Understanding Class-level Testability Through Dynamic Analysis

It is generally acknowledged that software testing is both challenging and time-consuming. Understanding the factors that may positively or negatively affect testing effort will point to possibilities for reducing this effort. Consequently there is a significant body of research that has investigated relationships between static code properties and testability. The work reported in this paper complements this body of research by providing an empirical evaluation of the degree of association between runtime properties and class-level testability in object-oriented (OO) systems. The motivation for the use of dynamic code properties comes from the success of such metrics in providing a more complete insight into the multiple dimensions of software quality. In particular, we investigate the potential relationships between the runtime characteristics of production code, represented by Dynamic Coupling and Key Classes, and internal class-level testability. Testability of a class is consider ed here at the level of unit tests and two different measures are used to characterise those unit tests. The selected measures relate to test scope and structure: one is intended to measure the unit test size, represented by test lines of code, and the other is designed to reflect the intended design, represented by the number of test cases. In this research we found that Dynamic Coupling and Key Classes have significant correlations with class-level testability measures. We therefore suggest that these properties could be used as indicators of class-level testability. These results enhance our current knowledge and should help researchers in the area to build on previous results regarding factors believed to be related to testability and testing. Our results should also benefit practitioners in future class testability planning and maintenance activities

Identification & Analysis of Parameters for Program Quality Improvement: A Reengineering Perspective

The nature of software development is very dynamic and more complex by the perspective of reengineering or further program maintenances so the developed programs must be flexible, reusable and more scalable and which will be possible by the optimum quality parameters satisfaction. Having these issues in concern the software development houses trying to find out some established, usable methods to improve the quality of programs, the work presented in this paper is to identify, describe and analyze various parameters for quality which can affect the productivity and reusability of the software program and its future maintenance in form of reengineering. The work presented also analyzes the literature, previous research with different aspects and issues, and discussed its affects on present quality of the program because it is necessary to consider the potential impact on other requirements when designing a program to meet quality parameters requirements. Quality parameters are the overall factors that affect run-time behavior, system design, and user experience because many of these parameters are major concern to the program design and architecture, and also applied to establish  program functionality, reusability, performance, reliability, and security which indicates the success of the design and the overall quality of the program and its application, integration. Keywords: AOSD, DoD, FURPS,LOC,Parameters

Categorizing Non-Functional Requirements Using a Hierarchy in UML.

Non-functional requirements (NFRs) are a subset of requirements, the means by which software system developers and clients communicate about the functionality of the system to be built. This paper has three main parts: first, an overview of how non-functional requirements relate to software engineering is given, along with a survey of NFRs in the software engineering literature. Second, a collection of 161 NFRs is diagrammed using the Unified Modelling Language, forming a tool with which developers may more easily identify and write additional NFRs. Third, a lesson plan is presented, a learning module intended for an undergraduate software engineering curriculum. The results of presenting this learning module to a class in Spring, 2003 is presented

Survey of source code metrics for evaluating testability of object oriented systems

Software testing is costly in terms of time and funds. Testability is a software characteristic that aims at producing systems easy to test. Several metrics have been proposed to identify the testability weaknesses. But it is sometimes difficult to be convinced that those metrics are really related with testability. This article is a critical survey of the source-code based metrics proposed in the literature for object-oriented software testability. It underlines the necessity to provide testability metrics that are proved to be intuitive and adequate for the testing cost prediction

The effectiveness of refactoring, based on a compatibility testing taxonomy and a dependency graph

In this paper, we describe and then appraise a testing taxonomy proposed by van Deursen and Moonen (VD&M) based on the post-refactoring repeatability of tests. Four categories of refactoring are identified by VD&M ranging from semantic-preserving to incompatible, where, for the former, no new tests are required and for the latter, a completely new test set has to be developed. In our appraisal of the taxonomy, we heavily stress the need for the inter-dependence of the refactoring categories to be considered when making refactoring decisions and we base that need on a refactoring dependency graph developed as part of the research. We demonstrate that while incompatible refactorings may be harmful and time-consuming from a testing perspective, semantic-preserving refactorings can have equally unpleasant hidden ramifications despite their advantages. In fact, refactorings which fall into neither category have the most interesting properties. We support our results with empirical refactoring data drawn from seven Java open-source systems (OSS) and from the same analysis form a tentative categorization of code smells

Design of Quality Model during Reengineering of Legacy System

The purpose of this paper is design such kind of model that will improve the quality of system during reengineering[1] of legacy system that why this model is known as Quality Model. During reengineering of object oriented system[2,3], the methodology is design in such a way that will create a link/bridge between problem detection and problem correction in the legacy system, as well as simultaneously improvement in object oriented design, that can be used during later reengineering and also reduces the complexity as compared to object oriented design[4,5,6]. The further design of legacy system in such a way to specifying, how branches can be selected, how behavior is preserved and how code transformation applied. Quality of model, depends upon two factor favor and disfavor, attach to each branches, software quality is directly proportional to maintenance cost. Quality model is used for two purpose sketch and blueprint. Sketch is used a thinking tool, which help developer communicates, some aspects of a system and alternative about, what are about to be done. Blueprint intends to be comprehensive and definitive. It is used for guiding the implementation

On the Impact of Refactoring on the Relationship between Quality Attributes and Design Metrics

Refactoring is a critical task in software maintenance and is generally performed to enforce the best design and implementation practices or to cope with design defects. Several studies attempted to detect refactoring activities through mining software repositories allowing to collect, analyze and get actionable data-driven insights about refactoring practices within software projects. Aim: We aim at identifying, among the various quality models presented in the literature, the ones that are more in-line with the developer’s vision of quality optimization, when they explicitly mention that they are refactoring to improve them. Method: We extract a large corpus of design-related refactoring activities that are applied and documented by developers during their daily changes from 3,795 curated open source Java projects. In particular, we extract a large-scale corpus of structural metrics and anti-pattern enhancement changes, from which we identify 1,245 quality improvement commits with their corresponding refactoring operations, as perceived by software engineers. Thereafter, we empirically analyze the impact of these refactoring operations on a set of common state-of-the-art design quality metrics. Results: The statistical analysis of the obtained results shows that (i) a few state-of-the-art metrics are more popular than others; and (ii) some metrics are being more emphasized than others. Conclusions: We verify that there are a variety of structural metrics that can represent the internal quality attributes with different degrees of improvement and degradation of software quality. Most of the metrics that are mapped to the main quality attributes do capture developer intentions of quality improvement reported in the commit messages, but for some quality attributes, they don’t