Enhancement and Comparison of Ant Colony Optimization for Software Reliability Models

Shanmugam, None

doi:10.3844/jcssp.2013.1232.1240

Cited by 11 publications

(1 citation statement)

References 10 publications

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“…Latha Shanmugam et al[57] studied enhancement and Comparison of Ant Colony Optimization Methods for Software Reliability Models. The Enhanced method shows significant advantages in finding the goodness of fit for software reliability model such as finite and infinite failure Poisson model and binomial models.…”

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confidence: 99%

Software Reliability Modeling using Soft Computing Techniques: Critical Review

Kaswan¹,

Choudhary²,

Sharma³

2015

IJITCS

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Software reliability models assess the reliability by predicting faults for the software. Reliability is a real world phenomenon with many associated real-time problems. To obtain solutions to problems quickly, accurately and acceptably, a large number of soft computing techniques have been developed, but it is very difficult to find out which one is the most suitable and can be used globally. In this paper, we have provided an overview of existing soft computing techniques, and then critically analyzed the work done by the various researchers in the field of software reliability. Further to this, we have also compared soft computing techniques in terms of software reliability modeling capabilities.

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confidence: 99%

Software Reliability Modeling using Soft Computing Techniques: Critical Review

Kaswan¹,

Choudhary²,

Sharma³

2015

IJITCS

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A Comprehensive Review on Software Reliability Growth Models utilizing Soft Computing Approaches

Lohmor

Sagar²

2016

Advances in Intelligent Systems and Computing

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Prediction of Software Reliability using Bio Inspired Soft Computing Techniques

et al. 2018

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A lot of models have been made for predicting software reliability. The reliability models are restricted to using particular types of methodologies and restricted number of parameters. There are a number of techniques and methodologies that may be used for reliability prediction. There is need to focus on parameters consideration while estimating reliability. The reliability of a system may increase or decreases depending on the selection of different parameters used. Thus there is need to identify factors that heavily affecting the reliability of the system. In present days, reusability is mostly used in the various area of research. Reusability is the basis of Component-Based System (CBS). The cost, time and human skill can be saved using Component-Based Software Engineering (CBSE) concepts. CBSE metrics may be used to assess those techniques which are more suitable for estimating system reliability. Soft computing is used for small as well as large-scale problems where it is difficult to find accurate results due to uncertainty or randomness. Several possibilities are available to apply soft computing techniques in medicine related problems. Clinical science of medicine using fuzzy-logic, neural network methodology significantly while basic science of medicine using neural-networks-genetic algorithm most frequently and preferably. There is unavoidable interest shown by medical scientists to use the various soft computing methodologies in genetics, physiology, radiology, cardiology and neurology discipline. CBSE boost users to reuse the past and existing software for making new products to provide quality with a saving of time, memory space, and money. This paper focused on assessment of commonly used soft computing technique like Genetic Algorithm (GA), Neural-Network (NN), Fuzzy Logic, Support Vector Machine (SVM), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), and Artificial Bee Colony (ABC). This paper presents working of soft computing techniques and assessment of soft computing techniques to predict reliability. The parameter considered while estimating and prediction of reliability are also discussed. This study can be used in estimation and prediction of the reliability of various instruments used in the medical system, software engineering, computer engineering and mechanical engineering also. These concepts can be applied to both software and hardware, to predict the reliability using CBSE.

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Enhancement and Comparison of Ant Colony Optimization for Software Reliability Models

Cited by 11 publications

References 10 publications

Software Reliability Modeling using Soft Computing Techniques: Critical Review

Software Reliability Modeling using Soft Computing Techniques: Critical Review

A Comprehensive Review on Software Reliability Growth Models utilizing Soft Computing Approaches

Prediction of Software Reliability using Bio Inspired Soft Computing Techniques

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