Naive Bayes: applications, variations and vulnerabilities: a review of literature with code snippets for implementation
I Wickramasinghe, H Kalutarage - Soft Computing, 2021 - Springer
Naïve Bayes (NB) is a well-known probabilistic classification algorithm. It is a simple but
efficient algorithm with a wide variety of real-world applications, ranging from product …
efficient algorithm with a wide variety of real-world applications, ranging from product …
Asset Management in Machine Learning: State-of-research and State-of-practice
Machine learning components are essential for today's software systems, causing a need to
adapt traditional software engineering practices when developing machine-learning-based …
adapt traditional software engineering practices when developing machine-learning-based …
Learning software configuration spaces: A systematic literature review
Most modern software systems (operating systems like Linux or Android, Web browsers like
Firefox or Chrome, video encoders like ffmpeg, x264 or VLC, mobile and cloud applications …
Firefox or Chrome, video encoders like ffmpeg, x264 or VLC, mobile and cloud applications …
Sampling effect on performance prediction of configurable systems: A case study
Numerous software systems are highly configurable and provide a myriad of configuration
options that users can tune to fit their functional and performance requirements (eg …
options that users can tune to fit their functional and performance requirements (eg …
An empirical study toward dealing with noise and class imbalance issues in software defect prediction
SK Pandey, AK Tripathi - Soft Computing, 2021 - Springer
The quality of the defect datasets is a critical issue in the domain of software defect
prediction (SDP). These datasets are obtained through the mining of software repositories …
prediction (SDP). These datasets are obtained through the mining of software repositories …
Asset management in machine learning: A survey
Machine Learning (ML) techniques are becoming essential components of many software
systems today, causing an increasing need to adapt traditional software engineering …
systems today, causing an increasing need to adapt traditional software engineering …
Tackling combinatorial explosion: a study of industrial needs and practices for analyzing highly configurable systems
Highly configurable systems are complex pieces of software. To tackle this complexity,
hundreds of dedicated analysis techniques have been conceived, many of which able to …
hundreds of dedicated analysis techniques have been conceived, many of which able to …
Does configuration encoding matter in learning software performance? An empirical study on encoding schemes
Learning and predicting the performance of a configurable software system helps to provide
better quality assurance. One important engineering decision therein is how to encode the …
better quality assurance. One important engineering decision therein is how to encode the …
Feature-oriented defect prediction
S Strüder, M Mukelabai, D Strüber… - Proceedings of the 24th …, 2020 - dl.acm.org
Software errors are a major nuisance in software development and can lead not only to
reputation damages, but also to considerable financial losses for companies. Therefore …
reputation damages, but also to considerable financial losses for companies. Therefore …
Predicting configuration performance in multiple environments with sequential meta-learning
Learning and predicting the performance of given software configurations are of high
importance to many software engineering activities. While configurable software systems will …
importance to many software engineering activities. While configurable software systems will …