Hybrid functional link artificial neural network approach for predicting maintainability of object-oriented software

Kumar, Lov; Rath, Santanu Kumar

doi:10.1016/j.jss.2016.01.003

Cited by 37 publications

(16 citation statements)

References 26 publications

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“…(6) for each dataset. [4] 0.4464 0.3833 CSA [9] 0.0937 0.1587 CSA(PCA) [9] 0.0998 0.1181 CSA(RST) [9] 0.0537 0.1374 Jaya Algorithm [13] 0.0235 0.0381 Proposed 0.0211 0.0272…”

Section: Resultsmentioning

confidence: 99%

“…This paper focuses on the CK and Li & Henry metrics to determine software quality. The metrics are used to compute the number of lines changed per class in the software which in turn determines the maintainability of the software [9]. This work takes some changes directly proportional to the complexity of software, i.e., higher software complexity will lead to a large number of changes per class and vice-versa.…”

Section: Introductionmentioning

confidence: 99%

“…The techniques are given by the authors of [10 -12] work on the original given set of attributes which includes relevant as well as noisy attributes resulting low performance. While the author of [9], uses various combinations of optimization technique along with neural network to determine the software maintainability. The technique is FLANN-CSA, i.e., functional line artificial neural network with clone selection algorithm.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Jaya Algorithm and Artificial Neural Network Based Approach for Object- Oriented Software Quality Analysis

Bansal¹,

Agrawal²

2018

IJIES

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This paper develops a technique by using Jaya algorithm and feed-forward neural network to determine the quality of object-oriented software by using Chidamber & Kemerer (CK) along with Li & Henry metrics. The technique basically focuses on the maintainability factor of software quality which in turn depends upon the software complexity. The software complexity is directly proportional to the number of changes done per class which is determined by the technique. The analysis has been done on UIMS (User Interface Management System) and QUES (Quality Evaluation System) datasets by using the mean absolute error as the analysis parameter. The reduction in the mean absolute error as compared to the existing state of art techniques along with the individual component of proposed technique proves the significance of the technique.

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“…(6) for each dataset. [4] 0.4464 0.3833 CSA [9] 0.0937 0.1587 CSA(PCA) [9] 0.0998 0.1181 CSA(RST) [9] 0.0537 0.1374 Jaya Algorithm [13] 0.0235 0.0381 Proposed 0.0211 0.0272…”

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Jaya Algorithm and Artificial Neural Network Based Approach for Object- Oriented Software Quality Analysis

Bansal¹,

Agrawal²

2018

IJIES

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“…A considerable amount of studies have employed different models and techniques for predicting software maintenance using basic metrics and models: McCall's model in 1976 [20], Barry Boehm's quality model presented in 1978 [1], Sneed-Mercy Model in 1985 [23], Li-Henry Model in 1993 [16], Marcela Genero Model in 2004 [8]. Later, slightly different techniques were used from simple statistical models such as regression [25] to machine learning [7,24], and deep learning [9,13]. To predict maintainability of software, different metrics have been proposed in literature.…”

Section: Related Researchmentioning

confidence: 99%

An Empirical Analysis of the Maintainability Evolution of Open Source Systems

Kapllani

Khomyakov

Mirgalimova

et al. 2020

IFIP Advances in Information and Communication Technology

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Maintainability is a key factor for the evolution of an open source system due to the highly distributed development teams that contribute to many projects. In the literature there are a number of different approaches that has been developed to evaluate the maintainability of a product but almost each method has been developed in an independent way without leveraging on the existing work and with almost no independent evaluation of the performance of the models. In most of the cases, the models are only validated through a limited set of projects only by the people that propose the specific approach. This paper is a first step towards a different direction focusing on the independent application of the existing models to popular open source projects.

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“…Kumar and S.U. Rath [13] designed a predicting maintainability model with the help of three AI techniques such as particle swarm optimization (PSO), hybrid approach of functional link artificial neural network (FLANN) with genetic algorithm (GA), and clonal selection algorithm (CSA), i.e., FLANN-CSA (FCSA), FLANN-Genetic (FGA and AFGA), FLANN-PSO (FPSO and MFPSO). The maintainability on the two case studies were predicted by this AI techniques, and the two study case are namely; (1) User Interface System (UIMS) and (2) Quality Evaluation System (QUES).…”

Section: Literature Reviewmentioning

confidence: 99%

Automization of Object Oriented Design Using Back Propagation Neural Network for Better Maintainability of Software

Vorsu¹,

Arramraju²,

Bhanothu³

2018

IJIES

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Object Oriented Program (OOP) provides the way to reuse the program by pre-implementing functionalities in the software. It is difficult to develop the object oriented software, which is important in the computer programing. For OOP, modularization mainly depends on the class. There are many methods present for the assigning responsibilities, but most of them are based on the human for decision making. In this research, back propagation neural network (BPNN) was used to provide the solution to object oriented design of the software. The Cinema Booking System (CBS) was taken as the input documentation and Formal Concept analysis (FCA) then found the relationship of the element in the lattice manner, after that the relationship was set with each other. The result showed that the proposed system outperformed the existing system and also the design made manually.

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Hybrid functional link artificial neural network approach for predicting maintainability of object-oriented software

Cited by 37 publications

References 26 publications

Jaya Algorithm and Artificial Neural Network Based Approach for Object- Oriented Software Quality Analysis

Jaya Algorithm and Artificial Neural Network Based Approach for Object- Oriented Software Quality Analysis

An Empirical Analysis of the Maintainability Evolution of Open Source Systems

Automization of Object Oriented Design Using Back Propagation Neural Network for Better Maintainability of Software

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