Best Practices & Conventions
Use consistent names and a predictable layout.
Naming Conventions
Recommended naming:
Problem Name, Test Cases, Generators, Solutions: Use
camelCasefor the machine-readable identifier. This name is often used in directory paths, so avoid spaces or special characters.- Good:
aPlusB,newYearGreeting. - Bad:
A + B Problem,new_year_greeting.
- Good:
Traits: Use concise, descriptive
snake_casenames that state the property precisely.- For numeric constraints, prefer
variable_comparison_value, such asn_le_1000,a_ge_100, ora_mod_2_eq_0. - For categorical or structural properties, use an affirmative
is_propertyorvariable_is_propertyname, such asis_treeorn_is_odd. Other concise and descriptive names, such asall_positive, are also appropriate. - Avoid vague names such as
n_is_small,trait1, andsubtask2_property. - Avoid negation in trait names. For example, use
is_tree = falseinstead ofis_not_tree = true.
- For numeric constraints, prefer
Directory Structure
Recommended layout:
A typical problem directory looks like this:
.
├── data/
│ └── 1.in
├── document/
│ └── statement/
│ ├── en.typ
│ └── ...
├── generator/
│ └── rand.23.cpp
├── include/
│ └── problem.23.hpp
├── solution/
│ ├── bf.23.cpp
│ └── std.23.cpp
├── .clang-format
├── .clangd
├── .editorconfig
├── .gitignore
├── checker.23.cpp
├── flake.nix
├── problem.nix
└── validator.23.cppdata/: Manually created test case input files.document/: Source files for generating problem statements (e.g., Typst files).generator/: Source code for test data generators.include/: Shared header files, likeproblem.23.hpp, used by other components.solution/: Source code for all solutions (correct, incorrect, suboptimal).checker.23.cpp: The checker program.validator.23.cpp: The validator program.problem.nix: The central declarative configuration for the problem.flake.nix: The Nix flake definition for the project.
Sharing Problem Definitions
Keep definitions used by both the checker and validator in the matching include/problem.*.hpp, and add ./include to includes in problem.nix. This shared header should be the single source of truth for input models, parsing rules, constraint constants, and other reusable problem structures. Interactive problems should use the same approach for definitions shared by the interactor and validator.
Keep checker.*.cpp, validator.*.cpp, and interactor.*.cpp as thin entry points that include the shared header and register the relevant component. Do not duplicate input structures, bounds, or parsing logic between these programs: duplicated definitions can drift and cause the checker or interactor to interpret input differently from the validator.
Testing Core Components
Your validator and checker are critical pieces of software that can contain bugs. Hull provides a built-in mechanism to write tests for them directly within problem.nix, ensuring they behave as expected.
Testing the Validator and Checker
You can add a tests attribute to your validator and checker definitions. Each test case specifies an input and a prediction function that verifies the program’s output.
# In problem.nix
{
# ...
validator = {
src = ./validator.23.cpp;
tests = {
# Test case with a valid input
valid = {
inputFile = builtins.toFile "invalid.in" "1 2\n";
prediction = { status, traits, ... }:
status == "valid" && traits.a_positive;
};
# Test case with an invalid input
invalid = {
inputFile = builtins.toFile "invalid.in" "1001 1002\n";
prediction = { status, ... }: status == "invalid";
};
};
};
checker = {
src = ./checker.23.cpp;
tests = {
# Test an accepted case
ac = {
inputFile = builtins.toFile "ac.in" "1 2\n";
outputFile = builtins.toFile "ac.out" "3\n";
prediction = { status, ... }: status == "accepted";
};
};
};
# ...
}When you run hull build, these tests are executed automatically. If any prediction fails, the build will stop, alerting you to a potential issue with your validator or checker.
Keep component tests short and focused on plausible defects, such as a missing bound, trailing token, malformed construction, floating-point tolerance boundary, or protocol violation. Do not enumerate the input domain or add tests that only assert constants or implementation shape.
Predicting Solution Behavior
subtaskPredictions checks expected solution behavior.
For a brute-force solution that is expected to be too slow for larger subtasks, you can write a prediction that accepts either “accepted” (for small cases) or “time_limit_exceeded”.
# In problem.nix
{
# ...
solutions = {
std = {
src = ./solution/std.23.cpp;
mainCorrectSolution = true;
subtaskPredictions."0" = { score, ... }: score == 1.0; # Expect AC
};
bruteForce = {
src = ./solution/bf.23.cpp;
subtaskPredictions."0" = { statuses, ... }:
builtins.all (s: s == "accepted" || s == "time_limit_exceeded") statuses;
};
};
# ...
}Code Style
Maintaining a consistent code style is essential for collaboration and long-term maintenance. The Hull template provides configuration files for common formatting and linting tools.
Nix Formatting
The project flake includes a formatter for Nix code using nixfmt-tree. You can format all Nix files in your project by running:
nix fmtC/C++ Development Environment
The template provides configuration files for a consistent C/C++ development experience.
- .clang-format: Defines the code style for
clang-format. - .clangd: Configures the
clangdlanguage server, enabling features like auto-completion and diagnostics. It automatically sets the correct C++ standard based on file extensions (e.g.,.23.cppfor C++ 23).
Reproducible Test Data
Make generator output depend only on its complete command-line argument sequence. Avoid wall-clock seeds, rand, implementation-dependent iteration order, and other runtime state. Running the same generator with the same arguments should produce byte-for-byte identical output.
Give independently variable input dimensions separate generator modes, such as size, value distribution, parity, density, or structural shape. Combine relevant modes systematically and add directed boundary cases; random sampling alone is not coverage.
Use generated inputs by default. Fixed input files remain appropriate for small samples or exceptional constructions that are clearer as literal data. Both sample and sampleLarge are sample groups: sample cases are embedded in generated statements, while sampleLarge cases are distributed without being expanded inline.
Subtasks And Test Coverage
Define subtask membership through precise affirmative traits emitted by the validator. Trait hints are checked author assertions, not a replacement for validator-derived traits. Keep statement constraints, validator conditions, generator arguments, testcase traits, and solution assumptions consistent.
A single-subtask ICPC-style problem often needs roughly 20 to 100 testcases. A problem with many partial-scoring subtasks may need hundreds or thousands. These are guidelines rather than quotas; use the smallest set that strongly covers algorithm branches, boundaries, structural families, and plausible unintended approaches.
Problem scores conventionally total 1.0. Allocate partial scores primarily by difficulty, with modest additional weight when a subtask gives useful insight toward the intended solution. For a problem without partial scoring, prefer one subtask containing every testcase.
Participant Visibility
Keep solutions, generators, validators, checkers, and interactors private unless participants require a specific distributed interface. Statements and required grader headers or libraries are exceptions. Check the generated option reference before setting visibility because component kinds use different option types.
Editor Configuration
The .editorconfig file helps maintain consistent coding styles (like indentation and line endings) across various editors and IDEs.
Version Control
Keep build artifacts and temporary files out of version control.