Software engineering activities in the Industry has come a long way with various improvements brought in various stages of the software development life cycle. The complexity of modern software, the commercial constraints and the expectation for high quality products demand the accurate fault prediction based on OO design metrics in the class level in the early stages of software development. The object oriented class metrics are used as quality predictors in the entire OO software development life cycle even when a highly iterative, incremental model or agile software process is employed. Recent research has shown some of the OO design metrics are useful for predicting fault-proneness of classes. In this paper the empirical validation of a set of metrics proposed by Chidamber and Kemerer is performed to assess their ability in predicting the software quality in terms of fault proneness and degradation. We have also proposed the design complexity of object-oriented software with Weighted Methods per Class metric (WMC-CK metric) expressed in terms of Shannon entropy, and error proneness.Property 1: Non-Coarseness Given a class P and a metric µ another class Q can always be found such that: µ(P )_µ(Q). This implies that not every class can have the same value for a metric; otherwise it has lost its value as a measurement.
Property 2: Non-uniqueness (notion of equivalence)There can exist distinct classes P and Q, µ(P ) = µ(Q). This implies that two classes can have the same metric value, i, e., the two classes are equally complex.
In this paper an effective estimation model is proposed for software reusability. The structural properties of the software are analyzed at design level with an engineering approach. This leads to the analysis of intricate relationship existing between the reusability and the design properties. An estimation model is created based on the empirical studies and weighted combination of polynomials using CK meas-ures.
Software engineering is continuously facing the challenges of growing complexity of software packages and increased level of data on defects and drawbacks from software production process. This makes a clarion call for inventions and methods which can enable a more reusable, reliable, easily maintainable and high quality software systems with deeper control on software generation process. Quality and productivity are indeed the two most important parameters for controlling any industrial process. Implementation of a successful control system requires some means of measurement. Software metrics play an important role in the management aspects of the software development process such as better planning, assessment of improvements, resource allocation and reduction of unpredictability. The process involving early detection of potential problems, productivity evaluation and evaluating external quality factors such as reusability, maintainability, defect proneness and complexity are of utmost importance. Here we discuss the application of CK metrics and estimation model to predict the external quality parameters for optimizing the design process and production process for desired levels of quality. Estimation of defect-proneness in object-oriented system at design level is developed using a novel methodology where models of relationship between CK metrics and defect-proneness index is achieved. A multifunctional estimation approach captures the correlation between CK metrics and defect proneness level of software modules.
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