CSRE4SOC (CSR evaluation for software companies)
September 27, 2022 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Elisa Jimenez, Coral Calero, Maria Γngeles Moraga
arXiv ID
2209.13372
Category
cs.SE: Software Engineering
Cross-listed
cs.CY
Citations
0
Venue
arXiv.org
Last Checked
5 months ago
Abstract
Software development companies are increasingly concerned about their impact on the environment. This is translated into the incorporation of actions related to software sustainability in their Corporate Social Responsibility (CSR) document. CSR reflects a company's obligations to society and the environment. However, we have found that companies do not always have the necessary knowledge to be able to include actions related to software sustainability. Moreover, there is still a lot of work to be done, as the number of actions they incorporate is often insufficient. Taking all this into account, we consider it essential for software development companies to have a tool that allows them to assess their level of software sustainability, based on the actions of their CSR, and to automatically provide them with a series of improvements to advance their level of software sustainability. Therefore, this paper introduces CSRE4SOC, a tool for the evaluation and monitoring of the software sustainability level of software development companies according to their CSR.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Software Engineering
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Microservices: yesterday, today, and tomorrow
π
π
The Cartographer
A Survey of Machine Learning for Big Code and Naturalness
R.I.P.
π»
Ghosted
An Overview on Smart Contracts: Challenges, Advances and Platforms
R.I.P.
π»
Ghosted
Slither: A Static Analysis Framework For Smart Contracts
R.I.P.
π»
Ghosted
ContractFuzzer: Fuzzing Smart Contracts for Vulnerability Detection
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted