Testability is an important software quality factor that is ineffective if it is not available at an early stage in the development life-cycle. It becomes more essential in the case of object oriented design. Flexibility is an important key factor to testability analysis and measurement for delivering high class testable and maintainable software. Flexibility is a criterion of crucial significance to software developers, designers and the quality controllers. It constantly guides and supports to avoid wastage of resources as well as enable the designers for continuous improvement in the development process. Flexibility is concerned with building high quality and reliable software within the constraints of cost and time. It greatly influences cost, quality and reliability at software evolution process. Despite the fact flexibility is vital and highly significant aspect for software development processes, it is poorly managed. This paper focuses the need and importance of flexibility early at design phase. A model has been proposed for flexibility measurement of object oriented design by establishing multiple linear regression. Finally the proposed model has been validated using experimental tryout.

Measuring testability early in the development life cycle especially at design phase is a criterion of crucial

Changeability has a direct relation to software maintainability and has a major role in providing high quality maintainable and trustworthy software. In this paper a correlation between the major attributes of object oriented design and changeability has been ascertained. A changeability evaluation model using multiple linear regression has been proposed for object oriented design. The validation of the proposed changeability evaluation model is made known by means of experimental tests and the results show that the model is highly significant.

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Measuring testability early in the development life cycle considerably reduces the overall development cost, effort and rework. It is very expensive and error prone decision to correct the design to get better testability after the coding has started. This paper proposes a testability measurement framework for object oriented software concerning at design phase. This framework correlates the testability factor with object oriented design properties and also correlates design properties with object oriented design metrics. No such framework has been presented in the literature that accurately measure testability of object oriented software taking design phase into consideration. The proposed framework reduces the gap between object oriented design properties, metrics and testability. This framework measures effort in measuring testability of object oriented software early at design phase and makes it possible to produce reliable end product within time and budget.

In a relational database, classification algorithms are used to look for patterns across several interconnected relations. Most of the methods for multi-relational classification algorithms implicitly assume that the classes in the target relation are equally represented. Thus, they tend to produce poor predictive performance over the imbalanced dataset. In this paper, the authors propose an algorithm-level method MCMRC_IB for the classification of imbalanced multi-relational dataset. The proposed method extends MCMRC which is for balanced datasets. MCMRC_IB exploits the property of the imbalanced datasets that the minority class is represented by a smaller number of records usually 20-30% of the total records and is to be dealt accordingly by giving them weightages. The proposed method is able to handle multiple classes. Experimental results conðrm the efficiency of the proposed method in terms of predictive accuracy, F-measure, and G-mean.

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