This Zig code provides a function `concatenateStrings` that merges two optional string slices into a single, newly allocated string. It uses a provided `Allocator` to manage memory for the result, ensuring it's null-term...

The `concatenateStrings` function takes an `Allocator` and two optional string slices (`?[]const u8`). It first determines the lengths of the input strings, treating null pointers as empty strings (length 0). It then allocates enough memory from the provided `allocator` to hold both strings plus a null terminator (`\0`). The contents of the input strings are copied into the newly allocated buffer using `std.mem.copy`. Finally, a null terminator is placed at the end of the buffer, and the resulting slice is returned. The `main` function demonstrates its usage with a `GeneralPurposeAllocator`, including handling optional inputs and freeing the allocated memory. The time complexity is O(N+M) where N and M are the lengths of the input strings, due to copying. Space complexity is O(N+M) for the new string.

function concatenateStrings(allocator, string1, string2): length1 = length of string1, or 0 if null/empty length2 = length of string2, or 0 if null/empty total_length = length1 + length2 // Allocate memory for the result...

This Zig code defines a function `parseHeader` that reads and validates a simple network protocol header from a byte slice. It utilizes Zig's error union feature to signal various parsing failures, such as incorrect magi...

The `parseHeader` function takes a byte slice `data` and attempts to interpret it as a `Header` struct. It first checks if the input data is at least the size of the `Header` struct. Then, it uses `std.io.BinaryReader` to sequentially read the `magic` number (u32), `version` (u16), and `payload_len` (u32). Each read operation can return an error, which is propagated using the `try` keyword. Specific checks are performed for the `magic` number and `version`. Finally, it verifies if the total data length matches the header size plus the declared `payload_len`. If any check fails, a specific `ProtocolError` is returned. The `main` function demonstrates calling `parseHeader` with valid and invalid data, showcasing error handling.

Define ProtocolError enum (InvalidMagic, InvalidVersion, UnexpectedEndOfData, BufferTooSmall) Define Header struct (magic: u32, version: u16, payload_len: u32) function parseHeader(data: byte array) returns Header or Pro...

This Zig code implements a lock-free queue using atomic operations. A lock-free data structure allows multiple threads to access it concurrently without using traditional locks (like mutexes), which can prevent deadlocks...

The `LockFreeQueue` uses a linked list approach with `head` and `tail` pointers. Both `head` and `tail` are pointers to `Node`s, which contain a value and a pointer to the next node. `init` sets both `head` and `tail` to `null`. `deinit` iterates through the list and frees each node. The `enqueue` operation creates a new node. It then enters a loop, attempting to atomically update the `next` pointer of the current tail node and then the `tail` pointer itself. It uses `std.atomic.cmpxchg` (compare-and-swap) to ensure that these updates happen only if the pointers haven't changed since they were read, preventing race conditions. If the queue is empty, `head` and `tail` point to the same node. The `dequeue` operation reads the `head` and `next` pointers. It checks if the queue is empty (`head == tail` and `next == null`). If not empty, it attempts to atomically update the `head` pointer to the `next` node. If successful, it frees the old head node and returns its value. The use of `cmpxchg` with `Acquire` and `Release` memory orders ensures proper visibility of memory operations between threads. Time complexity for `enqueue` and `dequeue` is O(1) amortized, as contention can lead to retries. Space complexity is O(N) for N elements in the queue.

Node struct: value (integer), next (pointer to Node) LockFreeQueue struct: head (pointer to Node), tail (pointer to Node) init(): head = null tail = null return LockFreeQueue deinit(): current = head while current is not...

This Zig code implements a simple arena allocator. An arena allocator is a memory management technique where memory is allocated from a large pre-allocated block (the arena). Unlike traditional allocators, individual all...

The `ArenaAllocator` struct manages a contiguous block of memory. The `init` function allocates the memory block and initializes the `current` pointer to the beginning. The `alloc` function calculates the aligned size needed, checks for sufficient capacity, and returns a slice from the `memory` array, advancing the `current` pointer. Crucially, `dealloc` is a no-op, as individual deallocations are not supported. The `reset` function simply sets `current` back to 0, effectively making all previously allocated memory available again. The `createAndUseArena` function demonstrates allocation, including an out-of-memory scenario, and resetting the arena. Time complexity for `alloc` is O(1) as it's just pointer arithmetic and a capacity check. Space complexity is O(N) where N is the arena's capacity. Edge cases include attempting to allocate more memory than available and ensuring correct alignment.

