Performance Smell Detection

// 🔴 Still problematic - new String each iteration
String result = "";
for (String s : items) {
    result += s;  // O(n²) - creates n strings
}

// ✅ StringBuilder for loops
StringBuilder sb = new StringBuilder();
for (String s : items) {
    sb.append(s);
}
String result = sb.toString();

// ✅ Or use String.join / Collectors.joining
String result = String.join("", items);

// ✅ Fine in Java 9+ - JVM optimizes this
String message = "User " + name + " logged in at " + timestamp;

// ✅ Also fine
return "Error: " + code + " - " + description;

// 🟡 String.format has parsing overhead
log.debug(String.format("Processing %s with id %d", name, id));

// ✅ Parameterized logging (SLF4J)
log.debug("Processing {} with id {}", name, id);

// 🔴 Stream created per iteration in hot loop
for (int i = 0; i < 1_000_000; i++) {
    boolean found = items.stream()
        .anyMatch(item -> item.getId() == i);
}

// ✅ Pre-compute lookup structure
Set<Integer> itemIds = items.stream()
    .map(Item::getId)
    .collect(Collectors.toSet());

for (int i = 0; i < 1_000_000; i++) {
    boolean found = itemIds.contains(i);
}

// ✅ Single pass, readable, not in tight loop
List<String> names = users.stream()
    .filter(User::isActive)
    .map(User::getName)
    .sorted()
    .collect(Collectors.toList());

// ✅ Primitive streams avoid boxing
int sum = numbers.stream()
    .mapToInt(Integer::intValue)
    .sum();

// 🔴 Parallel on small collection - overhead > benefit
smallList.parallelStream().map(...);  // < 10K items

// 🔴 Parallel with shared mutable state
List<String> results = new ArrayList<>();
items.parallelStream()
    .forEach(results::add);  // Race condition!

// ✅ Parallel for CPU-intensive + large collections
List<Result> results = largeDataset.parallelStream()  // > 10K items
    .map(this::expensiveCpuComputation)
    .collect(Collectors.toList());

// 🔴 Boxing in tight loop - creates millions of objects
Long sum = 0L;
for (int i = 0; i < 1_000_000; i++) {
    sum += i;  // Unbox, add, box
}

// ✅ Primitive
long sum = 0L;
for (int i = 0; i < 1_000_000; i++) {
    sum += i;
}

// 🟡 Boxing overhead
int sum = list.stream()
    .reduce(0, Integer::sum);

// ✅ Primitive stream
int sum = list.stream()
    .mapToInt(Integer::intValue)
    .sum();

// 🔴 Compiles pattern every iteration
for (String input : inputs) {
    if (input.matches("\\d{3}-\\d{4}")) {  // Compiles regex!
        process(input);
    }
}

// ✅ Pre-compile
private static final Pattern PHONE = Pattern.compile("\\d{3}-\\d{4}");

for (String input : inputs) {
    if (PHONE.matcher(input).matches()) {
        process(input);
    }
}

// 🟢 Low severity - but free optimization if size known
List<User> users = new ArrayList<>(expectedSize);
Map<String, User> map = new HashMap<>(expectedSize * 4 / 3 + 1);

// 🟡 O(n) lookup in loop
List<String> allowed = getAllowed();
for (Request r : requests) {
    if (allowed.contains(r.getId())) { }  // O(n) each time
}

// ✅ O(1) lookup
Set<String> allowed = new HashSet<>(getAllowed());
for (Request r : requests) {
    if (allowed.contains(r.getId())) { }  // O(1)
}

// 🔴 Memory risk - could grow unbounded
@GetMapping("/users")
public List<User> getAllUsers() {
    return userRepository.findAll();  // Millions of rows?
}

// ✅ Pagination
@GetMapping("/users")
public Page<User> getUsers(Pageable pageable) {
    return userRepository.findAll(pageable);
}

// 🟡 Traditional thread pool for I/O - wastes OS threads
ExecutorService executor = Executors.newFixedThreadPool(100);
for (Request request : requests) {
    executor.submit(() -> callExternalApi(request));  // Blocks OS thread
}

// ✅ Virtual threads - millions of concurrent I/O operations
try (ExecutorService executor = Executors.newVirtualThreadPerTaskExecutor()) {
    for (Request request : requests) {
        executor.submit(() -> callExternalApi(request));
    }
}

// ✅ Structured concurrency for parallel I/O
try (StructuredTaskScope.ShutdownOnFailure scope = new StructuredTaskScope.ShutdownOnFailure()) {
    Future<User> user = scope.fork(() -> fetchUser(id));
    Future<Orders> orders = scope.fork(() -> fetchOrders(id));

    scope.join();
    scope.throwIfFailed();

    return new UserProfile(user.resultNow(), orders.resultNow());
}

# Find regex in loops (potential compile overhead)
grep -rn "\.matches(\|\.split(" --include="*.java"

# Find potential boxing (Long/Integer as variables)
grep -rn "Long\s\|Integer\s\|Double\s" --include="*.java" | grep "= 0\|+="

# Find ArrayList without capacity
grep -rn "new ArrayList<>()" --include="*.java"

# Find findAll without pagination
grep -rn "findAll()" --include="*.java"