Precompute and cache

Avoid performing expensive operations repeatedly, especially in hot code paths. Identify operations such as parsing, deserialization, or configuration lookups that can be done once and reused.

Three key strategies:

1. Move computation to initialization: ```go // Inefficient: Parsing on every evaluation func (w *workerQueryEngine) EvaluateWorker(hb *workerpb.WorkerHeartbeat) (bool, error) { query, err := prepareQuery(w.query) // Parsing repeatedly // … }

// Optimized: Parse once during initialization func newWorkerQueryEngine(nsID string, query string) *workerQueryEngine { parsedQuery, _ := prepareQuery(query) // Parse once return &workerQueryEngine{ nsID: nsID, query: query, parsedQuery: parsedQuery, } }

2. **Cache expensive results**:
```go
// Add a TODO for caching deserialized tasks
taskValue, err := deserializeTask(registrableTask, taskInfo.Data)
// TODO: Cache the deserialized task to avoid repeated deserialization

1. Use pointers to existing data: ```go // Inefficient: Creates new allocation return &cv, nil

// Efficient: Returns pointer to existing data return &cvs[idx], nil // Returns pointer into slice, avoiding allocation

4. **Calculate values once and pass as parameters**:
```go
// Inefficient: Repeatedly evaluating expensive config
for _, start := range starts {
    if e.shouldYield(scheduler, *actionsTaken) { // Config lookup each time
        break
    }
    // ...
}

// Efficient: Calculate once and reuse
tweakables := e.Config.Tweakables(scheduler.Namespace)
maxActions := tweakables.MaxActionsPerExecution
for _, start := range starts {
    if *actionsTaken >= maxActions {
        break
    }
    // ...
}

Also consider proper ordering of operations - perform cheap checks before expensive ones. For example, check exclusion conditions before making dynamic config calls.