A Fuzzy Logic Approach to Measure Complexity of Generic Aspect-Oriented Systems.

Kumar, Rajesh; Grover, P. S.; Kumar, Avadhesh

doi:10.5381/jot.2010.9.3.a1

Cited by 9 publications

(3 citation statements)

References 13 publications

(10 reference statements)

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“…Reusability can be assessed with the help of those quality characteristics on which reusability depends in that particular domain. These may be internal characteristics such as cohesion [5], coupling [6], and complexity [7,8] or external characteristics such as maintainability, understandability, modularity, and adaptability [9,10,11] of aspect-oriented systems. Here, we are focused on assessment of reusability of the projects developed in AspectJ [12], which is an extension of Java.…”

Section: Introductionmentioning

confidence: 99%

Assessment of reusability in aspect-oriented systems using fuzzy logic

Nerurkar

Kumar

Shrivastava

2010

SIGSOFT Softw. Eng. Notes

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Reusability of the software systems is becoming a very important factor due to rapid software development and increasing complexity. Software reusability improves the quality of software product by reducing development time, effort and cost. Researchers have explored many methodologies in order to assess the reusability of Object-Oriented (OO) software systems but the assessment of the reusability of Aspect-Oriented (AO) software systems is underexplored. Aspect-Oriented Software Development (AOSD) is an emerging paradigm that aims to modularize the crosscutting concerns in an application, which cannot be modularized using traditional procedure-oriented and object-oriented approaches. By applying an aspect-oriented approach, such concerns can be isolated resulting in the increase maintainability and reusability of the system. In this paper, we propose a reusability model for aspect-oriented systems and assess it using fuzzy logic technique.

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Section: Introductionmentioning

confidence: 99%

Assessment of reusability in aspect-oriented systems using fuzzy logic

Nerurkar

Kumar

Shrivastava

2010

SIGSOFT Softw. Eng. Notes

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“…We have used the complexity model proposed by [14,15] for measuring code complexity as discussed in chapter 3. Tool is based upon the concept of fuzzy logic [16].…”

Section: Complexity Calculationmentioning

confidence: 99%

Correlation between Various Quality Characteristics for Aspect-Oriented Systems

Arora¹,

Singhal²,

Bansal³

2012

IJCA

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Aspect-oriented system is a new emerging technique of software development that provides mechanism for implementing cross-cutting concerns. Quality assessment of important characteristics like cohesion, coupling, complexity, reusability, maintaibility, etc. is fairly unexplored for Aspectoriented systems. Through this research work we have tried to find out the correlation between some of the quality characteristic of aspect-oriented system. We have established correlation between cohesion and complexity, Cohesion and Changeability. Then we have find out that whether cohesion metric can be used as indicator for assessing complexity and changeability of aspect oriented system. Then will find out that whether cohesion metric and complexity can be used as indicator for assessing reusability of aspect oriented system through finding the correlation between cohesion and reusability, and complexity and reusability.

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“…Fuzzy Logic is a powerful problem-solving methodology to deal with imprecision and information granularity [12] [16]. A fuzzy model is used when the system is not suitable for analysis by conventional approach or when the available data is uncertain, inaccurate or vague.…”

Section: Background On Multi-criteria Fuzzy Based Approachmentioning

confidence: 99%

Prediction of Software Requirements Stability Based on Complexity Point Measurement Using Multi-Criteria Fuzzy Approach

Francis¹,

Christopher²

2012

IJSEA

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Many software projects fail due to instable requirements and lack of managing the requirements changes efficiently. Software Requirements Stability Index Metric (RSI) helps to evaluate the overall stability of requirements and also keep track of the project status. Higher the stability, less changes tends to propagate. The existing system use Function Point modeling for measuring the Requirements Stability. However, the main drawback of the existing modeling is that the complexity of non-functional requirements has not been measured for Requirements KEYWORDS: Multi-Criteria Fuzzy Based Approach, Functional Requirement Complexity, Non-Functional Requirement Complexity, Input Output Complexity, Interface Complexity, File Complexity, Software Complexity Point Measurement, Requirements Stability Index. INTRODUCTIONRequirements Elicitation is the most important stage in the Software Development Life Cycle Process. If the requirements have not been captured correctly during the Elicitation process, then the whole development process will fail which results in time and monetary costs [18]. Software developers often start with unclear, ambiguous, and incomplete requirements with inaccurate understanding of the user needs or insufficient requirements. Therefore, requirements development and management are the start point of the software development process. Software system needs to evolve. In particular, changes in the requirements may be related to the addition of new functionalities, modification to the existing ones, deleting the functionalities which are International Journal of Software Engineering & Applications (IJSEA), Vol.3, No.6, November 2012 102 obsolete or to the improvement in the quality of service offered [10]. Requirements changes not only cause software defects but also cause in delay of delivery of the software project. Requirements changes at the later stage can cause uncertainty in the software development. Sometimes, these requirement changes will affect the quality of the software. For requirements engineering, the challenging issue is not the requirements change. It is how to deal with the change and how to measure them. For measuring the change, measure the software complexity. IEEE defines software complexity as "the degree to which a system or component has a design or implementation that is difficult to understand or verify" [1].Software Complexity Measurement can be classified into three categories: Size, Structure and Quality Measurement [17]. In present, there are many algorithmic models and non-algorithmic models have been developed to measure the complexity of the software [20]. Some of the famous algorithmic models are Function Point Modeling, Constructive Cost Model (COCOMO), Software Life Cycle Management model (SLIM). Non-algorithmic techniques include Price-toWin, Expert Judgment and Machine learning approaches. Machine Learning is used to group together a set of techniques that embody some of the facets of human mind. For example, fuzzy systems, analogy, regressi...

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A Fuzzy Logic Approach to Measure Complexity of Generic Aspect-Oriented Systems.

Cited by 9 publications

References 13 publications

Assessment of reusability in aspect-oriented systems using fuzzy logic

Assessment of reusability in aspect-oriented systems using fuzzy logic

Correlation between Various Quality Characteristics for Aspect-Oriented Systems

Prediction of Software Requirements Stability Based on Complexity Point Measurement Using Multi-Criteria Fuzzy Approach

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