A Regression Test Selection Technique for Graphical User Interfaces

Regression testing is a quality control measure to ensure that the newly modified part of the software still complies with its specified requirements and that the unmodified part has not been affected by the maintenance activity. Regression testing is an important and expensive activity during the software maintenance process and its purpose is to ensure quality and reliability in modified software. Regression testing selection techniques are focused on the reusability of existing test suites for a modified program from a previous version. Many regression testing selection techniques have been approached for conventional and object-oriented software. There is little discussion about those techniques to be applied for the Graphical User Interfaces (GUIs). This thesis addresses the gap. GUIs have characteristics different from traditional software, and the conventional testing techniques do not directly apply to GUIs. Unlike most previous techniques for selective retest, this thesis focuses on developing an event driven regression testing selection technique for GUIs. It defines an event dependence graph (EDG) to identify the interaction and relationship of the events within GUI components, develops an algorithm to construct the EDG for GUIs, and presents the GUI modeling structure and its selection retest technique. An algorithm is given to determine and generate a modified test suite automatically for GUI based on its original version. Experiments are presented on an implementation of this solution and discusses newly found challenges when applied to an established GUI application. Finally, feasibility and future areas of research are addressed on the findings during the implementation of the solution

Inconsistency of Bayesian Inference for Misspecified Linear Models, and a Proposal for Repairing It

We empirically show that Bayesian inference can be inconsistent under misspecification in simple linear regression problems, both in a model averaging/selection and in a Bayesian ridge regression setting. We use the standard linear model, which assumes homoskedasticity, whereas the data are heteroskedastic, and observe that the posterior puts its mass on ever more high-dimensional models as the sample size increases. To remedy the problem, we equip the likelihood in Bayes' theorem with an exponent called the learning rate, and we propose the Safe Bayesian method to learn the learning rate from the data. SafeBayes tends to select small learning rates as soon the standard posterior is not `cumulatively concentrated', and its results on our data are quite encouraging.Comment: 70 pages, 20 figure

Regression test selection model: a comparison between ReTSE and pythia

As software systems change and evolve over time regression tests have to be run to validate these changes. Regression testing is an expensive but essential activity in software maintenance. The purpose of this paper is to compare a new regression test selection model called ReTSE with Pythia. The ReTSE model uses decomposition slicing in order to identify the relevant regression tests. Decomposition slicing provides a technique that is capable of identifying the unchanged parts of a system. Pythia is a regression test selection technique based on textual differencing. Both techniques are compare using a Power program taken from Vokolos and Frankl’s paper. The analysis of this comparison has shown promising results in reducing the number of tests to be run after changes are introduced

Assuring the model evolution of protocol software specifications by regression testing process improvement

A preliminary version of this paper has been presented at the 10th International Conference on Quality Software (QSIC 2010).Model-based testing helps test engineers automate their testing tasks so that they are more cost-effective. When the model is changed because of the evolution of the specification, it is important to maintain the test suites up to date for regression testing. A complete regeneration of the whole test suite from the new model, although inefficient, is still frequently used in the industry, including Microsoft. To handle specification evolution effectively, we propose a test case reusability analysis technique to identify reusable test cases of the original test suite based on graph analysis. We also develop a test suite augmentation technique to generate new test cases to cover the change-related parts of the new model. The experiment on four large protocol document testing projects shows that our technique can successfully identify a high percentage of reusable test cases and generate low-redundancy new test cases. When compared with a complete regeneration of the whole test suite, our technique significantly reduces regression testing time while maintaining the stability of requirement coverage over the evolution of requirements specifications. Copyright © 2011 John Wiley & Sons, Ltd.link_to_subscribed_fulltex

Automating Regression Test Selection for Web Services

As Web services grow in maturity and use, so do the methods which are being used to test and maintain them. Regression Testing is a major component of most major testing systems but has only begun to be applied to Web services. The majority of the tools and techniques applying regression test to Web services are focused on test-case generation, thus ignoring the potential savings of regression test selection. Regression test selection optimizes the regression testing process by selecting a subset of all tests, while still maintaining some level of confidence about the system performing no worse than the unmodified system. A safe regression test selection technique implies that after selection, the level of confidence is as high as it would be if no tests were removed. Since safe regression test selection techniques generally involve code-based (white-box) testing, they cannot be directly applied to Web services due to their loosely-coupled, standards-based, and distributed nature. A framework which automates both the regression test selection and regression testing processes for Web services in a decentralized, end-to-end manner is proposed. As part of this approach, special consideration is given to the concurrency issues which may occur in an autonomous and decentralized system. The resulting synchronization method will be presented along with a set of algorithms which manage the regression testing and regression test selection processes throughout the system. A set of empirical results demonstrate the feasibility and benefit of the approach

