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Application of data mining methods for effort estimation of software projects
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/s10462-012-9339-xopenalex-snapshot
Neural network based models for software effort estimation: a review
inferredcites →https://doi.org/10.1007/s10664-011-9187-3openalex-snapshot
Using tabu search to configure support vector regression for effort estimation
inferredcites →https://doi.org/10.1007/s10664-011-9193-5openalex-snapshot
Special issue on repeatable results in software engineering prediction
inferredcites →https://doi.org/10.1007/s10664-013-9241-4openalex-snapshot
A flexible method to estimate the software development effort based on the classification of projects and localization of comparisons
inferredcites →https://doi.org/10.1007/s10664-016-9472-2openalex-snapshot
Negative results for software effort estimation
inferredcites →https://doi.org/10.1007/s13748-016-0092-2openalex-snapshot
Data mining for software engineering and humans in the loop
inferredcites →https://doi.org/10.1016/b978-0-12-374765-5.00018-8openalex-snapshot
Model Complexity (and How Ensembles Help)
inferredcites →https://doi.org/10.1016/c2012-0-07289-4openalex-snapshot
The Art and Science of Analyzing Software Data
inferredcites →https://doi.org/10.1016/j.ijforecast.2007.05.008openalex-snapshot
Forecasting of software development work effort: Evidence on expert judgement and formal models
inferredcites →https://doi.org/10.1016/j.infsof.2011.12.008openalex-snapshot
Evaluating prediction systems in software project estimation
inferredcites →https://doi.org/10.1016/j.infsof.2016.01.003openalex-snapshot
Exact Mean Absolute Error of Baseline Predictor, MARP0
inferredcites →https://doi.org/10.1016/j.jss.2016.03.048openalex-snapshot
Unit effects in software project effort estimation: Work-hours gives lower effort estimates than workdays
inferredcites →https://doi.org/10.1109/ase.2011.6100072openalex-snapshot
Local vs. global models for effort estimation and defect prediction
inferredcites →https://doi.org/10.1109/ase.2017.8115719openalex-snapshot
Learning effective changes for software projects
inferredcites →https://doi.org/10.1109/iwsm-mensura.2016.040openalex-snapshot
The Missing Links in Software Estimation: Team Loading and Team Power
inferredcites →https://doi.org/10.1109/mc.2009.256openalex-snapshot
Data Mining for Software Engineering
inferredcites →https://doi.org/10.1109/ms.2014.49openalex-snapshot
What We Do and Don't Know about Software Development Effort Estimation
inferredcites →https://doi.org/10.1109/nasase.2002.1176229openalex-snapshot
Smarter software engineering: practical data mining approaches
inferredcites →https://doi.org/10.1109/promise.2007.2openalex-snapshot
Assessing the Reliability of a Human Estimator
inferredcites →https://doi.org/10.1109/raise.2012.6227961openalex-snapshot
The role of Artificial Intelligence in Software Engineering
inferredcites →https://doi.org/10.1109/raise.2013.6615197openalex-snapshot
The synergy of human and artificial intelligence in software engineering
inferredcites →https://doi.org/10.1109/seaa.2014.41openalex-snapshot
A Comparison of Cross-Versus Single-Company Effort Prediction Models for Web Projects
inferredcites →https://doi.org/10.1109/tnn.2005.845141openalex-snapshot
Survey of Clustering Algorithms
inferredcites →https://doi.org/10.1109/tse.1978.231521openalex-snapshot
A General Empirical Solution to the Macro Software Sizing and Estimating Problem
inferredcites →https://doi.org/10.1109/tse.1983.235271openalex-snapshot
Software Function, Source Lines of Code, and Development Effort Prediction: A Software Science Validation
inferredcites →https://doi.org/10.1109/tse.2007.256943openalex-snapshot
A Systematic Review of Software Development Cost Estimation Studies
inferredcites →https://doi.org/10.1109/tse.2017.2754374openalex-snapshot
