International Journal of Computer Applications (0975 8887) Volume 61No.2, January 2013 34 Validation of Software Architectural Tool for Object-Orinted Testing using with the Facilitate Quality Attributes Lalji Prasad Truba College of Engineering and Technology, Department of Computer science and Engineering (RGTU), Indore, INDIA Sarita Singh Bhadauria Madhav Institute of Technology and Science, Department of Electronics Engineering (RGTU), Gwalior, INDIA ABSTRACT In this research investigate, quality of software using comprehend our architecture testing model [34], with the help of object oriented characteristic relationship, using different software metrics. The objective of ‘Design Architectural Testing Tool’ is to facilitate a design that may contribute to the comprehensiveness of the software testing tool. In this research work first we try to draw an architecture of testing method based on their attribute nature and shows their relationship next phase will be applied testing (based on different software metrics) on each component and after testing we apply different statistical analysis for validation of our research work . General Terms Software Testing, Software Architecture. Keywords Comprehensiveness, Architectural Completeness, Architectural Quality Attribute, Architectural Metrics 1. INTRODUCTION Different researcher work on quality of software architecture and testing for ensuring the quality of software, here discuss only prominence few literature. Bass and et al. , articulated importance of software architecture [12] .Soni and et al. Say , Software architectures describe how a system is decomposed into components, how these components are interconnected, and how they communicate and interact with each other’s” [14]. Perry and et al. Work on Software architecture is concerned with the study of the structure of software, including its topology, properties, constituent components and their relationships and patterns of combination [21]. Gary Chastek and et al., enlighten software architectural attributes and quality- related [1]. Huang and et al., describe the basic rules for program testing, which provide basic principle for testing [3,10,14,15,16,17]. Poston [26], Williams [27], and Hareton [19] shows, Integration all the data across tools and repositories, Integration of control across the tools and Integration to provide a single graphical interface into the test tool set. Limitation: emphasize only integration tool (usability & portability). Rosenberg [4] provides, the approach to software metric for object oriented based different from the standard metric sets. Some metrics, such as, line of code & cyclomatic complexity, have become accepted as standard for traditional functional / procedural programs, but for an object oriented scenario, there are many proposed object oriented metrics in the literature. Limitation: this provides the only conceptual framework for measurement .Agrawal and et al. [25] cited in this paper the importance of software measurement is increasing leading to the development of new measurement techniques. Limitation: a) It does not provide any relationship between requirement & testing attribute. b) It cannot evaluate for large data sets. Anderson and et al. [5] Emphasized the software industry has performed a significant amount of research on improving software quality using software tools & metrics will improve the software quality and reduce the overall development time. Good quality code will also be easier to write, understand, maintain and upgrade. Limitation a) it does not provide any relationship between the required testing attribute. b) Its not provide a full featured testing tool (only Complexity & cohesion measure). c) It provides the only conceptual framework for measurement. Briand and some other researchers [9,11,28,29,30,31] demonstrate aims is that empirically the relationships between most of the existing coupling & Cohesion measures for object oriented (OO) system & fault proneness of object oriented system classes can be studied. Limitation: a) Only emphasis on cohesion & coupling metric. Bitman [6] exhibit key problem in software development of changing software- development complexity and the method to reduce complexity. Limitation: a) It does provide only complexity measurement techniques. Krauskopf &Juan [32] and Harrison [8] demonstrate, Coupling is the degree of interdependence between two modules. In a good design, they are kept low. Coupling should be lower in large and complex system. No coupling is highly is desirable but practically it is not possible. The good & bad points of different types of coupling are discussed. Limitation: a) Only emphasis on cohesion & coupling metrics. Chidambaram [8] and Harrison [7] emphasized the coupling between object (CBO) metric and evaluated for five object oriented systems & compared with alternative design metric called NAS which measure the number of associations between class & its peers (Harrison R.S). NAS metric is directly collectible from design documents such as the object model. Limitation: a) it’s not providing any relationship between requirement & testing attribute. b) They don't provide some basic idea for size & effort estimation. c) Measuring complexity of a class is subject to bias. Reiner R., Dumke and Achim S., Show How to manage component based software and identify related metrics. [18] Comprehensive means that it includes all or nearly all features (maintainability, reusability, flexibility and portability) and relationships required for migrating from one testing class to another. It is designed to overcome the limitation of existing software tools by providing a final class level architecture having relationships between various testing classes. Software quality is another focus of our architecture. We wish to achieve good maintainability, reusability, flexibility and portability in the architecture of the software testing tool by validating the architecture using testing algorithms and performing metrics calculation on each relationship existing between the different testing techniques [1, 2, 3].