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A Data-driven Approach For Estimating/Evaluating Software Testability

License: MIT License

Python 100.00%

adafest's Introduction

ADAFEST

ADAFESTLOGO

A Data-Driven Approach For Estimating Software Testability

Connecting runtime information to the static properties of the program is a key point in measuring software quality, including testability. Despite a large number of researches on software testability, we observed that the relationship between testability and test adequacy criteria had not been studied, and testability metrics still are far from measuring the actual testing effort. We hypothesize that testability has a significant impact on automatic testing tools. Therefore, we propose a new methodology to measure and quantify software testability by exploiting both runtime information and static properties of the source code.

Release date

The full version of source code will be available as soon as the relevant paper(s) are published.

Read more

Visit the project website at https://m-zakeri.github.io/ADAFEST

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