use crate::{llm::LLMManager, Result, ShieldContractError};
use serde::{Deserialize, Serialize};
use std::path::Path;
pub struct Optimizer {
platform: String,
ai_enabled: bool,
llm_manager: Option<LLMManager>,
focus_areas: Vec<String>,
}
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct OptimizationSuggestion {
pub id: String,
pub title: String,
pub description: String,
pub category: String,
pub performance_gain: f32,
pub implementation_difficulty: Difficulty,
pub code_before: String,
pub code_after: String,
pub explanation: String,
}
#[derive(Debug, Clone, Serialize, Deserialize)]
pub enum Difficulty {
Easy,
Medium,
Hard,
}
impl Optimizer {
pub fn new(platform: &str) -> Result<Self> {
Ok(Self {
platform: platform.to_string(),
ai_enabled: false,
llm_manager: None,
focus_areas: vec![],
})
}
pub fn enable_ai_suggestions(&mut self, llm_manager: LLMManager) {
self.ai_enabled = true;
self.llm_manager = Some(llm_manager);
}
pub fn set_focus_areas(&mut self, areas: Vec<String>) {
self.focus_areas = areas;
}
pub async fn analyze(&self, path: &Path) -> Result<Vec<OptimizationSuggestion>> {
let content = tokio::fs::read_to_string(path).await?;
let mut suggestions = Vec::new();
match self.platform.to_lowercase().as_str() {
"fabric" => {
suggestions.extend(self.analyze_fabric_optimizations(&content).await?);
}
_ => {
suggestions.extend(self.analyze_generic_optimizations(&content).await?);
}
}
if !self.focus_areas.is_empty() {
suggestions.retain(|s| {
self.focus_areas
.iter()
.any(|area| s.category.to_lowercase().contains(&area.to_lowercase()))
});
}
if self.ai_enabled && self.llm_manager.is_some() {
}
Ok(suggestions)
}
async fn analyze_fabric_optimizations(
&self,
content: &str,
) -> Result<Vec<OptimizationSuggestion>> {
let mut suggestions = Vec::new();
if content.matches("GetState").count() > 5 {
suggestions.push(OptimizationSuggestion {
id: "FABRIC-OPT-001".to_string(),
title: "Batch GetState operations".to_string(),
description: "Multiple GetState calls can be batched for better performance"
.to_string(),
category: "State Management".to_string(),
performance_gain: 30.0,
implementation_difficulty: Difficulty::Medium,
code_before: r#"
balance1 := stub.GetState("account1")
balance2 := stub.GetState("account2")
balance3 := stub.GetState("account3")
"#
.to_string(),
code_after: r#"
keys := []string{"account1", "account2", "account3"}
balances := make(map[string][]byte)
for _, key := range keys {
balances[key] = stub.GetState(key)
}
"#
.to_string(),
explanation: "Batching state reads reduces round trips to the state database"
.to_string(),
});
}
if content.contains("GetQueryResult") {
suggestions.push(OptimizationSuggestion {
id: "FABRIC-OPT-002".to_string(),
title: "Replace rich queries with composite keys".to_string(),
description: "Rich queries are not performant in production".to_string(),
category: "Query Optimization".to_string(),
performance_gain: 50.0,
implementation_difficulty: Difficulty::Hard,
code_before: r#"
query := `{"selector":{"type":"asset","owner":"Alice"}}`
resultsIterator := stub.GetQueryResult(query)
"#
.to_string(),
code_after: r#"
compositeKey, _ := stub.CreateCompositeKey("type~owner", []string{"asset", "Alice"})
resultsIterator := stub.GetStateByPartialCompositeKey("type~owner", []string{"asset"})
"#
.to_string(),
explanation: "Composite keys provide deterministic and performant queries"
.to_string(),
});
}
if content.contains("for ") && content.contains("json.Marshal") {
suggestions.push(OptimizationSuggestion {
id: "FABRIC-OPT-003".to_string(),
title: "Move JSON marshaling outside loops".to_string(),
description: "JSON operations in loops impact performance".to_string(),
category: "Data Processing".to_string(),
performance_gain: 20.0,
implementation_difficulty: Difficulty::Easy,
code_before: r#"
for _, item := range items {
data, _ := json.Marshal(item)
stub.PutState(item.ID, data)
}
"#
.to_string(),
code_after: r#"
// Pre-process all items
dataMap := make(map[string][]byte)
for _, item := range items {
data, _ := json.Marshal(item)
dataMap[item.ID] = data
}
// Batch write
for id, data := range dataMap {
stub.PutState(id, data)
}
"#
.to_string(),
explanation: "Separating processing from I/O operations improves performance"
.to_string(),
});
}
Ok(suggestions)
}
#[allow(dead_code)]
async fn analyze_ethereum_optimizations(
&self,
content: &str,
) -> Result<Vec<OptimizationSuggestion>> {
let mut suggestions = Vec::new();
if content.contains("storage") && content.contains("=") {
suggestions.push(OptimizationSuggestion {
id: "ETH-OPT-001".to_string(),
title: "Optimize storage usage".to_string(),
description: "Pack struct variables to save gas".to_string(),
category: "Gas Optimization".to_string(),
performance_gain: 15.0,
implementation_difficulty: Difficulty::Medium,
code_before: "// Ethereum-specific optimization".to_string(),
code_after: "// Packed structs".to_string(),
explanation: "Storage is expensive on Ethereum".to_string(),
});
}
Ok(suggestions)
}
async fn analyze_generic_optimizations(
&self,
content: &str,
) -> Result<Vec<OptimizationSuggestion>> {
let mut suggestions = Vec::new();
if content.contains("append") && content.contains("for ") {
suggestions.push(OptimizationSuggestion {
id: "GEN-OPT-001".to_string(),
title: "Pre-allocate slices".to_string(),
description: "Pre-allocating slices avoids repeated allocations".to_string(),
category: "Memory Management".to_string(),
performance_gain: 10.0,
implementation_difficulty: Difficulty::Easy,
code_before: r#"
var results []Item
for _, item := range items {
results = append(results, processItem(item))
}
"#
.to_string(),
code_after: r#"
results := make([]Item, 0, len(items))
for _, item := range items {
results = append(results, processItem(item))
}
"#
.to_string(),
explanation: "Pre-allocation reduces memory allocations and improves performance"
.to_string(),
});
}
Ok(suggestions)
}
pub async fn apply_suggestions(&self, suggestions: &[OptimizationSuggestion]) -> Result<usize> {
Ok(0)
}
}