Resource-Driven CLP-Based Test Case Generation

Albert, Elvira; Gómez-Zamalloa, Miguel; Rojas, José Miguel

doi:10.1007/978-3-642-32211-2_3

Cited by 4 publications

(10 citation statements)

References 20 publications

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“…The closest studies are the ones from De Oliveira et al [25] and Albert et al [26], which fit the context of this study. However, both studies leveraged only a subset of proxies investigated in this paper, focused on different testing problems and techniques.…”

Section: Performance Proxiessupporting

confidence: 67%

“…De Oliveira et al [25] investigated performance proxies in the context of regression testing. Albert et al [26] proposed three performance proxies for symbolic execution and showed their benefits on example programs. Symbolic execution can be used as an alternative technique to generate test cases rather than GAs; however, it has various limitations widely discussed in the literature [42,43], such as the path explosion problem, it cannot handle external environmental dependencies, and complex objects.…”

Section: Performance Proxiesmentioning

confidence: 99%

“…Therefore, this proxy only considers loops with a frequency higher than one. [26]. We implement two types of method call proxies: covered method calls (I 2 ), which is related to method calls in the paths of the CFG that are covered by a test t; and test case method calls (I 3 ), which counts method calls in t. Notice, the former proxy considers the number of calls to each production method (i.e., the frequency) rather than a single boolean value denoting whether a method has been called or not, as in method coverage [8].…”

Section: Performance Proxiesmentioning

confidence: 99%

See 2 more Smart Citations

Testing with Fewer Resources: An Adaptive Approach to Performance-Aware Test Case Generation

Grano

Laaber

Panichella

et al. 2021

IIEEE Trans. Software Eng.

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Automated test case generation is an effective technique to yield high-coverage test suites. While the majority of research effort has been devoted to satisfying coverage criteria, a recent trend emerged towards optimizing other non-coverage aspects. In this regard, runtime and memory usage are two essential dimensions: less expensive tests reduce the resource demands for the generation process and for later regression testing phases. This study shows that performance-aware test case generation requires solving two main challenges: providing accurate measurements of resource usage with minimal overhead and avoiding detrimental effects on both final coverage and fault detection effectiveness. To tackle these challenges we conceived a set of performance proxies (inspired by previous work on performance testing) that provide an approximation of the test execution costs (i.e., runtime and memory usage). Thus, we propose an adaptive strategy, called pDynaMOSA, which leverages these proxies by extending DynaMOSA, a state-of-the-art evolutionary algorithm in unit testing. Our empirical study -involving 110 non-trivial Java classes-reveals that our adaptive approach has comparable results to DynaMOSA over seven different coverage criteria (including branch, line, and weak mutation coverage) and similar fault detection effectiveness (measured via strong mutation coverage). Additionally, we observe statistically significant improvements regarding runtime and memory usage for test suites with a similar level of target coverage. Our quantitative and qualitative analyses highlight that our adaptive approach facilitates selecting better test inputs, which is an essential factor to test production code with fewer resources.

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Section: Performance Proxiessupporting

confidence: 67%

Section: Performance Proxiesmentioning

confidence: 99%

Section: Performance Proxiesmentioning

confidence: 99%

See 1 more Smart Citation

Testing with Fewer Resources: An Adaptive Approach to Performance-Aware Test Case Generation

Grano

Laaber

Panichella

et al. 2021

IIEEE Trans. Software Eng.

View full text Add to dashboard Cite

show abstract

“…To the best of our knowledge, previous approaches (e.g., [4,17]) to test case generation based on partial evaluation, the closest to our approach, do not claim full coverage w.r.t. any coverage criteria.…”

mentioning

confidence: 85%

A framework for computing finite SLD trees

Nishida

Vidal

2015

Journal of Logical and Algebraic Methods in Programming

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The search space of SLD resolution, usually represented by means of a socalled SLD tree, is often infinite. However, there are many applications that must deal with possibly infinite SLD trees, like partial evaluation or some static analyses. In this context, being able to construct a finite representation of an infinite SLD tree becomes useful.In this work, we introduce a framework to construct a finite data structure representing the (possibly infinite) SLD derivations for a goal. This data structure, called closed SLD tree, is built using four basic operations: unfolding, flattening, splitting, and subsumption. We prove some basic properties for closed SLD trees, namely that both computed answers and calls are preserved. We present a couple of simple strategies for constructing closed SLD trees with different levels of abstraction, together with some examples of its application. Finally, we illustrate the viability of our approach by introducing a test case generator based on exploring closed SLD trees.

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“…Finally, other works have focused on automation. However, most of this research has focused on automating the generation of load test suites [1,13]. For example, [16] proposes an approach to automate the generation of test cases based on specified levels of load and combinations of resources.…”

Section: Related Workmentioning

confidence: 99%