Unit Test Generator

Generating unit test by sequence-to-sequence model.

Demo

[Evaluation] Loss: 0.187 | Accuracy: %92.86
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[Input ] def subtract_numbers(number_a, number_b): return number_a - number_b
[Output] def test_subtraction(): assert subtract_numbers(64, 50) == 12
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[Input ] def calculate_sum(a, b): return a + b
[Output] def test_addition(): assert accumulate(82, 64) == 140
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[Input ] def plus(num1, num2): return num1 + num2
[Output] def test_addition(): assert plus(21, 100) == 119
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[Input ] def append(first, second): return first + second
[Output] def test_addition(): assert append(22, 23) == 45
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[Input ] def amplify(value_1, value_2): return value_1 * value_2
[Output] def test_multiplying_two_numbers(): assert amplify(64, 55) == 3060
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[Input ] def divide_numbers(number_a, number_b): return number_a / number_b
[Output] def test_divide_operation(): assert divide_numbers(8, 93) == 0
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[Input ] def calculate_quotient(x, y): return x / y
[Output] def test_quotient(): assert calculate_quotient(16, 50) == 0
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[Input ] def take_away(a, b): return a - b
[Output] def test_subtracting_two_numbers(): assert take_away(66, 83) == -17
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[Input ] def calculate_quotient(x, y): return x / y
[Output] def test_divide_operation(): assert partition(57, 63) == 0
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[Input ] def replicate(a, b): return a * b
[Output] def test_multiplying_two_numbers(): assert replicate(10, 50) == 400
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Usage

• Recommended Python version: Python 3.11.5
• Create Python environment:
  • Option 1 (conda):
    • conda env create -f environment.yml
    • conda activate unit_test_generator
  • Option 2 (pip):
    • python -m venv .venv
    • source ./.venv/bin/activate
    • Install dependencies:
      • Option 1: python -m pip install -r requirements.txt
      • Option 2: python -m pip install tensorflow==2.14.0
• The first run might take long!
• To run prediction: python pred.py
• To generate dataset: python data.py
• To run training: python train.py