Show/Hide Menu
Hide/Show Apps
anonymousUser
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Açık Bilim Politikası
Açık Bilim Politikası
Frequently Asked Questions
Frequently Asked Questions
Browse
Browse
By Issue Date
By Issue Date
Authors
Authors
Titles
Titles
Subjects
Subjects
Communities & Collections
Communities & Collections
Improved Software Reliability Prediction by Using Model Stacking and Averaging
Date
2019-01-01
Author
Karaomer, Rabia Burcu
Yet, Barbaros
CHOUSEİNOGLOU, OUMOUT
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
8
views
0
downloads
Software reliability is an important factor for the success of a software project. Accurate modelling of software reliability enables estimation of remaining defects, the timing of deployment and required future effort. These factors contribute to successful planning of project schedule and resources. A number of software reliability prediction models have been proposed, each with different assumptions regarding software defect introduction and discovery. The performances of these models differ depending on the properties of the software project they are applied. Model averaging and stacking techniques offer flexible approaches for combining the predictions of different models based on observed data. In this study, we use model stacking and averaging approaches to combine the predictions of four well-known Non-Homogeneous Poisson Process (NHPP) software reliability models. These models have different assumptions with respect to failure rate, residual defects and the overall reliability of the software being investigated. We evaluate these techniques in simulated experiments and then apply the techniques to defect data collected from four software projects with different characteristics. Our results show that stacking and averaging approaches provide a robust approach with consistently high-performance results for both simulated defect experiments and actual defect data, whereas the performance of individual prediction models varies between different projects.
Subject Keywords
Non-homogeneous Poisson process models
,
Failure prediction
,
Stacking
,
Model averaging
,
Software reliability models
URI
https://hdl.handle.net/11511/57050
DOI
https://doi.org/10.1109/seaa.2019.00038
Collections
Graduate School of Informatics, Conference / Seminar