When implementing algorithms, ensure they handle all edge cases correctly and robustly. Code should gracefully manage exceptional conditions rather than producing incorrect results or panicking.
When implementing algorithms, ensure they handle all edge cases correctly and robustly. Code should gracefully manage exceptional conditions rather than producing incorrect results or panicking.
Key practices:
Test boundary conditions: Verify your algorithm works correctly with empty collections, maximum/minimum values, and other edge cases.
Handle hash functions comprehensively: Include all relevant state in hash functions to prevent unintended collisions.
// Suboptimal: Missing important fields
impl Hash for ImportTask {
fn hash<H: Hasher>(&self, state: &mut H) {
self.key_range.hash(state);
self.path.hash(state);
}
}
// Better: Includes all relevant fields
impl Hash for ImportTask {
fn hash<H: Hasher>(&self, state: &mut H) {
self.shard_identity.hash(state); // Include this for robustness
self.key_range.hash(state);
self.path.hash(state);
}
}
// Problematic: Assumes perfect precision
if total_percentage == 100.0 {
// ...
}
// Better: Use appropriate epsilon or handle the last case separately
let last_variant = variants.last().unwrap();
if mapped_user_id <= total_percentage / 100.0 {
return Some(last_variant.key.clone());
}
// Incorrect: Complex condition with a logic error
if !(plan_hash == progress.import_plan_hash || progress.jobs != plan.jobs.len()) {
anyhow::bail!("Import plan does not match storcon metadata");
}
// Correct: Simplified, clear conditions
if plan_hash != progress.import_plan_hash {
anyhow::bail!("Import plan hash does not match storcon metadata hash");
}
if progress.jobs != plan.jobs.len() {
anyhow::bail!("Import plan job length does not match storcon metadata");
}
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