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Ai Applications in Software Functional Size Measurement: A Systematic Literature Review

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/9781119896838.ch15openalex-extracted

Software Effort Estimation with Machine Learning – A Systematic Literature Review

inferredcites →https://doi.org/10.1007/978-3-030-64694-3_14openalex-extracted

Investigating the Impact of Functional Size Measurement on Predicting Software Enhancement Effort Using Correlation-Based Feature Selection Algorithm and SVR Method

inferredcites →https://doi.org/10.1007/978-3-319-24285-9_7openalex-extracted

Application of Function Points and Data Mining Techniques for Software Estimation - A Combined Approach

inferredcites →https://doi.org/10.1016/j.infsof.2016.08.007openalex-extracted

Functional size approximation based on use-case names

inferredcites →https://doi.org/10.1016/j.infsof.2020.106310openalex-extracted

Deep learning model for end-to-end approximation of COSMIC functional size based on use-case names

inferredcites →https://doi.org/10.1109/access.2024.3471428openalex-extracted

Using Machine Learning and Simplified Functional Measures to Estimate Software Development Effort

inferredcites →https://doi.org/10.1109/access.2025.3540548openalex-extracted

COSMIC-Based Early Software Size Estimation Using Deep Learning and Domain-Specific BERT

inferredcites →https://doi.org/10.1109/iwsm-mensura.2016.039openalex-extracted

Approximation of COSMIC Functional Size of Scenario-Based Requirements in Agile Based on Syntactic Linguistic Features—A Replication Study

inferredcites →https://doi.org/10.1186/s40411-017-0037-xopenalex-extracted

A genetic algorithm based framework for software effort prediction

inferredcites →https://doi.org/10.1201/9780367854690-5openalex-extracted

Use of artificial neural networks and decision trees for cost estimation of software projects – A model proposal

inferredcites →https://doi.org/10.13140/rg.2.1.3749.0004openalex-extracted

Software Effort and Function Points Estimation Models Based Radial Basis Function and Feedforward Artificial Neural Networks

What points at this work

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inferred← citeshttps://doi.org/10.1007/s00766-026-00463-yopenalex-snapshot

Large language models for agile effort estimation: a post-mortem study incorporating developer experience and optimism

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