Open AccessUsing Bayesian Networks to Support Managing Technological Risk on Software Projects
Author(s) -
Emanuel Dantas,
Ademar França de Sousa Neto,
Mirko Perkusich,
Hyggo Almeida,
Angelo Perkusich
Publication year - 2021
Language(s) - English
Resource type - Conference proceedings
DOI - 10.5753/ise.2021.17277
Subject(s) - bayesian network , computer science , risk management , software , domain (mathematical analysis) , risk analysis (engineering) , software project management , focus (optics) , software engineering , software development , data science , knowledge management , software construction , artificial intelligence , business , mathematical analysis , physics , mathematics , finance , optics , programming language
Risk management is essential in software project management. It includes activities such as identifying, measuring and monitoring risks. The literature presents different approaches to support software risk management. In particular, the researchers popularly used Bayesian Networks because they can be learned from data or elicited from domain experts. Even though the literature presents many Bayesian networks (BN) for software risk management, none focus on technological risk factors. Given this, this paper presents a BN for managing risks of software projects and the results of a static validation performed through a focus group with eight practitioners. As a result, the practitioners agreed that our proposed to manage technological risks of software projects using BN is valuable and easy to use. Given the successful results, we concluded that the proposed solution is promising.