Machine learning for software engineering: A tertiary study
Machine learning (ML) techniques increase the effectiveness of software engineering (SE)
lifecycle activities. We systematically collected, quality-assessed, summarized, and …
lifecycle activities. We systematically collected, quality-assessed, summarized, and …
Toward improving the efficiency of software development effort estimation via clustering analysis
Introduction: The precise estimation of software effort is a significant difficulty that project
managers encounter during software development. Inaccurate forecasting leads to either …
managers encounter during software development. Inaccurate forecasting leads to either …
Parametric software effort estimation based on optimizing correction factors and multiple linear regression
Context: Effort estimation is one of the essential phases that must be accurately predicted in
the early stage of software project development. Currently, solving problems that affect the …
the early stage of software project development. Currently, solving problems that affect the …
A random forest model for early-stage software effort estimation for the SEERA dataset
Context Publicly available software cost estimation datasets are outdated and may not
represent current industrial environments. Thus most research has concentrated on the …
represent current industrial environments. Thus most research has concentrated on the …
Effective Software Effort Estimation enabling Digital Transformation
Software effort estimation is a necessary component of software development projects that
belong to industrial software systems and digital transformation initiatives. Digital …
belong to industrial software systems and digital transformation initiatives. Digital …
Echo: An approach to enhance use case quality exploiting large language models
UML use cases are commonly used in software engineering to specify the functional
requirements of a system since they are an effective tool for interacting with stakeholders …
requirements of a system since they are an effective tool for interacting with stakeholders …
Propose-specific information related to prediction level at X and mean magnitude of relative error: A case study of software effort estimation
The prediction level at x (PRED (x)) and mean magnitude of relative error (MMRE) are
measured based on the magnitude of relative error between real and predicted values. They …
measured based on the magnitude of relative error between real and predicted values. They …
Using Machine Learning and Simplified Functional Measures to Estimate Software Development Effort
Functional size measures are often used as the basis for estimating development effort,
because they are available in the early stages of software development. Several simplified …
because they are available in the early stages of software development. Several simplified …
On the value of project productivity for early effort estimation
In general, estimating software effort using a Use Case Point (UCP) size requires the use of
productivity as a second prediction factor. However, there are three drawbacks to this …
productivity as a second prediction factor. However, there are three drawbacks to this …
An empirical study on software test effort estimation for defense projects
E Cibir, TE Ayyildiz - IEEE Access, 2022 - ieeexplore.ieee.org
Effort estimation of software testing plays a vital role in the effective completion of testing. In
particular, software test effort estimation in defense projects is not an easy and simple …
particular, software test effort estimation in defense projects is not an easy and simple …