Software Carbon Footprint Reduction via Scenario Segmentation
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Solution Overview
Problem
Software applications generate significant carbon footprints due to their resource-intensive operations, and existing methods lack a systematic approach to quantify and reduce these footprints during the development phase.
Innovation Solution
A method and device that calculate the unitary carbon footprint of each application scenario, estimate the number of executions, and determine a subset of scenarios to modify or remove, using Natural Language Processing to identify keywords and map them to a knowledge database, allowing for targeted reduction of high-impact features before production.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If software applications are developed with comprehensive features, then functionality and usability are improved, but carbon footprint increases
Solution Approach 1:
The patent applies preliminary action by calculating and evaluating the carbon footprint of application scenarios during the test phase, before the application is deployed to production. This allows identifying and removing high-carbon features early in the development cycle, preventing their implementation in the final production version. The method computes unitary carbon footprint for each scenario, estimates execution frequency, and determines a subset of scenarios to modify or remove, thereby reducing overall carbon footprint while preserving essential functionality.
2Reliability
If all application scenarios are tested thoroughly, then testing completeness is improved, but time consumption increases
Solution Approach 1:
The patent segments the application scenarios into distinct categories based on their carbon footprint characteristics. By calculating the unitary carbon footprint for each scenario and estimating execution frequency, the method identifies high-impact scenarios that contribute most to the overall carbon footprint. This segmentation allows prioritizing testing and modification efforts on the most critical scenarios, rather than treating all scenarios uniformly, thereby reducing time consumption while maintaining testing effectiveness.
Solution Approach 2:
The patent changes the parameter of evaluation from traditional functional testing to carbon footprint-based evaluation. By introducing carbon footprint calculation as a selection criterion, the method enables dynamic prioritization of scenarios based on their environmental impact. This parameter change allows the testing process to focus on scenarios with highest carbon footprint, optimizing the balance between testing completeness and time consumption.
3Object-generated harmful factors
If high-carbon features are removed from the application, then carbon footprint is reduced, but functionality may be compromised
Solution Approach 1:
The patent implements feedback by calculating the carbon footprint of each application scenario and using this information to determine which scenarios should be modified or removed. The method provides feedback to developers about the environmental impact of specific features, enabling informed decisions about which functionality to retain and which to eliminate. The feedback loop includes calculating unitary carbon footprint, estimating execution frequency, and determining a subset of scenarios for modification, allowing iterative improvement of the application's carbon footprint while preserving essential functionality.
Data Source
AI summary
A method for reducing the carbon footprint of a software application during a test phase including calculating a unitary carbon footprint of each application scenario of a determined set of application scenarios, estimating the number of executions of the each application scenario of the determined set of application scenarios over a predetermined period of time, calculating a total carbon footprint of the each application scenario over the predetermined period of time using the unitary carbon footprint that is calculated and the number of executions that is estimated of the each application scenario. The method also includes determining a subset of the set of application scenarios using at least the total carbon footprint of the each application scenario, and modifying or removing from the software application at least one application scenario of the subset to reduce the carbon footprint of the software application.