolution: We designed an efficient conflict resolution protocol to handle data inconsistencies. This involved timestamping every interaction and prioritizing the most recent updates. In cases of conflict, nodes would refer to the timestamp to resolve discrepancies.

3. Data Caching and Synchronization: We introduced local caching mechanisms to temporarily store updates and changes, which were then periodically synchronized with the main network. This reduced the load on the network and helped manage data consistency more effectively.

4. Testing and Debugging: Extensive testing was conducted in simulated environments to identify and fix synchronization issues. We used automated testing tools to replicate various scenarios and ensure the system behaved as expected under different conditions.

By addressing these challenges with a combination of advanced algorithms and thorough testing, we were able to overcome the synchronization issues and ensure a seamless user experience on Timeline Social.