selveri 0.9.3

SelVeri: Self-Verifying Programming Language

SelVeri : Self-Verifying Programming Language

SelVeri is an educational, imperative programming language designed to bridge the gap between sequential programming and formal methods.

Unlike traditional languages that rely on runtime errors or unit tests to catch bugs, SelVeri employs Dynamic Verification by utilizing its First-Order Logic Runtime Engine. SelVeri integrates the Z3 SMT Solver directly into its runtime. This allows developers to embed complex mathematical and logical specifications—including quantifiers ($\forall, \exists$) and logical implications—which are verified in real-time as the program executes.

Source layout

Python package root: src/selveri/

src/selveri/
├── __init__.py
├── __main__.py              # python -m selveri
├── cli.py                   # CLI entry (parse → compile → run)
│
├── common/                  # shared infrastructure
│   ├── diagnostics.py       # source spans, rendered errors
│   ├── errors.py            # SelVeriError hierarchy
│   ├── runtime.py           # State, Scope, DeclType
│   └── types.py             # shared scalars (e.g. real = float)
│
├── high_level/              # .svi source language
│   ├── ast.py               # HL AST nodes
│   ├── parser.py            # Lark parser, parse_selveri
│   ├── preprocessor.py      # {spec} extraction
│   └── grammars/
│       └── grammar.lark
│
├── spec/                    # specification / annotation language
│   ├── models.py            # Spec, RawSpec, domains
│   ├── parser.py            # parse_spec
│   └── grammars/
│       └── spec_grammar.lark
│
├── compiler/                # high-level AST → SelVerIR
│   └── compiler.py
│
├── ir/                      # intermediate representation
│   ├── instr.py             # IRInstr
│   └── text.py              # IR text parse/serialize helpers
│
├── abstract_machine/        # SelVerIR interpreter (VM)
│   ├── config.py            # RuntimeConfiguration
│   └── interpreter.py
│
└── verifier/                # Z3 / LTL verification engine
    ├── engine.py            # VerificationEngine
    ├── z3_mapper.py
    ├── future_mapper.py
    ├── future_automaton.py
    └── models.py            # FutureAutomaton, obligations, …

Pipeline flow: high_level → compiler → ir → abstract_machine, with spec + verifier hooked into compile/run, and common used throughout.

Setup

Create a Virtual Environment (Optional):

python -m venv .venv
.\.venv\Scripts\activate (for Windows)
source .\.venv\Scripts\activate (for Linux/MacOS)

Install dependencies:

pip install -r requirements.txt

Or install the project in editable mode to enable the selveri command:

pip install -e .

Future LTL (fLTL) and MONA

Specs using temporal operators such as Eventually, Always, and Until are verified by compiling an automaton through MONA. The mona executable must be on your PATH; otherwise SelVeri raises a verification error for those specs.

Linux (Debian/Ubuntu) — MONA is packaged as mona in the universe repository:

sudo apt update
sudo apt install mona

macOS / Windows — Install from the official MONA page, or use a Linux environment (WSL on Windows, then follow the Debian/Ubuntu steps).

To confirm:

mona -h

Run Full Pipeline

Run parser -> compiler -> interpreter from the project root:

python selveri.py examples/example_loop.svi

After editable install, you can use the command directly:

selveri examples/example_loop.svi

By default, IR is not written to disk. To generate .svir output, pass --emit-ir:

selveri examples/example_loop.svi --emit-ir

Or choose a custom path:

selveri examples/example_loop.svi --emit-ir --output-ir out/example_loop.svir

Error Diagnostics

SelVeri reports parser, preprocessor, compiler, runtime, and verification failures as structured diagnostics with source spans, labels, hints, and counterexamples when available.

See docs/errors.md for diagnostic codes, examples, and guidance for adding new errors.

Selveri VsCode Extension

Prerequisites

The selveri Python package and LSP dependencies must be installed in the interpreter used by the extension:

pip install -e <path_to_selveri>
pip install -r vscode-selveri/server/requirements.txt

Build & Install

cd vscode-selveri
npm install
npm run compile
npx vsce package
code --install-extension selveri-0.9.3.vsix

Development

1. Open the vscode-selveri folder in VS Code.
2. Open client/src/extension.ts.
3. Press F5 to launch an Extension Development Host.

Example .vscode/launch.json:

{
  "version": "0.2.0",
  "configurations": [
    {
      "name": "Launch Extension",
      "type": "extensionHost",
      "request": "launch",
      "args": ["--extensionDevelopmentPath=${workspaceFolder}"],
      "outFiles": ["${workspaceFolder}/client/out/**/*.js"]
    }
  ]
}