GAS_CASE_STUDIES.md

Gas Optimization Case Studies (Predictify Hybrid)

1) Voting: Avoid per-iteration storage access

Issue: Repeated .get()/.set() inside loops increases read/write entries.

Fix: Read market once, update in-memory, write once.

See the vote implementation which already batches to a single final write:

market.votes.set(user.clone(), outcome);
market.stakes.set(user.clone(), stake);
market.total_staked += stake;
env.storage().persistent().set(&market_id, &market);

Further improvement: Pre-validate outcome using an in-memory set if outcomes are large to avoid repeated scans.

2) Claiming: Scale with participants carefully

Current approach iterates all votes to compute winning_total:

let mut winning_total = 0;
for (voter, outcome) in market.votes.iter() {
    if &outcome == winning_outcome {
        winning_total += market.stakes.get(voter.clone()).unwrap_or(0);
    }
}

Optimizations:

• Maintain stakes_per_outcome totals during vote to avoid O(n) scan at claim time.
• Consider a compact bitmap/flag for claimed to reduce map overhead.

3) Market Creation: Bound string sizes

Cost driver: question and outcomes lengths inflate write-bytes.

Guideline: Enforce caps (e.g., 140/32 chars). Reject overlong inputs to protect fees.

4) Oracle Resolution: Validate before calling

Call the cheapest checks first (staleness, feed format) before cross-contract calls. Skip persistence until a valid result is known.

5) Events over Storage

Emit events for analytics (e.g., vote tally changes) and only persist aggregates needed for on-chain reads.