Cause reduction for quick testing

pre-printAbstract-In random testing, it is often desirable to produce a "quick test" - an extremely inexpensive test suite that can serve as a frequently applied regression and allow the benefits of random testing to be obtained even in very slow or oversubscribed test environments. Delta debugging is an algorithm that, given a failing test case, produces a smaller test case that also fails, and typically executes much more quickly. Delta debugging of random tests can produce effective regression suites for previously detected faults, but such suites often have little power for detecting new faults, and in some cases provide poor code coverage. This paper proposes extending delta debugging by simplifying tests with respect to code coverage, an instance of a generalization of delta debugging we call cause reduction. We show that test suites reduced in this fashion can provide very effective quick tests for real-world programs. For Mozilla's SpiderMonkey JavaScript engine, the reduced suite is more effective for finding software faults, even if its reduced runtime is not considered. The effectiveness of a reduction-based quick test persists through major changes to the software under test

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

Aplicación del modelo mgrsoft en la reutilización de revisiones a requsitos de software

En este trabajo se presentan las experiencias de la implementación de un Modelo para la Gestión de Revisiones (MGRSoft), haciendo énfasis en la utilización de mecanismos de reuti-lización para las revisiones de los requisitos a nuevos proyectos de software. Se exponen las características de una herramienta que reutiliza revisiones anteriores y su utilización dentro del modelo MGRSoft. Se presentan, además, los resultados obtenidos en una prueba rea-lizada a proyectos reales, que evidencia el aprovechamiento de la experiencia acumulada utilizando los mecanismos de reutilización incluidos en el modelo.This paper presents the implementation experiences of the Manage Revisions Model (MGR-Soft), making emphasis in the use of reutilization mechanisms for revisions to requirements in new software projects. It includes the characteristics of a tool that reuse previous revisions and its use inside the MGRSoft model. The results of the results of a test on real projects, which demonstrates the use of experience using the reuse mechanisms included in the mo-del

Recovering fitness gradients for interprocedural Boolean flags in search-based testing

National Research Foundation (NRF) Singapore under Corp Lab @ University scheme; National Research Foundation (NRF) Singapore under its NSoE Programm

Enabling real-time feedback in software engineering

Modern software projects consist of more than just code: Teams follow development processes, the code runs on servers or mobile phones and produces run time logs and users talk about the software in forums like StackOverflow and Twitter and rate it on app stores. Insights stemming from the real-time analysis of combined software engineering data can help software practitioners to conduct faster decision-making. With the development of CodeFeedr, a Real-time Software Analytics Platform , we aim to make software analytics a core feedback loop for software engineering projects. CodeFeedr's vision entails: (1) The ability to unify archival and current software analytics data under a single query language, and (2) The feasibility to apply new techniques and methods for high-level aggregation and summarization of near real-time information on software development. In this paper, we outline three use cases where our platform is expected to have a significant impact on the quality and speed of decision making; dependency management, productivity analytics, and run-time error feedback