On the public citation graph

Effort and Cost Estimation Using Decision Tree Techniques and Story Points in Agile Software Development

0 signed · 134 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

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

inferredcites →https://doi.org/10.1002/9781119562757openalex-snapshot
Effective Project Management
inferredcites →https://doi.org/10.1002/smr.2245openalex-snapshot
A systematic review of studies on use case points and expert‐based estimation of software development effort
inferredcites →https://doi.org/10.1002/wics.1278openalex-snapshot
Decision trees
inferredcites →https://doi.org/10.1002/widm.1249openalex-snapshot
Ensemble learning: A survey
inferredcites →https://doi.org/10.1002/widm.8openalex-snapshot
Classification and regression trees
inferredcites →https://doi.org/10.1007/978-1-4419-9326-7openalex-snapshot
Ensemble Machine Learning: Methods and Applications
inferredcites →https://doi.org/10.1007/978-1-4842-5940-5openalex-snapshot
Ensemble Learning for AI Developers
inferredcites →https://doi.org/10.1007/978-1-84628-839-5openalex-snapshot
Fundamentals of the New Artificial Intelligence: Neural, Evolutionary, Fuzzy and More
inferredcites →https://doi.org/10.1007/978-3-030-31362-3_39openalex-snapshot
A Review of the Regression Models Applicable to Software Project Effort Estimation
inferredcites →https://doi.org/10.1007/978-3-319-63913-0openalex-snapshot
An Introduction to Machine Learning
inferredcites →https://doi.org/10.1007/bf00116251openalex-snapshot
Induction of Decision Trees
inferredcites →https://doi.org/10.1007/s10664-018-9647-0openalex-snapshot
An ensemble-based model for predicting agile software development effort
inferredcites →https://doi.org/10.1007/s11222-009-9153-8openalex-snapshot
Estimation of prediction error by using K-fold cross-validation
inferredcites →https://doi.org/10.1007/s11334-017-0288-zopenalex-snapshot
Empirical assessment of machine learning models for agile software development effort estimation using story points
inferredcites →https://doi.org/10.1007/s11334-020-00379-yopenalex-snapshot
A pragmatic ensemble learning approach for effective software effort estimation
inferredcites →https://doi.org/10.1007/s13369-019-04250-6openalex-snapshot
A Comparative Analysis on Effort Estimation for Agile and Non-agile Software Projects Using DBN-ALO
inferredcites →https://doi.org/10.1016/j.aei.2019.100944openalex-snapshot
Times-series data augmentation and deep learning for construction equipment activity recognition
inferredcites →https://doi.org/10.1016/j.cosrev.2020.100288openalex-snapshot
Advancement from neural networks to deep learning in software effort estimation: Perspective of two decades
inferredcites →https://doi.org/10.1016/j.jss.2012.04.005openalex-snapshot
On using planning poker for estimating user stories
inferredcites →https://doi.org/10.1016/j.jss.2021.111031openalex-snapshot
A software engineering perspective on engineering machine learning systems: State of the art and challenges
inferredcites →https://doi.org/10.1016/j.procs.2015.07.474openalex-snapshot
Empirical Validation of Neural Network Models for Agile Software Effort Estimation based on Story Points
inferredcites →https://doi.org/10.1016/j.protcy.2012.05.124openalex-snapshot
Story Points Based Effort Estimation Model for Software Maintenance
inferredcites →https://doi.org/10.1016/s0950-5849(98)00074-3openalex-snapshot
Construction of an FPA-type metric for early lifecycle estimation
inferredcites →https://doi.org/10.1023/a:1024218913435openalex-snapshot
Use of Noise to Augment Training Data: A Neural Network Method of Mineral–Potential Mapping in Regions of Limited Known Deposit Examples
inferredcites →https://doi.org/10.1038/s41598-022-11565-2openalex-snapshot
An efficient ANFIS-EEBAT approach to estimate effort of Scrum projects
inferredcites →https://doi.org/10.1080/01621459.1984.10478083openalex-snapshot
Cross-Validation of Regression Models
inferredcites →https://doi.org/10.1080/01621459.1993.10476299openalex-snapshot
Linear Model Selection by Cross-Validation
inferredcites →https://doi.org/10.1109/32.345828openalex-snapshot
Machine learning approaches to estimating software development effort
