Impact of Aspect Oriented Programming on Software Development Quality Metrics

The aspect-oriented programming (AOP) is a new paradigm for improving the system’s features such as modularity, readability and maintainability. Owing to a better modularisation of cross-cutting concerns, the developed system implementation would be less complex, and more readable.Thus, software development efficiency would increase, so the system would be created faster than its object-oriented programming (OOP) equivalent. In this paper, we provide some insight into the OO software development quality metrics were significantly associated with using AOP.The method that we are currently studying is based on a popular C & K metrics suite that extends the metrics traditionally used with the OO paradigm and also extend to AO paradigm. We argue that a shift similar to the one leading to the Chidamber and Kemerer’s metrics is necessary when moving from OO to AOP software

An Approach for the Empirical Validation of Software Complexity Measures

Software metrics are widely accepted tools to control and assure software quality. A large number of software metrics with a variety of content can be found in the literature; however most of them are not adopted in industry as they are seen as irrelevant to needs, as they are unsupported, and the major reason behind this is due to improper empirical validation. This paper tries to identify possible root causes for the improper empirical validation of the software metrics. A practical model for the empirical validation of software metrics is proposed along with root causes. The model is validated by applying it to recently proposed and well known metrics

Evaluation Criteria for Object-oriented Metrics

In this paper an evaluation model for object-oriented (OO) metrics is proposed. We have evaluated the existing evaluation criteria for OO metrics, and based on the observations, a model is proposed which tries to cover most of the features for the evaluation of OO metrics. The model is validated by applying it to existing OO metrics. In contrast to the other existing criteria, the proposed model is simple in implementation and includes the practical and important aspects of evaluation; hence it suitable to evaluate and validate any OO complexity metric

Crosscutting, what is and what is not? A Formal definition based on a Crosscutting Pattern

Crosscutting is usually described in terms of scattering and tangling. However, the distinction between these concepts is vague, which could lead to ambiguous statements. Sometimes, precise definitions are required, e.g. for the formal identification of crosscutting concerns. We propose a conceptual framework for formalizing these concepts based on a crosscutting pattern that shows the mapping between elements at two levels, e.g. concerns and representations of concerns. The definitions of the concepts are formalized in terms of linear algebra, and visualized with matrices and matrix operations. In this way, crosscutting can be clearly distinguished from scattering and tangling. Using linear algebra, we demonstrate that our definition generalizes other definitions of crosscutting as described by Masuhara & Kiczales [21] and Tonella and Ceccato [28]. The framework can be applied across several refinement levels assuring traceability of crosscutting concerns. Usability of the framework is illustrated by means of applying it to several areas such as change impact analysis, identification of crosscutting at early phases of software development and in the area of model driven software development

An empirical investigation of an object-oriented software system

This is the post print version of the article. The official published version can be obtained from the link below.This paper describes an empirical investigation into an industrial object-oriented (OO) system comprised of 133,000 lines of C++. The system was a subsystem of a telecommunications product and was developed using the Shlaer-Mellor method. From this study, we found that there was little use of OO constructs such as inheritance and, therefore, polymorphism. It was also found that there was a significant difference in the defect densities between those classes that participated in inheritance structures and those that did not, with the former being approximately three times more defect-prone. We were able to construct useful prediction systems for size and number of defects based upon simple counts such as the number of states and events per class. Although these prediction systems are only likely to have local significance, there is a more general principle that software developers can consider building their own local prediction systems. Moreover, we believe this is possible, even in the absence of the suites of metrics that have been advocated by researchers into OO technology. As a consequence, measurement technology may be accessible to a wider group of potential users