Systematic literature review of machine learning based software development effort estimation models
CONTEXT: Software development effort estimation (SDEE) is the process of predicting the
effort required to develop a software system. In order to improve estimation accuracy, many …
effort required to develop a software system. In order to improve estimation accuracy, many …
A systematic review of software development cost estimation studies
M Jorgensen, M Shepperd - IEEE Transactions on software …, 2006 - ieeexplore.ieee.org
This paper aims to provide a basis for the improvement of software-estimation research
through a systematic review of previous work. The review identifies 304 software cost …
through a systematic review of previous work. The review identifies 304 software cost …
Advancement from neural networks to deep learning in software effort estimation: Perspective of two decades
In the software engineering, estimation of the effort, time and cost required for the
development of software projects is an important issue. It is a very difficult task for project …
development of software projects is an important issue. It is a very difficult task for project …
An empirical validation of a neural network model for software effort estimation
H Park, S Baek - Expert Systems with Applications, 2008 - Elsevier
As software becomes more complex and its scope dramatically increases, the importance of
research on developing methods for estimating software development efforts has …
research on developing methods for estimating software development efforts has …
Comprehensible software fault and effort prediction: A data mining approach
J Moeyersoms, EJ de Fortuny, K Dejaeger… - Journal of Systems and …, 2015 - Elsevier
Software fault and effort prediction are important tasks to minimize costs of a software
project. In software effort prediction the aim is to forecast the effort needed to complete a …
project. In software effort prediction the aim is to forecast the effort needed to complete a …
Improved estimation of software project effort using multiple additive regression trees
MO Elish - Expert Systems with Applications, 2009 - Elsevier
Accurate estimation of software project effort is crucial for successful management and
control of a software project. Recently, multiple additive regression trees (MART) has been …
control of a software project. Recently, multiple additive regression trees (MART) has been …
A study of mutual information based feature selection for case based reasoning in software cost estimation
Software cost estimation is one of the most crucial activities in software development
process. In the past decades, many methods have been proposed for cost estimation. Case …
process. In the past decades, many methods have been proposed for cost estimation. Case …
Systematic literature review on software effort estimation using machine learning approaches
P Sharma, J Singh - 2017 International Conference on Next …, 2017 - ieeexplore.ieee.org
Accurate effort estimation is amongst the key activities in the software project development. It
directly impacts the time and cost of the software projects. This paper presents a systematic …
directly impacts the time and cost of the software projects. This paper presents a systematic …
Empirical study of homogeneous and heterogeneous ensemble models for software development effort estimation
Accurate estimation of software development effort is essential for effective management
and control of software development projects. Many software effort estimation methods have …
and control of software development projects. Many software effort estimation methods have …
Technical efficiency-based selection of learning cases to improve forecasting accuracy of neural networks under monotonicity assumption
PC Pendharkar, JA Rodger - Decision support systems, 2003 - Elsevier
In this paper, we show that when an artificial neural network (ANN) model is used for
learning monotonic forecasting functions, it may be useful to screen training data so the …
learning monotonic forecasting functions, it may be useful to screen training data so the …