Uncertainty-aware Model-based Testing Module

Matteo Camilli

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Uncertainty-aware Model-based Testing Module

Matteo Camilli

2019

Handle:

https://hdl.handle.net/10863/27497

Abstract

A Java open-source software implementation of the testing module described in: * Camilli, Matteo, Angelo Gargantini, and Patrizia Scandurra. "Model‐based hypothesis testing of uncertain software systems." Software Testing, Verification and Reliability 30.2 (2020): e1730. The repository contains: * testing module for uncertain software systems; * sources and working examples.

Files and links (1)

url

https://github.com/SELab-unimi/mbt-moduleView

Details

Title: Uncertainty-aware Model-based Testing Module
Creators: Matteo Camilli
Identifiers: (UNIBZ)38470257
991006483997701241
Academic Unit: Faculty of Computer Science
Language: English
Resource Type: Code
Author Names String: Camilli M
Additional Description: description: Model-based Testing software tailored to uncertainty as a first-class concern in order to quantify it and deliver increased confidence in the level of assurance of the target software system. It uses novel model-based exploration strategies that generate test cases targeting uncertain components of the system under test. It leverages Markov Decision Processes as modeling formalism of choice. The tester explicitly specifies uncertainty by means of beliefs attached to transition probabilities. The structural properties of the model and the uncertainty specification are then exploited to drive the test case generation process. Bayesian inference is used to achieve this objective by updating the initial beliefs through the evidence collected by testing.

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