Core Concepts
This systematic literature review provides a comprehensive classification of 30 non-functional requirements affecting machine learning-enabled software systems, and identifies over 23 key challenges faced by researchers and practitioners when dealing with these non-functional requirements.
Abstract
The study conducted a systematic literature review to address two key objectives:
Classify the non-functional requirements of machine learning-enabled software systems identified in the research literature.
The review identified a total of 30 distinct non-functional requirements, which were grouped into 6 main classes: Accuracy, Resiliency, Performance, Interpretability, Sustainability, and Fairness.
The non-functional requirements span across various domains where machine learning is applied, including environmental, healthcare, and financial domains.
Identify the key challenges faced when dealing with non-functional requirements in machine learning-enabled systems.
The review compiled a catalog of over 23 software engineering challenges, including issues with requirements elicitation, modeling, testing, and optimization of non-functional attributes.
The challenges cover aspects such as the inherent trade-offs between different non-functional requirements, the difficulty in specifying and measuring certain non-functional properties, and the need for automated approaches to handle the complexity.
The findings provide a comprehensive overview of the state of research on non-functional requirements in machine learning-enabled systems, and highlight important directions for future work to better support practitioners in developing reliable and trustworthy AI-powered software.
Stats
"memory problems and battery drain" [S1]
"accuracy" [S2-S54]
"robustness" [S2-S7, S9, S10, S12, S19, S20, S22-S24, S27-S31, S40, S45, S46, S48, S49, S51, S53, S55-S64]
"security" [S2, S3, S7, S9, S12, S14, S19, S22-S24, S27, S31-S33, S36, S45, S49, S55, S56, S58-S60, S62]
"performance" [S1, S10, S13, S15-S17, S28-S30, S32, S37, S39, S40, S46, S50, S52, S53, S58-S60, S65]
"fairness" [S13, S15, S17, S21, S26, S33-S35, S41, S42, S54, S61, S63-S69]
"behavioral" [S7, S14, S20, S28, S43, S47-S49, S59, S61, S63]
"interpretability" [S14, S17, S27, S33, S38, S39, S45, S59]
"transferability" [S24, S31, S49, S55, S57, S58, S60]
"safety" [S6, S7, S14, S24, S47, S50, S57]
"reliability" [S20, S27, S28, S33, S48, S59, S62]
"explainability" [S9, S21, S38, S39, S61, S68]
"retrainability" [S3, S5, S23, S46, S62]
Quotes
"memory problems and battery drain" [S1]
"accuracy" [S2-S54]
"robustness" [S2-S7, S9, S10, S12, S19, S20, S22-S24, S27-S31, S40, S45, S46, S48, S49, S51, S53, S55-S64]
"security" [S2, S3, S7, S9, S12, S14, S19, S22-S24, S27, S31-S33, S36, S45, S49, S55, S56, S58-S60, S62]