Towards a Regression Test Selection Technique for Message-Based Software Integration

Regression testing is essential to ensure software quality. Regression Test-case selection is another process wherein, the testers would like to ensure that test-cases which are obsolete due to the changes in the system should not be considered for further testing. This is the Regression Test-case Selection problem. Although existing research has addressed many related problems, most of the existing regression test-case selection techniques cater to procedural systems. Being academic, they lack the scalability and detail to cater to multi-tier applications. Such techniques can be employed for procedural systems, usually mathematical applications. Enterprise applications have become complex and distributed leading to component-based architectures. Thus, inter-process communication has become a very important activity of any such system. Messaging is the most widely employed intermodule interaction mechanism. Today\u27s systems, being heavily internet dependent, are Web-Services based which utilize XML for messaging. We propose an RTS technique which is specifically targeted at enterprise applications

Towards a Regression Test Selection Technique for Message-Based Software Integration

Regression testing is essential to ensure software quality. Regression Test-case selection is another process wherein, the testers would like to ensure that test-cases which are obsolete due to the changes in the system should not be considered for further testing. This is the Regression Test-case Selection problem. Although existing research has addressed many related problems, most of the existing regression test-case selection techniques cater to procedural systems. Being academic, they lack the scalability and detail to cater to multi-tier applications. Such techniques can be employed for procedural systems, usually mathematical applications. Enterprise applications have become complex and distributed leading to component-based architectures. Thus, inter-process communication has become a very important activity of any such system. Messaging is the most widely employed intermodule interaction mechanism. Today\u27s systems, being heavily internet dependent, are Web-Services based which utilize XML for messaging. We propose an RTS technique which is specifically targeted at enterprise applications

Automated Regression Testing Approach To Expansion And Refinement Of Speech Recognition Grammars

This thesis describes an approach to automated regression testing for speech recognition grammars. A prototype Audio Regression Tester called ART has been developed using Microsoft\u27s Speech API and C#. ART allows a user to perform any of three tasks: automatically generate a new XML-based grammar file from standardized SQL database entries, record and cross-reference audio files for use by an underlying speech recognition engine, and perform regression tests with the aid of an oracle grammar. ART takes as input a wave sound file containing speech and a newly created XML grammar file. It then simultaneously executes two tests: one with the wave file and the new grammar file and the other with the wave file and the oracle grammar. The comparison result of the tests is used to determine whether the test was successful or not. This allows rapid exhaustive evaluations of additions to grammar files to guarantee forward process as the complexity of the voice domain grows. The data used in this research to derive results were taken from the LifeLike project. However, the capabilities of ART extend beyond LifeLike. The results gathered have shown that using a person\u27s recorded voice to do regression testing is as effective as having the person do live testing. A cost-benefit analysis, using two published equations, one for Cost and the other for Benefit, was also performed to determine if automated regression testing is really more effective than manual testing. Cost captures the salaries of the engineers who perform regression testing tasks and Benefit captures revenue gains or losses related to changes in product release time. ART had a higher benefit of $21461.08 when compared to manual regression testing which had a benefit of$21393.99. Coupled with its excellent error detection rates, ART has proven to be very efficient and cost-effective in speech grammar creation and refinement

Regression test selection for distributed Java RMI programs by means of formal concept analysis

Software maintenance is the process of modifying an existing system to ensure that it meets current and future requirements. As a result, performing regression testing becomes an essential but time consuming aspect of any maintenance activity. Regression testing is initiated after a programmer has made changes to a program that may have inadvertently introduced errors. It is a quality control approach to ensure that the newly modified code still complies with its specified requirements and that unmodified code has not been affected by the maintenance activity. In the literature various types of test selection techniques have been proposed to reduce the effort associated with re-executing the required test cases. However, the majority of these approach has been focusing only on sequential programs, and provide no or only very limited support for distributed programs or database-driven applications. The thesis presents a lightweight methodology, which applies Formal Concept Analysis to support a regression test selection analysis, in combination with execution trace collection and external data sharing analysis, for distributed Java RMI programs. Two Eclipse plug-ins were developed to automate the regression test selection process and to evaluate our methodology

A Methodology to Support the Maintenance of Object -Oriented Systems Using Impact Analysis.

