Zignet

# Advanced Zig Test Report **Model**: mistral:7b **Date**: 2025-10-26T11:44:02.261Z **Total Tests**: 6 **Passed**: 6 **Failed**: 0 **Average Response Time**: 37.61s ## Results ### 1. Basic Zig Syntax [EASY] **Status**: ✅ PASS **Time**: 21.03s **Response**: ```zig Here is a simple Zig function in Zig that returns the sum of two integers: ```zig const std = @import("std"); pub fn main() !void { const a = 5; const b = 10; const sum = _sum(a, b); std.io.putln!("The sum of {} and {} is {}", a, b, sum); } pub fn _sum(x: i32, y: i32) i32 { return x + y; } ``` In this example, the function `_sum` takes two `i32` integers as arguments and returns an `i32` result. The main function demonstrates how to use this sum function with some sampl ``` ### 2. Memory Allocation [EASY] **Status**: ✅ PASS **Time**: 69.88s **Response**: ```zig In Zig, you can create an allocator for custom data types. Here's a simple example of an allocator for integers: ```zig const std = @import("std"); const stdio = @import("std/stdio"); pub const MyIntAllocator = struct { .data: *u8, .capacity: u64, .size: u64, }; fn initMyIntAllocator(alloc: *std.system.Allocator) MyIntAllocator { var result = undefined; try @alloc.alloc(szOf<MyIntAllocator>()) with drop(result) { result.data = alloc.asPtr(); result.capaci ``` ### 3. Error Handling [MEDIUM] **Status**: ✅ PASS **Time**: 44.84s **Response**: ```zig In Zig, the `Result` type is not built-in but can be easily defined using enums and tuples. Here's an example of a custom Result type implementation: ```zig const std = @import("std"); enum Error { Success, CustomError = i32, // You can define your own custom error codes here } pub struct Result { kind: Error, value: anyptr, } fn newResult(kind: Error, value: anyptr) Result { var _res = try alloc(Result); _res.kind = kind; _res.value = value; return _res; } ``` ### 4. Structs & Methods [MEDIUM] **Status**: ✅ PASS **Time**: 24.04s **Response**: ```zig In Zig language, here's a simple struct for a Point with `x` and `y` coordinates, and a method to calculate the distance from the origin (0, 0). ```zig const Point = struct { x: u64, y: u64, }; fn Point_distanceFromOrigin(point: const Point) u64 { return point.x.squared() + point.y.squared(); } ``` This struct `Point` has two fields `x` and `y` of type `u64`. The function `Point_distanceFromOrigin` takes a constant Point as an argument and returns the square of the distance from ``` ### 5. Generics [HARD] **Status**: ✅ PASS **Time**: 31.72s **Response**: ```zig In Zig, you can create a generic function to find the maximum of two values for various numeric types by using templates. Here's an example of how you might implement it: ```zig pub const std = _builtin; pub fn max(a: T, b: T) !T { if (a > b) { return a; } return b; } template <ty T> struct MaxConstraint { static constexpr bool check(type-param T) = a.compare(b) >= 0; } pub const fn maxTwoValues<T: MaxConstraint>(a: T, b: T) !T { return max(a, b); } ``` This cod ``` ### 6. Comptime Magic [HARD] **Status**: ✅ PASS **Time**: 34.17s **Response**: ```zig In Zig, `comptime` is used for performing computations at compile-time. However, Zig currently doesn't support recursion at compile-time due to its design philosophy of simplicity and performance. To calculate a factorial at compile-time without recursion, we can use loops and bit manipulation techniques. Here's an example of how you might implement a factorial function using `comptime`: ```zig const fn comptime_factorial(n: u64) !comptime(builtin) { if (n == 0) { return 1; } ```