Regression Test Selection by Exclusion

This thesis addresses the research in the area of regression testing. Software systems change and evolve over time. Each time a system is changed regression tests have to be run to validate these changes. An important issue in regression testing is how to minimise reuse the existing test cases of original program for modied program. One of the techniques to tackle this issue is called regression test selection technique. The aim of this research is to signicantly reduce the number of test cases that need to be run after changes have been made. Specically, this thesis focuses on developing a model for regression test selection using the decomposition slicing technique. Decomposition slicing provides a technique that is capable of identifying the unchanged parts of the system. The model of regression test selection based on decomposition slicing and exclusion of test cases was developed in this thesis. The model is called Regression Test Selection by Exclusion (ReTSE) and has four main phases. They are Program Analysis, Comparison, Exclusion and Optimisation phases. The validity of the ReTSE model is explored through the application of a number of case studies. The case studies tackle all types of modication such as change, delete and add statements. The case studies have covered a single and combination types of modication at a time. The application of the proposed model has shown that signicant reductions in the number of test cases can be achieved. The evaluation of the model based on an existing framework and comparison with another model also has shown promising results. The case studies have limited themselves to relatively small programs and the next step is to apply the model to larger systems with more complex changes to ascertain if it scales up. While some parts of the model have been automated tools will be required for the rest when carrying out the larger case studies

Program simplification as a means of approximating undecidable propositions

We describe an approach which mixes testing, slicing, transformation and formal verification to investigate speculative hypotheses concerning a program, formulated during program comprehension activity. Our philosophy is that such hypotheses (which are typically undecidable) can, in some sense, be `answered' by a partly automated system which returns neither `true' nor `false' but a program (the `test program') which computes the answer. The motivation for this philosophy is the way in which, as we demonstrate, static analysis and manipulation technology can be applied to ensure that the resulting test program is significantly simpler than the original program, thereby simplifying the process of investigating the original hypothesi

An integrated search-based approach for automatic testing from extended finite state machine (EFSM) models

This is the post-print version of the Article - Copyright @ 2011 ElsevierThe extended finite state machine (EFSM) is a modelling approach that has been used to represent a wide range of systems. When testing from an EFSM, it is normal to use a test criterion such as transition coverage. Such test criteria are often expressed in terms of transition paths (TPs) through an EFSM. Despite the popularity of EFSMs, testing from an EFSM is difficult for two main reasons: path feasibility and path input sequence generation. The path feasibility problem concerns generating paths that are feasible whereas the path input sequence generation problem is to find an input sequence that can traverse a feasible path. While search-based approaches have been used in test automation, there has been relatively little work that uses them when testing from an EFSM. In this paper, we propose an integrated search-based approach to automate testing from an EFSM. The approach has two phases, the aim of the first phase being to produce a feasible TP (FTP) while the second phase searches for an input sequence to trigger this TP. The first phase uses a Genetic Algorithm whose fitness function is a TP feasibility metric based on dataflow dependence. The second phase uses a Genetic Algorithm whose fitness function is based on a combination of a branch distance function and approach level. Experimental results using five EFSMs found the first phase to be effective in generating FTPs with a success rate of approximately 96.6%. Furthermore, the proposed input sequence generator could trigger all the generated feasible TPs (success rate = 100%). The results derived from the experiment demonstrate that the proposed approach is effective in automating testing from an EFSM

Safe Concurrency Introduction through Slicing

Traditional refactoring is about modifying the structure of existing code without changing its behaviour, but with the aim of making code easier to understand, modify, or reuse. In this paper, we introduce three novel refactorings for retrofitting concurrency to Erlang applications, and demonstrate how the use of program slicing makes the automation of these refactorings possible