Search

Model-based testing has been highlighted in the last few decades. Many improvements have been proposed for this testing method. One improvement is the use of extended regular expressions (EREs) for modeling software behavior, and then using the ERE model to generate test paths. To improve the theory of test generation based on the ERE model, this article presents an algebraic system, named transition algebra, by extending Kleene algebra. Eight operations and their corresponding operational properties, including basic and nonbasic operational properties, are designed for transition algebra, and all such properties are proven. Five examples are given to illustrate the use of ERE modeling and algebraic operations. To ensure the automatic generation of test paths from the ERE model, the article proves that any ERE model constructed by transition algebra can be converted to a set of transition sequences. Compared to Kleene algebra with tests, transition algebra has more operations to build a powerful ERE model and more operational properties to process the ERE model for the generation of test paths. [ABSTRACT FROM AUTHOR]

Scientific model developers are able to verify and validate their software via metamorphic testing (MT), even when the expected output of a given test case is not readily available. The tenet is to check whether certain relations hold among the expected outputs of multiple-related inputs. Contemporary approaches require the relations to be defined before tests. Our experience shows that it is often straightforward to first define the multiple iterations of tests for performing continuous simulations, and then keep multiple and even competing metamorphic relations open for investigating the testing-result patterns. We call this new approach exploratory MT, and report our experience of applying it to detect bugs, mismatches, and constraints in automatically calibrating parameters for the United States Environmental Protection Agency's Storm Water Management Model. [ABSTRACT FROM AUTHOR]

Modern programming environments provide extensive support for inspecting, analyzing, and testing programs based on the algorithmic structure of a program. Unfortunately, support for inspecting and understanding runtime data structures during execution is typically much more limited. This paper provides a general purpose technique for abstracting and summarizing entire runtime heaps. We describe the abstract heap model and the associated algorithms for transforming a concrete heap dump into the corresponding abstract model as well as algorithms for merging, comparing, and computing changes between abstract models. The abstract model is designed to emphasize high-level concepts about heap-based data structures, such as shape and size, as well as relationships between heap structures, such as sharing and connectivity. We demonstrate the utility and computational tractability of the abstract heap model by building a memory profiler. We use this tool to identify, pinpoint, and correct sources of memory bloat for programs from DaCapo. [ABSTRACT FROM PUBLISHER]

This paper provides a systematic meta-analysis of 27 studies that investigate the impact of Test-Driven Development (TDD) on external code quality and productivity. The results indicate that, in general, TDD has a small positive effect on quality but little to no discernible effect on productivity. However, subgroup analysis has found both the quality improvement and the productivity drop to be much larger in industrial studies in comparison with academic studies. A larger drop of productivity was found in studies where the difference in test effort between the TDD and the control group's process was significant. A larger improvement in quality was also found in the academic studies when the difference in test effort is substantial; however, no conclusion could be derived regarding the industrial studies due to the lack of data. Finally, the influence of developer experience and task size as moderator variables was investigated, and a statistically significant positive correlation was found between task size and the magnitude of the improvement in quality. [ABSTRACT FROM PUBLISHER]