A soft computing based approach to estimate reusability of software components

Sagar, Shrddha; Nerurkar, N. W.; Sharma, Arun

doi:10.1145/1811226.1811235

Cited by 7 publications

(3 citation statements)

References 12 publications

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“…Sagar et. al [11] Diwaker and Tomar [14] defined a Particle Swarm Optimization based fitness function using functionality, average execution time, interface complexity, which can be considered as CBS system metrics. According to the authors, sub-parameters like interaction among components, reusability, and resource usage were also used.…”

Section: Related Workmentioning

confidence: 99%

Relationship Between CBS Quality Parameters for Assessment of Computational Intelligence Techniques

Yadav¹,

Kishan²

2022

ijarcs

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Software reliability plays a vital role in the emerging field of digitalization. Everyone wants cost and time-efficient software along with reliability which is achieved using CBS. In CBS, if the individual components are computed for a large or complicated system, then integration becomes complex which results in difficulty in predicting CBSR. To solve this problem several computational intelligence techniques such as SVM, ACO, PSO, ABC, GA, Neural network, are used but in our paper, we have focused on optimization techniques Fuzzy, ACO, ABC, PSO. These techniques help in estimating and predicting reliability models for CBS. Also, we have done, an assessment and comparative analysis based on a literature review of ABC, ACO, and PSO that have also been presented, for choosing suitable parameters for software reliability modeling.

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Section: Related Workmentioning

confidence: 99%

Relationship Between CBS Quality Parameters for Assessment of Computational Intelligence Techniques

Yadav¹,

Kishan²

2022

ijarcs

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“…Sagar et al [39] extends the work in [38] to estimate the reusability of software components by using Mamdani-based fuzzy inference system. The proposed work is validated against two small classroom-based components.…”

Section: Reusability Metrics For Software Componentsmentioning

confidence: 99%

Quality aspects for component‐based systems: A metrics based approach

Kumar¹,

Sharma²,

Kumar

et al. 2012

Softw Pract Exp

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SUMMARY In component‐based development, software systems are built by assembling components already developed and prepared for integration. To estimate the quality of components, complexity, reusability, dependability, and maintainability are the key aspects. The quality of an individual component influences the quality of the overall system. Therefore, there is a strong need to select the best quality component, both from functional and nonfunctional aspects. The present paper produces a critical analysis of metrics for various quality aspects for components and component‐based systems. These aspects include four main quality factors: complexity, dependency, reusability, and maintainability. A systematic study is applied to find as much literature as possible. A total of 49 papers were found suitable after a defined search criteria. The analysis provided in this paper has a different objective as we focused on efficiency and practical ability of the proposed approach in the selected papers. The various key attributes from these two are defined. Each paper is evaluated based on the various key parameters viz. metrics definition, implementation technique, validation, usability, data source, comparative analysis, practicability, and extendibility. The paper critically examines various quality aspects and their metrics for component‐based systems. In some papers, authors have also compared the results with other techniques. For characteristics like complexity and dependency, most of the proposed metrics are analytical. Soft computing and evolutionary approaches are either not being used or much less explored so far for these aspects, which may be the future concern for the researchers. In addition, hybrid approaches like neuro‐fuzzy, neuro‐genetic, etc., may also be examined for evaluation of these aspects. However, to conclude that one particular technique is better than others may not be appropriate. It may be true for one characteristic by considering different set of inputs and dataset but may not be true for the same with different inputs. The intension in the proposed work is to give a score for each metric proposed by the researchers based on the selected parameters, but certainly not to criticize any research contribution by authors. Copyright © 2012 John Wiley & Sons, Ltd.

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“…The CISD environment is the process of assembling existing software components in an application such that they satisfy a predefined functionality. To assess the reuse of component, it is important to estimate reusability of these components [2].…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Logic Control Neural Network Hybrid System for Identification, Classification of Software Reusability Components through Relationships of Lattice Factors

Devi¹,

Rama²

2018

IJET

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The software reusability mode is highly required field for successful execution of artificial intelligence, machine learning based applications to fulfill the present and future human needs. The identification, classification and measuring the required components are key-roles concerns in fast development of software reusability components for producing the high quality software. This paper is proposing the Fuzzy Logic Controller Neural Network Hybrid System which is implicated to recognize the affecting factors of component reusability execution by instituting the strong, week relationships in among these considered factors to fulfill the user requirement. This approach considered eleven effecting factors such as Portability, Reliability, Complexity, Efficiency, Quality, Security, Cost, Maintainability, Cohesion, Availability and Flexibility along with their related attribute metrics. This paper has composed with four major objectives such as: the comparative analysis of Fuzzy Logic Control System and Neural Networks with their advantages and execution flow; The implications of Fuzzy Logic Control Neural Network Hybrid System architecture design for concern problem; The proposed FLCNNHS based algorithm and execution data flow diagram for executing the considered software reusability effecting factors along with their supporting attributes metrics for identification and Classification of Reusability Components through Strong, Week Relationships of Lattice Factors which is implacable for designing the better quality software product; and described the experimental analysis and results through proposed algorithmic approach. This innovative approach is more helpful for software developers to choose highly accurate components which are more required to build the high efficiency secure systems.

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A soft computing based approach to estimate reusability of software components

Cited by 7 publications

References 12 publications

Relationship Between CBS Quality Parameters for Assessment of Computational Intelligence Techniques

Relationship Between CBS Quality Parameters for Assessment of Computational Intelligence Techniques

Quality aspects for component‐based systems: A metrics based approach

Fuzzy Logic Control Neural Network Hybrid System for Identification, Classification of Software Reusability Components through Relationships of Lattice Factors

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