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 …
Analogy-based software development effort estimation: A systematic map** and review
Abstract Context Analogy-based Software development Effort Estimation (ASEE) techniques
have gained considerable attention from the software engineering community. However …
have gained considerable attention from the software engineering community. However …
Energy, economic and comfort optimization of building retrofits considering climate change: A simulation-based NSGA-III approach
Improving building energy performance is central to promote sustainability and mitigate
climate change, but it has proved to be a challenging process requiring investigation of a …
climate change, but it has proved to be a challenging process requiring investigation of a …
An empirical analysis of data preprocessing for machine learning-based software cost estimation
Context Due to the complex nature of software development process, traditional parametric
models and statistical methods often appear to be inadequate to model the increasingly …
models and statistical methods often appear to be inadequate to model the increasingly …
A deep learning model for estimating story points
Although there has been substantial research in software analytics for effort estimation in
traditional software projects, little work has been done for estimation in agile projects …
traditional software projects, little work has been done for estimation in agile projects …
A parallel computing simulation-based multi-objective optimization framework for economic analysis of building energy retrofit: A case study in Iran
The building sector represents a large share of rising global energy demand. Improving
energy efficiency in existing building stock is a crucial strategy. Adopting the best energy …
energy efficiency in existing building stock is a crucial strategy. Adopting the best energy …
Clami: Defect prediction on unlabeled datasets (t)
Defect prediction on new projects or projects with limited historical data is an interesting
problem in software engineering. This is largely because it is difficult to collect defect …
problem in software engineering. This is largely because it is difficult to collect defect …
Multi-stage and multi-objective optimization for energy retrofitting a developed hospital reference building: A new approach to assess cost-optimality
Abstract The 'Energy Performance of Buildings Directive'Recast (ie, 2010/31/EU) establishes
that building energy retrofit should pursue “cost-optimal levels”. However, a reliable and …
that building energy retrofit should pursue “cost-optimal levels”. However, a reliable and …
On the value of ensemble effort estimation
Background: Despite decades of research, there is no consensus on which software effort
estimation methods produce the most accurate models. Aim: Prior work has reported that …
estimation methods produce the most accurate models. Aim: Prior work has reported that …
A new methodology for cost-optimal analysis by means of the multi-objective optimization of building energy performance
The recast version of the Energy Performance of Buildings Directive (2010/31/EU) proposes
a comparative methodology aimed at defining the energy performance of buildings “with a …
a comparative methodology aimed at defining the energy performance of buildings “with a …