inferredcites →https://doi.org/10.1109/access.2017.2771257openalex-snapshot
Ontology Based Multiagent Effort Estimation System for Scrum Agile Method
inferredcites →https://doi.org/10.1109/access.2020.3021664openalex-snapshot
An Update on Effort Estimation in Agile Software Development: A Systematic Literature Review
inferredcites →https://doi.org/10.1109/cist.2018.8596370openalex-snapshot
Support Vector Regression Based on Grid-Search Method for Agile Software Effort Prediction
inferredcites →https://doi.org/10.1109/enc56672.2022.9882947openalex-snapshot
Software Effort Estimation for Agile Software Development Using a Strategy Based on k-Nearest Neighbors Algorithm
inferredcites →https://doi.org/10.1109/iccitechnology.2013.6579553openalex-snapshot
A comparison between decision trees and decision tree forest models for software development effort estimation
inferredcites →https://doi.org/10.1109/iccsre.2019.8807544openalex-snapshot
Decision Trees Based Software Development Effort Estimation: A Systematic Mapping Study
inferredcites →https://doi.org/10.1109/icraie51050.2020.9358309openalex-snapshot
Linear Regression Model for Agile Software Development Effort Estimation
inferredcites →https://doi.org/10.1109/icroit.2014.6798284openalex-snapshot
Cost and effort estimation in agile software development
inferredcites →https://doi.org/10.1109/ieom.2015.7228109openalex-snapshot
PCA based cost estimation model for agile software development projects
inferredcites →https://doi.org/10.1109/mcas.2006.1688199openalex-snapshot
Ensemble based systems in decision making
inferredcites →https://doi.org/10.1109/seaa.2019.00044openalex-snapshot
Analogy Software Effort Estimation Using Ensemble KNN Imputation
inferredcites →https://doi.org/10.1109/tse.2018.2792473openalex-snapshot
A Deep Learning Model for Estimating Story Points
inferredcites →https://doi.org/10.1109/tse.2022.3228739openalex-snapshot
Agile Effort Estimation: Have We Solved the Problem Yet? Insights From a Replication Study
inferredcites →https://doi.org/10.1111/insr.12016openalex-snapshot
Fifty Years of Classification and Regression Trees
inferredcites →https://doi.org/10.1134/s0361768820080095openalex-snapshot
User Story Estimation Based on the Complexity Decomposition Using Bayesian Networks
inferredcites →https://doi.org/10.1136/amiajnl-2012-000929openalex-snapshot
Discretization of continuous features in clinical datasets
inferredcites →https://doi.org/10.1142/s0218194020500035openalex-snapshot
Story Point-Based Effort Estimation Model with Machine Learning Techniques
inferredcites →https://doi.org/10.1145/3202710.3203160openalex-snapshot
Using developers' features to estimate story points
inferredcites →https://doi.org/10.1145/3236024.3236052openalex-snapshot
A novel automated approach for software effort estimation based on data augmentation
inferredcites →https://doi.org/10.1186/s40411-018-0059-zopenalex-snapshot
Back to the future: origins and directions of the “Agile Manifesto” – views of the originators
inferredcites →https://doi.org/10.1186/s40537-019-0197-0openalex-snapshot
A survey on Image Data Augmentation for Deep Learning
inferredcites →https://doi.org/10.1186/s42467-020-00005-4openalex-snapshot
Applications of AI in classical software engineering
inferredcites →https://doi.org/10.1201/9781315119588openalex-snapshot
Statistical Regression and Classification
inferredcites →https://doi.org/10.1201/9781351204750openalex-snapshot
A Concise Introduction to Machine Learning
inferredcites →https://doi.org/10.1214/09-ss054openalex-snapshot
A survey of cross-validation procedures for model selection
inferredcites →https://doi.org/10.12785/ijcds/1201012openalex-snapshot
Analysis of Software Effort Estimation Based on Story Point and Lines of Code using Machine Learning
inferredcites →https://doi.org/10.1515/jisys-2016-0294openalex-snapshot
A Novel Hybrid ABC-PSO Algorithm for Effort Estimation of Software Projects Using Agile Methodologies
inferredcites →https://doi.org/10.15242/ijccie.e0317026openalex-snapshot
Software Development Effort Estimation Using Ensemble Machine Learning
inferredcites →https://doi.org/10.21203/rs.3.rs-2461583/v1openalex-snapshot
A SLR on Deep Learning Models Based on Textual Information For Effort Estimation in Scrum
