A Review of Estimation in Software Engineering

Tomescu K. J., Gowran N., Gomez L., Delahunty E., McCarren A., Marks G., ...Daha Fazla

32nd European Conference on Systems, Software and Services Process Improvement, EuroSPI 2025, Riga, Letonya, 17 - 19 Eylül 2025, cilt.2657 CCIS, ss.158-175, (Tam Metin Bildiri) identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası: 2657 CCIS
  • Doi Numarası: 10.1007/978-3-032-04288-0_10
  • Basıldığı Şehir: Riga
  • Basıldığı Ülke: Letonya
  • Sayfa Sayıları: ss.158-175
  • Anahtar Kelimeler: Algorithmic, Cost, Effort, Ensemble, Expert, Hybrid, Machine Learning, Planning Poker, Software Estimation, Story Points
  • Gazi Üniversitesi Adresli: Evet

Özet

Estimation is an important challenge in software engineering, determining cost, effort, and resource planning. This paper presents an adapted Multivocal Literature Review (MLR) synthesising formal and grey literature on four main estimation approaches identified in literature: algorithmic, expert-based, machine learning, and ensemble-based hybrid approaches. This review discusses the strengths and limitations of each approach, identifying the emerging role of ML models, while also examining non-ML based agile approaches such as planning poker and story points. The findings indicate that estimation is both complex and non-deterministic, where no single approach universally applies across all contexts. Ensemble-based hybrid models which employ a variety of estimation techniques in parallel report promising results in terms of accuracy and adaptability.