The nature and practices of the use of Machine Learning and Deep Learning Frameworks to assist Software Project Management: A Developing Country Context

Abstract

The study conducted a comprehensive analysis of literature and interviews related to the use of ML and DL in SPM, identifying challenges and gaps in the field. The study adopts a qualitative research design, gathering data through semi-structured interviews with project managers involved in SPM using ML and DL frameworks. The collected data is analysed using thematic analysis to capture the participants' subjective experiences, perceptions, and opinions. The findings suggest that while the use of AI techniques for SPM has been gaining attention, it is still in its infancy, with limited research and practice in developing countries. The study also emphasizes the unique challenges faced by developing countries in SPM, including limited resources, diverse stakeholders, cultural differences, and rapid changes. It suggests that ML and DL frameworks can offer advantages in enhancing the productivity, innovation, and competitiveness of software projects in these contexts. However, the study acknowledges that there are limitations to these AI techniques for SPM, and further research is needed to address these limitations. The study bridge the gap between theory and practice by offering practical insights for project managers and recommendations for future research in utilizing ML and DL frameworks to assist SPM.