inferredcites →https://doi.org/10.22214/ijraset.2021.38977openalex-snapshot
Estimation Approaches of Machine Learning in Scrum Projects: A Review
inferredcites →https://doi.org/10.22581/muet1982.2002.18openalex-snapshot
A Study of Software Development Cost Estimation Techniques and Models
inferredcites →https://doi.org/10.2307/2289463openalex-snapshot
The Calculation of Posterior Distributions by Data Augmentation: Rejoinder
inferredcites →https://doi.org/10.3390/electronics10101195openalex-snapshot
Estimating Software Development Efforts Using a Random Forest-Based Stacked Ensemble Approach
inferredcites →https://doi.org/10.47836/pjst.29.2.08openalex-snapshot
A Review Article on Software Effort Estimation in Agile Methodology
inferredcites →https://doi.org/10.5120/12130-8506openalex-snapshot
Effect of Data Preprocessing on Software Effort Estimation
inferredcites →https://doi.org/10.5120/ijais12-450574openalex-snapshot
Effort Estimation in Agile Software Development using Story Points
inferredcites →https://doi.org/10.5120/ijca2017915664openalex-snapshot
Recurrent Neural Network based Prediction of Software Effort

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1002/smr.70158openalex-snapshot
Artificial Intelligence Techniques to Enhance Cost, Effort, and Schedule Estimates in Software Development Projects: A Systematic Literature Review
inferred← citeshttps://doi.org/10.1002/smr.70164openalex-snapshot
Agile Software Cost Estimation Model Based on Constricted Particle Swarm Optimization
inferred← citeshttps://doi.org/10.1007/978-3-031-71139-8_2openalex-snapshot
Data-Driven Software Engineering: A Systematic Literature Review
inferred← citeshttps://doi.org/10.1007/978-3-031-88188-6_8openalex-snapshot
Machine Learning Techniques for the Measurement of Software Attributes
inferred← citeshttps://doi.org/10.1007/978-3-031-98304-7_45openalex-snapshot
Enhancing Agile Story Point Estimation: Integrating Fuzzy AHP and Fibonacci Series with Triangular Distribution
inferred← citeshttps://doi.org/10.1007/978-3-032-04288-0_10openalex-snapshot
A Review of Estimation in Software Engineering
inferred← citeshttps://doi.org/10.1007/978-981-96-1185-0_35openalex-snapshot
An Analysis of Software Development for Agile Machine Learning Methodologies
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
inferred← citeshttps://doi.org/10.1007/s10515-025-00578-6openalex-snapshot
Artificial intelligence and machine learning in enhancing software project management processes: A systematic literature review
inferred← citeshttps://doi.org/10.1007/s10515-026-00607-yopenalex-snapshot
Effort estimation in scrum using AI
inferred← citeshttps://doi.org/10.1007/s12145-025-01900-2openalex-snapshot
Estimating saltwater wedge length in sloping coastal aquifers using explainable machine learning models
inferred← citeshttps://doi.org/10.1007/s13198-025-02746-zopenalex-snapshot
Predicting software effort using BERT-based word embeddings
inferred← citeshttps://doi.org/10.1007/s41062-025-01983-2openalex-snapshot
Concrete compressive strength classification using hybrid machine learning models and interactive GUI
inferred← citeshttps://doi.org/10.1007/s44196-024-00716-0openalex-snapshot
Adaptive Ensemble Learning Model-Based Binary White Shark Optimizer for Software Defect Classification
inferred← citeshttps://doi.org/10.1007/s44443-025-00058-7openalex-snapshot
A data-driven cost estimation model for agile development based on Kolmogorov-Arnold Networks and AdamW optimization
inferred← citeshttps://doi.org/10.1016/j.array.2025.100665openalex-snapshot
A data-driven comparative analysis of Agile and Waterfall methodologies: Predicting cost and schedule variances using statistical and machine learning approaches
inferred← citeshttps://doi.org/10.1016/j.engappai.2025.113546openalex-snapshot
Software development effort prediction using a hybrid of LeNet and Shepard convolutional neural networks
inferred← citeshttps://doi.org/10.1038/s41598-024-68360-4openalex-snapshot
Numerical and machine learning modeling of GFRP confined concrete-steel hollow elliptical columns
inferred← citeshttps://doi.org/10.1038/s41598-025-10990-3openalex-snapshot
Hydraulic Performance Modeling of Inclined Double Cutoff Walls Beneath Hydraulic Structures Using Optimized Ensemble Machine Learning