Data Scientists in Software Teams: State of the Art and Challenges
inferredcites →https://doi.org/10.1109/tse.2018.2792473openalex-snapshot
A Deep Learning Model for Estimating Story Points
inferredcites →https://doi.org/10.1142/s0218194011005438openalex-snapshot
EXPLORING THE EFFORT OF GENERAL SOFTWARE PROJECT ACTIVITIES WITH DATA MINING
inferredcites →https://doi.org/10.1145/1540438.1540444openalex-snapshot
Why comparative effort prediction studies may be invalid
inferredcites →https://doi.org/10.1145/2070821.2070829openalex-snapshot
Software analytics as a learning case in practice
inferredcites →https://doi.org/10.1145/2499393.2499394openalex-snapshot
The impact of parameter tuning on software effort estimation using learning machines
inferredcites →https://doi.org/10.1145/2568225.2568233openalex-snapshot
Analyze this! 145 questions for data scientists in software engineering
inferredcites →https://doi.org/10.1145/2884781.2884830openalex-snapshot
Multi-objective software effort estimation
inferredcites →https://doi.org/10.1145/2915970.2916005openalex-snapshot
Realistic assessment of software effort estimation models
inferredcites →https://doi.org/10.1145/3172871.3172891openalex-snapshot
Intelligent Software Engineering
inferredcites →https://doi.org/10.1287/isre.2.4.243openalex-snapshot
Software-Effort Estimation: An Exploratory Study of Expert Performance
inferredcites →https://doi.org/10.14236/ewic/ease2009.5openalex-snapshot
Building an Expert-based Web Effort Estimation Model using Bayesian Networks
inferredcites →https://doi.org/10.14445/22315381/ijett-v35p254openalex-snapshot
Early Phase Software Effort Estimation Model: A Review
inferredcites →https://doi.org/10.1504/ijdats.2010.034058openalex-snapshot
Applications of data mining in software engineering
inferredcites →https://doi.org/10.48550/arxiv.1804.00626openalex-snapshot
Why Software Effort Estimation Needs SBSE
inferredcites →https://doi.org/10.5120/7479-0540openalex-snapshot
Comparative Analysis of Software Effort Estimation Techniques
inferredcites →https://doi.org/10.5121/ijsea.2017.8103openalex-snapshot
Factors on Software Effort Estimation
inferredcites →https://doi.org/10.5220/0005002600260035openalex-snapshot
Estimators Characteristics and Effort Estimation of Software Projects
inferredcites →https://doi.org/10.5555/227726.227758openalex-snapshot
Effort estimation using analogy
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.2139/ssrn.4902731openalex-extracted
Predicting Software Effort Estimation Using the Stacked Ensemble Machine Learning Approach
inferred← citeshttps://doi.org/10.1002/smr.2365openalex-snapshot
Effort prediction for the software project construction phase
inferred← citeshttps://doi.org/10.1002/spe.3333openalex-snapshot
Impact of competence on agile effort estimation in academic setting
inferred← citeshttps://doi.org/10.1007/978-981-19-1610-6_54openalex-snapshot
A Novel Software Architecture to Calculate Effort Estimation for Industrial Big Data
inferred← citeshttps://doi.org/10.1016/j.csi.2021.103587openalex-snapshot
Unveiling process insights from refactoring practices
inferred← citeshttps://doi.org/10.1109/qrs54544.2021.00059openalex-snapshot
EPR: a Neural Network for Automatic Feature Learning from Code for Defect Prediction
inferred← citeshttps://doi.org/10.22541/au.168781687.72810121/v1openalex-snapshot
Impact of individual competence on agile effort estimation in academic setting
inferred← citeshttps://doi.org/10.23919/softcom.2019.8903752openalex-snapshot
Cross-Project Estimation of Software Development Effort Using In-House Sources and Data Mining Methods - an Experiment
inferred← citeshttps://doi.org/10.31341/jios.44.1.3openalex-snapshot
The Effects of Turnover on Expert Effort Estimation
inferred← citeshttps://doi.org/10.31449/inf.v44i2.2759openalex-snapshot
Data Mining Approach to Effort Modeling On Agile Software Projects
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