Owing to the critical role of software-intensive systems in society, software engineers have the accountability to consider sustainability as a goal while structuring a software system. However, there are no practical guidelines providing a tangible decomposition of the sustainability aspect. Moreover, there are limited quantifiable methods to support sustainable design and analysis.

The purpose of this study is to help software practitioners to take sustainability into account by providing systematic guidelines for the software engineering process. We propose a framework that presents a meta model to decompose sustainability requirements and an assessment approach to evaluate sustainability achievements.

This work presents an integrated framework that combines a goal-based approach, scenario-based approach, and feature modeling to gather sustainability related requirements and corresponding features. For sustainability assessment, software analysis and machine learning techniques are utilized to analyze software products based on sustainability metrics and criteria.

The empirical study conducted with participants from academia and industry revealed that the proposed framework improves participant’s ability to consider sustainability aspect in their software engineering tasks through focusing on requirements, design, and evaluation. With the provided sustainability meta-model, the participants could extract more stakeholders, requirements, and features in shorter time. Moreover, the empirical study result also demonstrated that this study is capable to indicate specific scenarios that should be redesigned to improve the sustainability achievements level.