Engineering ai systems: A research agenda
Artificial intelligence (AI) and machine learning (ML) are increasingly broadly adopted in
industry. However, based on well over a dozen case studies, we have learned that …
industry. However, based on well over a dozen case studies, we have learned that …
Automotive software engineering: A systematic map** study
The automotive industry is going through a fundamental change by moving from a
mechanical to a software-intensive industry in which most innovation and competition rely …
mechanical to a software-intensive industry in which most innovation and competition rely …
Modeling and analysis of reliability of multi-release open source software incorporating both fault detection and correction processes
Large software systems require regular upgrading that tries to correct the reported faults in
previous versions and add some functions to meet new requirements. It is thus necessary to …
previous versions and add some functions to meet new requirements. It is thus necessary to …
Decision support system for optimal selection of software reliability growth models using a hybrid approach
A hybrid approach, namely “entropy-combinative distance-Based assessment (CODAS-E),”
is proposed and presented to select and rank software reliability growth models based on …
is proposed and presented to select and rank software reliability growth models based on …
Parameter optimization of software reliability growth model with S-shaped testing-effort function using improved swarm intelligent optimization
C **, SW ** - Applied Soft Computing, 2016 - Elsevier
Software reliability growth model (SRGM) with testing-effort function (TEF) is very helpful for
software developers and has been widely accepted and applied. However, each SRGM with …
software developers and has been widely accepted and applied. However, each SRGM with …
Chapter 8 Recognizing Lines of Code Violating Company-Specific Coding Guidelines Using Machine Learning
Software developers in big and medium-size companies are working with millions of lines of
code in their codebases. Assuring the quality of this code has shifted from simple defect …
code in their codebases. Assuring the quality of this code has shifted from simple defect …
A two-phase software reliability modeling involving with software fault dependency and imperfect fault removal
Most existing software reliability growth models (SGRMs) often assume software faults are
mutually independent and the detected faults can be perfectly removed. However, those two …
mutually independent and the detected faults can be perfectly removed. However, those two …
Neuro-genetic approach on logistic model based software reliability prediction
In this paper, we propose a multi-layer feedforward artificial neural network (ANN) based
logistic growth curve model (LGCM) for software reliability estimation and prediction. We …
logistic growth curve model (LGCM) for software reliability estimation and prediction. We …
A software reliability model incorporating martingale process with gamma-distributed environmental factors
As the increasing application of software system in various industry, software reliability gains
more attention from the researchers and practitioners in the past few decades. The goal of …
more attention from the researchers and practitioners in the past few decades. The goal of …
An ideal software release policy for an improved software reliability growth model incorporating imperfect debugging with fault removal efficiency and change point
This paper presents a general software reliability growth model (SRGM) based on non-
homogeneous Poisson process (NHPP) and optimal software release policy with cost and …
homogeneous Poisson process (NHPP) and optimal software release policy with cost and …