Determining Non-Functional Requirements through Requirements Engineering Artefacts Analysis using Machine Learning.
Budget: $30 – $250 USD
1. To analyze the similarities and differences in related works of Safety, Availability (A), Fault Tolerance (FT), Legal & Licensing (L), Look & Feel (LF), Maintainability (MN), Operability (O), Performance (PE), Portability (PO), Scalability (SC), Security (SE), Usability (US), Non-Functional Requirements detection.
2. To develop a Non-Functional Requirements Detection Model using a Machine Learning algorithm.
3. To evaluate the accuracy performance of the model based on Accuracy, Precision, Recall, and F-Measure metrics.
4: Only use python
5: see the attached file for more details.
2. To develop a Non-Functional Requirements Detection Model using a Machine Learning algorithm.
3. To evaluate the accuracy performance of the model based on Accuracy, Precision, Recall, and F-Measure metrics.
4: Only use python
5: see the attached file for more details.