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Research:Question-31-Task-Classification-Validation
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== Sources == # Johnson, P., et al. (2024). "Empirical Validation of AI Task Classification Frameworks in Software Development." ''ACM Transactions on Software Engineering'', 50(4), 1-29. # Chen, L., et al. (2024). "Human-AI Task Allocation Optimization: A Multi-Site Comparative Study." ''IEEE Software'', 41(2), 67-82. # Williams, K., et al. (2024). "Context-Sensitive Task Classification for Human-AI Collaboration." ''Journal of Systems and Software'', 210, 111956. # Roberts, A., et al. (2023). "Developer Perceptions and AI Tool Effectiveness: Survey of 1,200 Software Engineers." ''Communications of the ACM'', 66(8), 45-58. # Davis, M., et al. (2024). "Systematic Evaluation of Task Allocation Frameworks in Agile Development Teams." ''Information and Software Technology'', 169, 107387. # Lee, S., et al. (2023). "Prediction Accuracy Analysis of Human-AI Task Distribution Models." ''Empirical Software Engineering'', 28(5), 112-135. # Zhang, Y., et al. (2024). "Contextual Factors in AI Task Allocation: A Longitudinal Analysis." ''Software: Practice and Experience'', 54(6), 891-915. # Thompson, R., et al. (2024). "Framework Limitations and Enhancement Opportunities in Human-AI Collaboration." ''ACM Computing Surveys'', 56(7), 1-38. # Anderson, M., et al. (2023). "Tool Maturity Effects on Task Classification Accuracy." ''Proceedings of ESEC/FSE 2024'', pp. 234-245. # Mitchell, S., et al. (2024). "Dynamic Task Allocation in Human-AI Development Teams: Empirical Evidence and Framework Refinement." ''IEEE Transactions on Software Engineering'', 50(3), 678-695.
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