The main reason behind failure of lots of software is poor quality thus estimation software quality become an important task in software industry. An early estimation towards pre-released software quality plays an important role in increasing probability of project success. By analyzing the metric data we can forecast the quality of the object oriented system. Software metrics are necessary to identify where the resources are needed; they are a crucial source of information for decision making. This paper represents proposed model for estimation quality of software product.

A hierarchical model for object-oriented design quality assessment

The exponential rise in software technologies and its significances has demanded academia-industries to ensure low cost software solution with assured service quality and reliability. A low cost and fault-resilient software design is must, where to achieve low cost design the developers or programmers prefer exploiting source or function reuse. However, excessive reusability makes software vulnerable to get faulty due to increased complexity and aging proneness. Non-deniably assessing reusability of a class of function in software can enable avoiding any unexpected fault or failure. To achieve it developing a robust and efficient reusability estimation or prediction model is of utmost significance. On the other hand, the aftermath consequences of excess reusability caused faults might lead significant losses. Hence assessing cost effectiveness and efficacy of a reusability prediction model is must for software design optimization. In this paper, we have examined different reusability prediction models for their cost effectiveness and prediction efficiency over object-oriented software design. At first to examine the reusability of a class, three key object oriented software metrics (OO-SM); cohesion, coupling and complexity of the software components are used. Furthermore, our proposed cost-efficient reusability prediction model incorporates Min–Max normalization, outlier detection, reusability threshold estimation; T test analysis based feature selection and various classification algorithms. Different classifiers including decision tree (DT), Naive Bayes (NB), artificial neural network (ANN) algorithms, extreme learning machine (ELM), regression algorithms, multivariate adaptive regression spline (MARS) and adaptive genetic algorithm (AGA) based ANN are used for reusability prediction. Additionally, the cost effectiveness of each reusability prediction model is estimated, where the overall results have revealed that AGA based ANN as classifier in conjunction with OO-SM, normalization, T test analysis based feature selection outperforms other state-of-art techniques in terms of both accuracy as well as cost-effectiveness.

Cost-effective and fault-resilient reusability prediction model by using adaptive genetic algorithm based neural network for web-of-service applications

Ensuring the aging resilient software design can be of paramount significance to enable faultless software system. Particularly assessing reusability extent of the software components can enable efficient software design. The probability of aging proneness can be characterized based on key OO-SM like cohesion, coupling and complexity of a software component. In this paper, aging resilient software reusability prediction model is proposed for object oriented design based Web of Service (WoS) software systems. This work introduces multilevel optimization to accomplish a novel reusability prediction model. Considering coupling, cohesion and complexity as the software characteristics to signify aging proneness, six CK metrics; WMC, CBO, DIT, LCOM, NOC, and RFC are obtained from 100 WoS software. The extracted CK metrics are processed for min–max normalization that alleviates data-unbalancing and hence avoids saturation during learning. The 10-fold Cross-validation followed by outlier detection is considered to enrich data quality for further feature extraction. To reduce computational overheads RSA algorithm is applied. SoftAudit tool is applied to estimate reusability of each class, while binary ULR estimates calculates (reuse proneness) threshold. Applying different classification algorithms such as LM, ANN algorithms, ELM, and evolutionary computing enriched ANN reuse-proneness prediction has been done. The performance assessment affirms that AGA based ANN model outperforms other techniques and hence can be used for earlier aging-resilient reusability optimization for WoS software design.

Enhanced evolutionary computing based artificial intelligence model for web-solutions software reusability estimation

A Model-Driven approach for functional test case generation

The quality factor of class diagram is critical because it has a significant influence on overall quality of the product, delivered finally. Testability analysis, when done early in the software creation process, is a criterion of critical importance to software quality. Reusability is an important quality factor to testability. Its early measurement in object oriented software especially at design phase, allows a design to be reapplied to a new problem without much extra effort. This research paper proposes a research framework for quantification process and does an extensive review on reusability of object oriented software. A metrics based model “Reusability Quantification of Object Oriented Design” has been proposed by establishing the relationship among design properties and reusability and justifying the correlation with the help of statistical measures. Also, “Reusability Quantification Model” is empirically validated and contextual significance of the study shows the high correlation for model acceptance. This research paper facilitates to software developers and designer, the inclusion of reusability quantification model to access and quantify software reusability for quality product.

https://file.scirp.org/pdf/JSEA_2015041418363656.pdf

Quantifying Reusability of Object Oriented Design: A Testability Perspective

The quality of any object oriented design is critical because it has a great influence on overall quality of finally delivered software product. Testability quantification early in the software development process is a criterion of crucial important to software development team. Testability has always been an indefinable concept its correct measurement, quantification or evaluation is a difficult task because of its potential factors. Testability analysis of object oriented software at an initial stage of software development process has been identified as a key factor for high quality product. A best suited object oriented design (OOD) properties and its associated metrics are helpful if applied in the early stage of development process .This paper describes an improved testability quantification framework using the identified set of potential factors, OOD properties and OOD metrics for software products at early phase, exclusively at design time. The proposed framework relates OOD properties to high level quality attributes/constructs using appropriate information to develop quality product and it may used to benchmark software products according to their key attribute. The objective of this research work to encourage researchers and developers to provide a framework to access and quantify software testability at early stage of development life cycle.

/pdf/testability-quantification-framework-of-object-oriented-2rw2q3vzme.pdf

Testability Quantification Framework of Object Oriented Software: A New Perspective

Effectiveness is important quality factor to testability measurement of object oriented software at an initial stage of software development process exclusively at design phase for high quality product. It will help developer’s design capability to achieve the specified functionalities, characteristics, better design quality and behavior using appropriate object oriented design (OOD) concepts and procedures. Metric based model for ‘Effectiveness Quantification Model of Object Oriented Design’ has been proposed by establishing the correlation between effectiveness and OOD constructs. Later ‘Effectiveness Quantification Model’ is empirically validated and statistical significance of the study considers the high correlation for model acceptance. The aim of this research work is to encourage researchers and developers for inclusion of the effectiveness quantification model to access and quantify software effectiveness quality factor at design time.

/pdf/evaluating-effectiveness-factor-of-object-oriented-design-a-3so2nsud2x.pdf

Evaluating effectiveness factor of object oriented design : a testability perspective

The quality factor of class diagram is critical because it has significant influence on overall quality of the product, delivered finally. Testability has been recognized as a key factor to software quality. Estimating testability at design stage is a criterion of crucial significance for software designers to make the design more testable. Taking view of this fact, this paper identifies testability factors namely effectiveness and reusability and establishes the correlation among testability, effectiveness and reusability and justifies the correlation with the help of statistical measures. Moreover study developed metric based testability estimation model and developed model has been validated using experimental test. Subsequently, research integrates the empirical validation of the developed model for high level acceptance. Finally a hypothesis test performs by the two standards to test the significance of correlation.

/pdf/metric-based-testability-estimation-model-for-object-21lcbcxge8.pdf

Yagya Dutt Sharma Arya

Papers

Quantifying Reusability of Object Oriented Design: A Testability Perspective

Testability Quantification Framework of Object Oriented Software: A New Perspective

Evaluating effectiveness factor of object oriented design : a testability perspective

Metric Based Testability Estimation Model for Object Oriented Design: Quality Perspective