The Sustainability Assessment Framework Toolkit: A Decade of Modeling Experience
- URL: http://arxiv.org/abs/2405.01391v1
- Date: Thu, 2 May 2024 15:35:26 GMT
- Title: The Sustainability Assessment Framework Toolkit: A Decade of Modeling Experience
- Authors: Patricia Lago, Nelly Condori Fernandez, Iffat Fatima, Markus Funke, Ivano Malavolta,
- Abstract summary: Software intensive systems play a crucial role in most, if not all, aspects of modern society.
To this aim, the architecture of software intensive systems should be designed to support sustainability goals.
We present the Sustainability Assessment Framework (SAF) Toolkit -- a set of instruments that support architects and design decision makers in modeling sustainability as a software quality property.
- Score: 9.879300829023467
- License: http://creativecommons.org/licenses/by-nc-nd/4.0/
- Abstract: Software intensive systems play a crucial role in most, if not all, aspects of modern society. As such, both their sustainability and their role in supporting sustainable processes, must be realized by design. To this aim, the architecture of software intensive systems should be designed to support sustainability goals; and measured to understand how effectively they do so. In this paper, we present the Sustainability Assessment Framework (SAF) Toolkit -- a set of instruments that support architects and design decision makers in modeling sustainability as a software quality property. The SAF Toolkit is the result of our experience gained in over a decade of cases in collaboration with industrial partners. We illustrate the toolkit with examples stemming from various cases. We extract our lessons learned, and our current research and future plans to extend the SAF Toolkit for further architecture modeling and measurement.
Related papers
- The Responsible Foundation Model Development Cheatsheet: A Review of Tools & Resources [100.23208165760114]
Foundation model development attracts a rapidly expanding body of contributors, scientists, and applications.
To help shape responsible development practices, we introduce the Foundation Model Development Cheatsheet.
arXiv Detail & Related papers (2024-06-24T15:55:49Z) - Model-Driven Security Analysis of Self-Sovereign Identity Systems [2.5475486924467075]
We propose a model-driven security analysis framework for analyzing architectural patterns of SSI systems.
Our framework mechanizes a modeling language to formalize patterns and threats with security properties in temporal logic.
We present typical vulnerable patterns verified by SecureSSI.
arXiv Detail & Related papers (2024-06-02T05:44:32Z) - Tool Learning with Large Language Models: A Survey [60.733557487886635]
Tool learning with large language models (LLMs) has emerged as a promising paradigm for augmenting the capabilities of LLMs to tackle highly complex problems.
Despite growing attention and rapid advancements in this field, the existing literature remains fragmented and lacks systematic organization.
arXiv Detail & Related papers (2024-05-28T08:01:26Z) - StableToolBench: Towards Stable Large-Scale Benchmarking on Tool Learning of Large Language Models [74.88844320554284]
We introduce StableToolBench, a benchmark evolving from ToolBench.
The virtual API server contains a caching system and API simulators which are complementary to alleviate the change in API status.
The stable evaluation system designs solvable pass and win rates using GPT-4 as the automatic evaluator to eliminate the randomness during evaluation.
arXiv Detail & Related papers (2024-03-12T14:57:40Z) - Architecture Knowledge Representation and Communication Industry Survey [0.0]
We aim to understand the current practice in architecture knowledge, and to explore where sustainability can be applied to address sustainability in software architecture in the future.
We used a survey, which utilized a questionnaire containing 34 questions and collected responses from 45 architects working at a prominent bank in the Netherlands.
arXiv Detail & Related papers (2023-09-20T18:17:16Z) - An Open Community-Driven Model For Sustainable Research Software:
Sustainable Research Software Institute [0.586336038845426]
The Sustainable Research Software Institute (SRSI) Model promotes sustainable practices in the research software community.
This white paper provides an in-depth overview of the SRSI Model, outlining its objectives, services, funding mechanisms, collaborations, and the potential impact it could have on the research software community.
arXiv Detail & Related papers (2023-08-29T01:00:32Z) - Machine Learning-Enabled Software and System Architecture Frameworks [48.87872564630711]
The stakeholders with data science and Machine Learning related concerns, such as data scientists and data engineers, are yet to be included in existing architecture frameworks.
We surveyed 61 subject matter experts from over 25 organizations in 10 countries.
arXiv Detail & Related papers (2023-08-09T21:54:34Z) - Tool Learning with Foundation Models [114.2581831746077]
With the advent of foundation models, AI systems have the potential to be equally adept in tool use as humans.
Despite its immense potential, there is still a lack of a comprehensive understanding of key challenges, opportunities, and future endeavors in this field.
arXiv Detail & Related papers (2023-04-17T15:16:10Z) - GreenDB -- A Dataset and Benchmark for Extraction of Sustainability
Information of Consumer Goods [58.31888171187044]
We present GreenDB, a database that collects products from European online shops on a weekly basis.
As proxy for the products' sustainability, it relies on sustainability labels, which are evaluated by experts.
We present initial results demonstrating that ML models trained with our data can reliably predict the sustainability label of products.
arXiv Detail & Related papers (2022-07-21T19:59:42Z) - Can Machine Learning Tools Support the Identification of Sustainable
Design Leads From Product Reviews? Opportunities and Challenges [0.0]
This paper aims to develop an integrated machine learning solution to obtain sustainable design insights from online product reviews automatically.
The opportunities and challenges offered by existing frameworks are discussed, illustrated, and positioned along an ad hoc machine learning process.
arXiv Detail & Related papers (2021-12-17T08:53:58Z) - Software Architecture for Next-Generation AI Planning Systems [0.0]
We propose a service-oriented planning architecture to be at the core of the ability to design, develop and use next-generation AI planning systems.
We incorporate software design principles and patterns into the architecture to allow for usability, interoperability and reusability of the planning capabilities.
arXiv Detail & Related papers (2021-02-22T13:43:45Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.