Test-aware combinatorial interaction testing

Combinatorial interaction testing (CIT) approaches system- atically sample a given configuration space and select a set of configurations, in which each valid t-way option setting combination appears at least once. A battery of test cases are then executed in the selected configurations. Exist- ing CIT approaches, however, do not provide a system- atic way of handling test-specific inter-option constraints. Improper handling of such constraints, on the other hand, causes masking effects, which in turn causes testers to de- velop false confidence in their test processes, believing them have tested certain option setting combinations, when they in fact have not. In this work, to avoid the harmful conse- quences of masking effects caused by improper handling of test-specific constraints, we compute t-way test-aware cov- ering arrays. A t-way test-aware covering array is not just a set of configurations as is the case in traditional covering arrays, but a set of configurations, each of which is asso- ciated with a set of test cases. We furthermore present a set of empirical studies conducted by using two widely-used highly-configurable software systems as our subject applica- tions, demonstrating that test-specific constraints are likely to occur in practice and the proposed approach is a promis- ing and effective way of handling them

Hybrid Algorithms Based on Integer Programming for the Search of Prioritized Test Data in Software Product Lines

In Software Product Lines (SPLs) it is not possible, in general, to test all products of the family. The number of products denoted by a SPL is very high due to the combinatorial explosion of features. For this reason, some coverage criteria have been proposed which try to test at least all feature interactions without the necessity to test all products, e.g., all pairs of features (pairwise coverage). In addition, it is desirable to first test products composed by a set of priority features. This problem is known as the Prioritized Pairwise Test Data Generation Problem. In this work we propose two hybrid algorithms using Integer Programming (IP) to generate a prioritized test suite. The first one is based on an integer linear formulation and the second one is based on a integer quadratic (nonlinear) formulation. We compare these techniques with two state-of-the-art algorithms, the Parallel Prioritized Genetic Solver (PPGS) and a greedy algorithm called prioritized-ICPL. Our study reveals that our hybrid nonlinear approach is clearly the best in both, solution quality and computation time. Moreover, the nonlinear variant (the fastest one) is 27 and 42 times faster than PPGS in the two groups of instances analyzed in this work.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Partially funded by the Spanish Ministry of Economy and Competitiveness and FEDER under contract TIN2014-57341-R, the University of Málaga, Andalucía Tech and the Spanish Network TIN2015-71841-REDT (SEBASENet)

Fuzzy Adaptive Tuning of a Particle Swarm Optimization Algorithm for Variable-Strength Combinatorial Test Suite Generation

Combinatorial interaction testing is an important software testing technique that has seen lots of recent interest. It can reduce the number of test cases needed by considering interactions between combinations of input parameters. Empirical evidence shows that it effectively detects faults, in particular, for highly configurable software systems. In real-world software testing, the input variables may vary in how strongly they interact, variable strength combinatorial interaction testing (VS-CIT) can exploit this for higher effectiveness. The generation of variable strength test suites is a non-deterministic polynomial-time (NP) hard computational problem \cite{BestounKamalFuzzy2017}. Research has shown that stochastic population-based algorithms such as particle swarm optimization (PSO) can be efficient compared to alternatives for VS-CIT problems. Nevertheless, they require detailed control for the exploitation and exploration trade-off to avoid premature convergence (i.e. being trapped in local optima) as well as to enhance the solution diversity. Here, we present a new variant of PSO based on Mamdani fuzzy inference system \cite{Camastra2015,TSAKIRIDIS2017257,KHOSRAVANIAN2016280}, to permit adaptive selection of its global and local search operations. We detail the design of this combined algorithm and evaluate it through experiments on multiple synthetic and benchmark problems. We conclude that fuzzy adaptive selection of global and local search operations is, at least, feasible as it performs only second-best to a discrete variant of PSO, called DPSO. Concerning obtaining the best mean test suite size, the fuzzy adaptation even outperforms DPSO occasionally. We discuss the reasons behind this performance and outline relevant areas of future work.Comment: 21 page

VADER - A Satellite Mission Concept For High Precision Dark Energy Studies

We present a satellite mission concept to measure the dark energy equation of state parameter w with percent-level precision. The Very Ambitious Dark Energy Research satellite (VADER) is a multi-wavelength survey mission joining X-ray, optical, and IR instruments for a simultaneous spectral coverage from 4microns (0.3eV) to 10keV over a field of view (FoV) of 1 square degree. VADER combines several clean methods for dark energy studies, the baryonic acoustic oscillations in the galaxy and galaxy cluster power spectrum and weak lensing, for a joint analysis over an unrivalled survey volume. The payload consists of two XMM-like X-ray telescopes with an effective area of 2,800cm^2 at 1.5keV and state-of-the-art wide field DEPFET pixel detectors (0.1-10keV) in a curved focal plane configuration to extend the FoV. The X-ray telescopes are complemented by a 1.5m optical/IR telescope with 8 instruments for simultaneous coverage of the same FoV from 0.3 to 4 microns. The 8 dichroic-separated bands (u,g,r,z,J,H,K,L) provide accurate photometric galaxy redshifts, whereas the diffraction-limited resolution of the central z-band allows precise shape measurements for cosmic shear analysis. The 5 year VADER survey will cover a contiguous sky area of 3,500 square degrees to a depth of z~2 and will yield accurate photometric redshifts and multi-wavelength object parameters for about 175,000 galaxy clusters, one billion galaxies, and 5 million AGN. VADER will not only provide unprecedented constraints on the nature of dark energy, but will additionally extend and trigger a multitude of cosmic evolution studies to very large (>10 Gyrs) look-back times.Comment: 14 pages, 7 figures, accepted for publication in the SPIE conference proceeding