Results 61 to 70 of about 9,202 (166)

Software fault prediction of unlabeled program modules

, 2009
Software metrics and fault data belonging to a previous software version are used to build the software fault prediction model for the next release of the software. Until now, different classification algorithms have been used to build this kind of models. However, there are cases when previous fault data are not present; and hence, supervised learning
Catal, C., Sevim, U., Diri, B.
openaire   +2 more sources

FSBOA: feature selection using bat optimization algorithm for software fault detection

Discover Internet of Things
Feature selection (FS) plays a crucial role in software fault prediction (SFP), aiming to identify a subset of relevant and discriminative features from a large pool of software metrics.
Yoginee Surendra Pethe, Mahendra Kumar Gourisaria, Pradeep Kumar Singh, Himansu Das   +3 more
doaj   +1 more source

A software reliability model for open source big data system considering fault introduction and fault removal efficiency

Journal of Big Data
Reliability is critical to the stable operation of open source big data system software. So far, the reliability modeling and evaluation of open source big data system software is still in its early stages, and traditional software reliability models are
Jinyong Wang, Haijun Geng, Pengda Li
doaj   +1 more source

Nature-inspired approaches in Software Fault Prediction

INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
In software engineering, predicting software faults is a crucial task for ensuring high software quality and reducing costs. In recent years, nature inspired approaches have been increasingly used in software fault prediction. In this paper, we explore the effectiveness of six nature inspired algorithms, namely Ant Colony, Particle Swarm ...
openaire   +1 more source

Software-defined self-learning control system for industrial robots by using reinforcement learning. [PDF]

Sci Rep
Moon J, Kim M, Lee T, Um J.
europepmc   +1 more source

Predicting Software Fault Proneness Using Machine Learning [PDF]

, 2018
Context: Continuous Integration (CI) is a DevOps technique which is widely used in practice. Studies show that its adoption rates will increase even further. At the same time, it is argued that maintaining product quality requires extensive and time consuming, testing and code reviews.
openaire  

Edge computing task scheduling mechanism based on multi-dimensional feature extraction and attention fusion. [PDF]

PLoS One
Zhang S, Li JY, Yu P.
europepmc   +1 more source

BugPrioritizeAI for multimodal test case prioritisation using bug reports, code changes, and test metadata. [PDF]

Sci Rep
Kalyani P, Rao CP, Goparaju B, Babu KK, Kandimalla PCR.   +4 more
europepmc   +1 more source

Enhancing fault detection in new energy vehicles via novel ensemble approach. [PDF]

Sci Rep
Akhtar I, Nabeel M, Shahid U, Munir K, Raza A, Noya ID, Villar SG, Ashraf I.   +7 more
europepmc   +1 more source

Research on a General-Type Hydraulic Valve Leakage Diagnosis Method Based on CLAF-MTL Feature Deep Integration. [PDF]

Sensors (Basel)
Tong C, Xiong Y, Xu X, Wu Y.
europepmc   +1 more source