inferred← citeshttps://doi.org/10.1038/s41598-025-27998-4openalex-snapshot
Assessing the impact of groundwater abstraction and concrete dam fractures on saltwater intrusion using numerical modeling and interpretable machine learning
inferred← citeshttps://doi.org/10.1038/s41598-025-29908-0openalex-snapshot
Software cost estimation using TabNet and Harris Hawks Optimization
inferred← citeshttps://doi.org/10.1038/s41598-026-41102-4openalex-snapshot
Intelligent techniques for predictive analytics in Agile software development
inferred← citeshttps://doi.org/10.1049/sfw2/9238663openalex-snapshot
Blockchain‐Based Model to Predict Agile Software Estimation Using Machine Learning Techniques
inferred← citeshttps://doi.org/10.1063/5.0259372openalex-snapshot
Software cost estimation with K-means clustering and random forest regression
inferred← citeshttps://doi.org/10.1080/0013791x.2026.2692361openalex-snapshot
Hierarchical multi-scale dense-RNN with sparse attention model for effort and cost estimation of IT projects in agile methodologies
inferred← citeshttps://doi.org/10.1080/0951192x.2026.2657827openalex-snapshot
Complexity index-based graph network estimation for adapting control programs in cyber-physical production systems
inferred← citeshttps://doi.org/10.1080/14680629.2026.2627519openalex-snapshot
Explainable machine learning and experimental modeling of mechanical properties in stabilized full-depth reclaimed pavement materials
inferred← citeshttps://doi.org/10.1088/1755-1315/1290/1/012012openalex-snapshot
Evaluating Smart Greenhouse Viability Through Engineering Design and Software Cost Modelling
inferred← citeshttps://doi.org/10.1108/ijmpb-07-2025-0291openalex-snapshot
Application of artificial intelligence in agile project management: a task-technology fit lens
inferred← citeshttps://doi.org/10.1108/jeim-04-2026-0622openalex-snapshot
Problematisation and reconfiguration of knowledge in AI-embedded agile software development
inferred← citeshttps://doi.org/10.1109/access.2024.3404879openalex-snapshot
Review and Empirical Analysis of Machine Learning-Based Software Effort Estimation
inferred← citeshttps://doi.org/10.1109/access.2025.3558715openalex-snapshot
Advancing Agile Software Cost Estimation Through Data Synthesis: A Comparative Analysis of Five Generation Techniques
inferred← citeshttps://doi.org/10.1109/cictn64563.2025.10932574openalex-snapshot
A Comparative Analysis of Different Machine Learning Techniques Used in Software Effort Estimation
inferred← citeshttps://doi.org/10.1109/emergin63207.2024.10961288openalex-snapshot
Agile Software Development Effort Estimation: A Comprehensive Survey
inferred← citeshttps://doi.org/10.1109/iccd59681.2023.10420603openalex-snapshot
Leveraging AI for Enhanced Software Effort Estimation: A Comprehensive Study and Framework Proposal
inferred← citeshttps://doi.org/10.1109/icimtech202671078.2026.11698927openalex-snapshot
Smart Digital Fabric Store Project Software Size Measurement Using Use Case Point Method
inferred← citeshttps://doi.org/10.1109/icocics68032.2025.11383851openalex-snapshot
Enhancing Story Point Estimation in Software Projects Using Transformer-Based Embeddings and Ensemble Regression Models
inferred← citeshttps://doi.org/10.1109/icoco67189.2025.11334137openalex-snapshot
Expert-Integrated Stacking Model for Estimating Software Development Effort
inferred← citeshttps://doi.org/10.1109/icraie59459.2023.10468186openalex-snapshot
Comparative Analysis of Regression Techniques for Software Effort Estimation
inferred← citeshttps://doi.org/10.1109/icscds65426.2025.11166951openalex-snapshot
Agile Software Development for Cost Cutting and Operational Efficiency
inferred← citeshttps://doi.org/10.1109/innocomp63224.2024.00073openalex-snapshot
A Novel Deep Learning Model for Effective Story Point Estimation in Agile Software Development
inferred← citeshttps://doi.org/10.1109/ocit66168.2025.11400137openalex-snapshot
Effort Prediction in Agile-Based Projects Using Class Models and Machine Learning Approaches
inferred← citeshttps://doi.org/10.1145/3639474.3640064openalex-snapshot
Teaching Software Development for Real-World Problems using a Microservice-Based Collaborative Problem-Solving Approach
inferred← citeshttps://doi.org/10.1145/3663365openalex-snapshot
