Assessment of reusability in aspect-oriented systems using fuzzy logic

Nerurkar, N. W.; Kumar, Avadhesh; Shrivastava, Pallavi

doi:10.1145/1838687.1838706

Cited by 15 publications

(9 citation statements)

References 22 publications

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“…Liang and Lien extend the quality model of the ISO/IEC 9126 standard [64] to encompass enterprise resource planning (ERP) software-related properties [65]; moreover, they describe the selection of the optimal ERP software as a multi-criteria decision-making problem and use a fuzzy analytic hierarchy process to produce a ranking with regard to the criteria considered [65]. In addition, Aggarwal et al, Nerurkar et al, Canfora et al, and Mittal and Bhatia applied fuzzy modelling to consider qualitative and quantitative data to assess the reusability and maintainability of software components in [103][104][105][106]. Galli et al carried out a pilot study in [18,107] to test the performance of the different fuzzy inference methods with different membership functions in the context of modelling execution tracing quality.…”

Section: Adaptive Methods In Quality Modellingmentioning

confidence: 99%

Genetic Algorithm-Based Fuzzy Inference System for Describing Execution Tracing Quality

2021

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Execution tracing is a tool used in the course of software development and software maintenance to identify the internal routes of execution and state changes while the software operates. Its quality has a high influence on the duration of the analysis required to locate software faults. Nevertheless, execution tracing quality has not been described by a quality model, which is an impediment while measuring software product quality. In addition, such a model needs to consider uncertainty, as the underlying factors involve human analysis and assessment. The goal of this study is to address both issues and to fill the gap by defining a quality model for execution tracing. The data collection was conducted on a defined study population with the inclusion of software professionals to consider their accumulated experiences; moreover, the data were processed by genetic algorithms to identify the linguistic rules of a fuzzy inference system. The linguistic rules constitute a human-interpretable rule set that offers further insights into the problem domain. The study found that the quality properties accuracy, design and implementation have the strongest impact on the quality of execution tracing, while the property legibility is necessary but not completely inevitable. Furthermore, the quality property security shows adverse effects on the quality of execution tracing, but its presence is required to some extent to avoid leaking information and to satisfy legal expectations. The created model is able to describe execution tracing quality appropriately. In future work, the researchers plan to link the constructed quality model to overall software product quality frameworks to consider execution tracing quality with regard to software product quality as a whole. In addition, the simplification of the mathematically complex model is also planned to ensure an easy-to-tailor approach to specific application domains.

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Section: Adaptive Methods In Quality Modellingmentioning

confidence: 99%

Genetic Algorithm-Based Fuzzy Inference System for Describing Execution Tracing Quality

2021

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“…Canfora, Aggarwal, Nerurkar amongst others have already illustrated how fuzzy mathematics can help to make judgements or predictions in connection with software maintainability [1], [3], [24] or reusability [26], [32]. However, these models cannot help with the assessment of software product quality as a whole because they are not linked to extensive software product quality frameworks like ISO/IEC 25010 [10].…”

Section: Related Workmentioning

confidence: 99%

“…Nerurkar, Kumar, Shrivastava in [26] proposed a model based on type-1 fuzzy logic for reusability of aspect-oriented systems. Singh, Bhatia, Sangwan in [32] examined different soft computing techniques for software reusability assessment.…”

Section: Related Workmentioning

confidence: 99%

Modelling Execution Tracing Quality by Means of Type-1 Fuzzy Logic

Galli

Chiclana

Carter

et al. 2013

APH

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Execution tracing quality is a crucial characteristic which contributes to the overall software product quality though the present quality frameworks neglect this property. In the scope of this pilot study the authors introduce a process to create a model for describing execution tracing as a quality property; moreover, the performance of four different models created is compared. The process and the models presented are capable of capturing subjective uncertainty which is an intrinsic part of the quality measurement process. In addition, the possibility of linking the presented models to software product quality frameworks is also illustrated.

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“…Figure 2. Measured values of all metrics are always normalized between number 0 and 1 [17,[25][26][27][28]. The result for all metrics will be used as an input to the fuzzy inference system (FIS) for measuring the reusability level of the component (overall component reusability).…”

Section: Component Reusability Evaluation Approach (Crea) 31 Softwamentioning

confidence: 99%

Development metrics measurement level for component reusability evaluation approach (CREA)

Ismail¹,

Mohd²,

Jalil³

et al. 2019

IJECE

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The study of software component reuse is rising in software development field and one of the methods used to reduce the production cost and time. Among the problems faced by software developers in component reuse, is the difficulty to determine which set of components are suitable to use in new software development. Thus, this study was conducted with the purpose; to define the characteristics of software component reusability evaluation approach (CREA) based on experienced software developer’s feedback, and to estimate the measurement level for each of the predefined metric. Three characteristics and sub characteristics, namely understandability (documentation level and observality), adaptability (customizability), and portability (external dependency) were identified that have been used to develop the metrics for CREA. The result for all metrics will be used as an input to the fuzzy inference system (FIS) for measuring the reusability level of the component.

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Assessment of reusability in aspect-oriented systems using fuzzy logic

Cited by 15 publications

References 22 publications

Genetic Algorithm-Based Fuzzy Inference System for Describing Execution Tracing Quality

Genetic Algorithm-Based Fuzzy Inference System for Describing Execution Tracing Quality

Modelling Execution Tracing Quality by Means of Type-1 Fuzzy Logic

Development metrics measurement level for component reusability evaluation approach (CREA)

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