ArenaAllocator: memory: byte array current_offset: integer capacity: integer init(capacity): allocate memory block of capacity return ArenaAllocator with memory, current_offset=0, capacity deinit(): free memory block all...

This Zig code defines a `build.zig` file, which is the build script for a Zig project. It demonstrates how to create a custom build pipeline that compiles a main executable and a separate static library. The script defin...

The `build.zig` file's `build` function is the entry point for the Zig build system. It receives a `*Build` object, which provides methods for defining build targets, optimization levels, executables, libraries, and build steps. `b.standardTargetOptions` and `b.standardOptimizeOption` are helpers to get common configurations. `b.addExecutable` and `b.addStaticLibrary` define the artifacts to be built. `exe.addModule` links the library as a dependency for the executable. `b.step` defines custom build steps, and `dependOn` establishes dependencies between them. `b.installArtifact` specifies files to be installed. The `addMyLibrary` helper function encapsulates the logic for building the static library. The example also includes conceptual steps for running a build-time tool (`addRunArtifact`) and potentially generating code. The `b.default_step` sets the primary action when the build command is run without arguments. Time complexity is dominated by the compiler's execution. Space complexity is related to the build artifacts and intermediate files.

function build(build_system): get target and optimize options // Build main executable executable = addExecutable("my_app", "src/main.zig") set target and optimize for executable // Build secondary library library = addS...

This Zig code implements a basic thread pool. A thread pool is a collection of pre-created worker threads that can execute tasks concurrently. Instead of creating a new thread for each task, tasks are submitted to a queu...

The `ThreadPool` struct manages worker threads, a task queue, and synchronization primitives. `init` creates a specified number of worker threads, each running `worker_thread`. `worker_thread` loops, acquiring a mutex, waiting on a condition variable if the queue is empty (and shutdown is not requested), then dequeuing a `Task`. If shutdown is requested and the queue is empty, the thread exits. Otherwise, it executes the task's function. `submit` adds a task to the queue, locks the mutex, appends the task, unlocks, and signals the condition variable to wake a waiting worker. `shutdown` sets a flag, broadcasts to all workers to wake them up, and then `join`s each worker thread to ensure they have completed. The `Task` struct holds a function pointer and its associated data. Time complexity for submitting a task is O(1) amortized (due to `ArrayList` resizing). Task execution time depends on the task itself. Space complexity is O(N + T) where N is the number of threads and T is the maximum number of tasks in the queue.

Task struct: func (function pointer), data (anytype) ThreadPool struct: allocator, workers (list of threads), task_queue (list of Tasks), queue_mutex, queue_cond, shutdown_requested (boolean) init(allocator, num_threads)...

This Zig program demonstrates asynchronous programming using channels for inter-task communication. A `producer` task generates numbers and sends them through a channel, while a `consumer` task receives and prints these...

The `producer` function is an `async` task that sends `count` integers through a `std.async.Channel`. It iterates, sends each number using `channel.send()`, and simulates work with `std.time.sleep()`. If `send` fails (e.g., channel is full and not being read from, or closed), it prints an error and exits. After sending all numbers, it closes the channel using `channel.close()`. The `consumer` function is another `async` task that continuously receives values from the channel using `channel.receive()`. The `while (channel.receive()) |value|` loop automatically terminates when the channel is closed and empty. It prints received values and simulates work. The `main` function initializes an allocator, creates a buffered channel, spawns the `producer` and `consumer` tasks using `std.async.spawn`, and then waits for both tasks to complete using `std.async.wait`. The channel's buffer size prevents the producer from blocking indefinitely if the consumer is slower, and `channel.close()` signals the end of data. Time complexity is dependent on the number of items and sleep durations, but channel operations are typically O(1) amortized. Space complexity is O(B) for the channel buffer, where B is the buffer size.

Define producer(channel, count): print "Producer started." for i from 0 to count-1: print "Producer sending: i" send i to channel if send fails, print error and return sleep for a short duration print "Producer finished....