A Systematic Literature Review on Reasons and Approaches for Accurate Effort Estimations in Agile
inferred← citeshttps://doi.org/10.1145/3749984openalex-snapshot
Enhancing Task In-Progress Time Predictions through Affective and Personality Factors
inferred← citeshttps://doi.org/10.1145/3787279.3787291openalex-snapshot
Identifying Transferable AI Use Cases for Scrum through an Analysis of Software Development Methods
inferred← citeshttps://doi.org/10.1186/s40537-026-01414-8openalex-snapshot
A novel stacking-based ensemble machine learning model for accurate user story effort estimation in scrum
inferred← citeshttps://doi.org/10.22201/fi.25940732e.2024.25.3.017openalex-snapshot
A systematic literature review on machine learning applications for agile project management
inferred← citeshttps://doi.org/10.2507/34th.daaam.proceedings.001openalex-snapshot
Productivity Factors in Agile Software Development Projects
inferred← citeshttps://doi.org/10.33022/ijcs.v13i4.4155openalex-snapshot
Artificial Intelligence Implementation in Agile Project Management Addressing Challenges and Maximizing Impact
inferred← citeshttps://doi.org/10.3390/app13169465openalex-snapshot
Advanced Bayesian Network for Task Effort Estimation in Agile Software Development
inferred← citeshttps://doi.org/10.3390/app132212353openalex-snapshot
Compiling Requirements from Models for Early Phase Scope Estimation in Agile Software Development Projects
inferred← citeshttps://doi.org/10.3390/electronics15184173openalex-snapshot
Assessing Embedded Software Contribution Under Data Scarcity: An Improved Grey PCA and GRA Framework
inferred← citeshttps://doi.org/10.3390/info15060354openalex-snapshot
The Use of AI in Software Engineering: A Synthetic Knowledge Synthesis of the Recent Research Literature
inferred← citeshttps://doi.org/10.3390/info17010110openalex-snapshot
GemSP: An Ensemble Model for User Story Point Estimation Using Gemini Embeddings
inferred← citeshttps://doi.org/10.3390/math12020200openalex-snapshot
An Optimized LSTM Neural Network for Accurate Estimation of Software Development Effort
inferred← citeshttps://doi.org/10.3390/software5020017openalex-snapshot
Decision-Making in Agile Software Engineering: A Systematic Literature Review of Models, Methods, Actors and Lifecycle Contexts
inferred← citeshttps://doi.org/10.3390/sym18091506openalex-snapshot
A Combined Framework for Agile Story Point Estimation Using AHP-Based Expert Weighting, Neutrosophic Z-Numbers, Bonferroni Aggregation, and XGBoost
inferred← citeshttps://doi.org/10.35585/inspir.v13i2.57openalex-snapshot
Time Effort Prediction Of Agile Software Development Using Machine Learning Techniques
inferred← citeshttps://doi.org/10.36948/ijfmr.2024.v06i03.21926openalex-snapshot
Evaluative Exploration of Comparative Analysis of Information Systems Design Methods
inferred← citeshttps://doi.org/10.3897/jucs.110051openalex-snapshot
Recommendation of Machine Learning Techniques for Software Effort Estimation using Multi-Criteria Decision Making
inferred← citeshttps://doi.org/10.5753/cibse.2025.35289openalex-snapshot
Integración de herramienta para el seguimiento ágil mediante el uso de Machine Learning
inferred← citeshttps://doi.org/10.5753/jbcs.2026.5860openalex-snapshot
User Story Estimation using Natural Language Processing and Deep Learning: A Comparative Study
inferred← citeshttps://doi.org/10.5753/sbqs_estendido.2025.13396openalex-snapshot
Cost Estimation for Agile Software Development in Small and Medium-Sized Enterprises
inferred← citeshttps://doi.org/10.59573/emsj.9(5).2025.31openalex-snapshot
AI as Your Agile Copilot: From Sprint Planning to Real-Time Delivery Adjustment
inferred← citeshttps://doi.org/10.60797/itech.2026.10.1openalex-snapshot
Обзор датасета TAWOS для анализа трудозатрат и процессов разработки ПО
inferred← citeshttps://doi.org/10.60797/itech.2026.10.1.1openalex-snapshot
Диаграмма сущностей датасета, их полей и отношений между ними
inferred← citeshttps://doi.org/10.60797/itech.2026.10.1.2openalex-snapshot
Сущности, составляющие датасет TAWOS
inferred← citeshttps://doi.org/10.60797/itech.2026.10.1.3openalex-snapshot
Обзор датасета TAWOS для анализа трудозатрат и процессов разработки ПО
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.