Effort Estimation in Global Software Development: An Updated Systematic Literature Review

Abstract Effort estimation remains a critical and unsolved challenge in global software development (GSD), where increase in project complexity, rapid technological growth, and the occurrence of distributed teams across the globe have declared traditional estimation paradigms insufficient for estimating a product. This updated systematic literature review thoroughly examines the evolution and empirical foundation of estimation methods in GSD, drawing on studies published between 2020 to 2024. Our analysis exposes a persistent trust in expert judgment and algorithmic models, with only experimental adaptation of AI/ML and hybrid approaches, none of which comprehensively address GSD-specific drivers such as time zone distribution, cultural differences, and coordination interruptions. Despite the proliferation of new techniques, there remains a noticeable scarcity of large-scale context-aware metric development, empirical validation and standardization. Particularly, our research gap mapping reveals that no prevailing method fully meets the core needs of modern GSD, indicating systemic weaknesses in methodological and practical applicability. By critically synthesizing these limitations and highlighting the disengagement between academic innovation and industrial adoption, this review provides not only an authoritative assessment of the current state-of-the-art methods for estimation but also a persuasive direction for the development of empirically grounded, standardized, and contextually adaptive estimation models. These insights are intended to guide researchers, practitioners, and policymakers towards resolving the long-standing bottlenecks that delay reliable effort estimation in global software engineering. Keywords Effort Estimation, Global Software Development, Systematic Literature Review.