Object-Oriented (OO) systems are difficult to understand due to the complex nature of the relationships that object-orientation supports. Inheritance, polymorphism, encapsulation, information hiding, aggregation, and association combine to make maintenance of OO systems difficult. Due to the presence of these characteristics in OO systems, maintenance activities on OO systems often have unexpected or unseen effects on the system. These effects can ripple through system components, complicating maintenance and testing of the system. The ability to trace the effects of maintenance provides the maintainer with knowledge that assists in debugging and testing modified and affected components. In this research, we show that the architecture of an OO system provides an effective framework for determining the impact of system changes. We developed the Comparative Software Maintenance (CSM) methodology to support the maintenance of OO systems. Through this methodology, we model relationships and structures, analyze the models to determine components that change as a result of maintenance, and perform impact analysis to determine components that are candidates for re-testing as a result of maintenance activity. The methodology includes a new data model, called Extended Low-Level Software Architecture (ELLSA), that facilitates impact analysis. CSM locates potential side effects, ripple effects, and other effects of maintenance on class structures, methods, and objects. The comprehensive architecture model enables CSM to perform either predictive, pre-modification impact analysis or post-modification impact analysis. The improved impact analysis process found in the methodology determines impact of changes to the component level. We apply the results of impact analysis to determine component level testing requirements. CSM enhances program understanding through the use of ELLSA. It also provides assistance for capturing complex dependencies found in object-oriented code. The methodology is implemented in JFlex. The automation provided by JFlex makes the application of CSM feasible

Developing Cost-Effective Model-Based Techniques for GUI Testing

Most of today's software users interact with the software through a graphical user interface (GUI), which constitutes as much as 45-60% of the total code. The correctness of the GUI is necessary to ensure the correctness of the overall software. Although GUIs have become ubiquitous, testing GUIs for functional correctness has remained a neglected research area. Existing GUI testing techniques are extremely resource intensive primarily because GUIs have very large input spaces and evolve frequently. This dissertation overcomes the limitations of existing techniques by developing a process with supporting models, techniques, and tools for continuous integration testing of evolving GUI-based applications. The key idea of this process is to create three concentric testing loops, each with specific GUI testing goals, resource usage, and targeted feedback. The innermost fully automatic loop called crash testing operates on each code change of the GUI software. The second semi-automated loop called smoke testing operates on each day's GUI build. The outermost loop called comprehensive GUI testing is executed after a major version of the GUI is available. The primary enablers of this process, also developed in this dissertation, include an abstract model of the GUI and a set of model-based techniques for test-case generation, test oracle creation, and continuous GUI testing. The model and techniques were obtained by studying GUI faults, interactions between GUI events, and why certain event interactions lead to faults. The continuous testing process and associated techniques are shown to be useful, via several large experiments involving millions of test cases, on both in-house and open-source GUI applications

Exploring regression testing and software product line testing - research and state of practice

In large software organizations with a product line development approach a selective testing of product variants is necessary in order to keep pace with the decreased development time for new products, enabled by the systematic reuse. The close relationship between products in product line indicates an option to reduce the testing effort due to redundancy. In many cases test selection is performed manually, based on test leaders’ expertise. This makes the cost and quality of the testing highly dependent on the skills and experience of the test leaders. There is a need in industry for systematic approaches to test selection. The goal of our research is to improve the control of the testing and reduce the amount of redundant testing in the product line context by applying regression test selection strategies. In this thesis, the state of art of regression testing and software product line testing are explored. Two extensive systematic reviews are conducted as well as an industrial survey of regression testing state of practice and an industrial evaluation of a pragmatic regression test selection strategy. Regression testing is not an isolated one-off activity, but rather an activity of varying scope and preconditions, strongly dependent on the context in which it is applied. Several techniques for regression test selection are proposed and evaluated empirically but in many cases the context is too specific for a technique to be easily applied directly by software developers. In order to improve the possibility for generalizing empirical results on regression test selection, guidelines for reporting the testing context are discussed in this thesis. Software product line testing is a relatively new research area. The understanding about challenges is well established but when looking for solutions to these challenges, we mostly find proposals, and empirical evaluations are sparse. Regression test selection strategies proposed in literature are not easily applicable in the product line context. Instead, control may be increased by increased visibility of the effects of testing and proper measurements of software quality. Focus of our future work will be on how to guide the planning and assessment of regression testing activities in large, complex reuse based systems, by visualizing the quality achieved in different parts of the system and evaluating the effects of different selection strategies when applied in various regression testing situations