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)

Statistical Model Checking for Product Lines

International audienceWe report on the suitability of statistical model checking forthe analysis of quantitative properties of product line models by an extendedtreatment of earlier work by the authors. The type of analysis thatcan be performed includes the likelihood of specific product behaviour,the expected average cost of products (in terms of the attributes of theproducts’ features) and the probability of features to be (un)installed atruntime. The product lines must be modelled in QFLan, which extendsthe probabilistic feature-oriented language PFLan with novel quantitativeconstraints among features and on behaviour and with advancedfeature installation options. QFLan is a rich process-algebraic specifi-cation language whose operational behaviour interacts with a store ofconstraints, neatly separating product configuration from product behaviour.The resulting probabilistic configurations and probabilistic behaviourconverge in a discrete-time Markov chain semantics, enablingthe analysis of quantitative properties. Technically, a Maude implementationof QFLan, integrated with Microsoft’s SMT constraint solver Z3,is combined with the distributed statistical model checker MultiVeStA,developed by one of the authors. We illustrate the feasibility of our frameworkby applying it to a case study of a product line of bikes

Family-Based Model Checking with mCRL2

\u3cp\u3eFamily-based model checking targets the simultaneous verfication of multiple system variants, a technique to handle feature-based variability that is intrinsic to software product lines (SPLs). We present an approach for family-based verification based on the feature μ-calculus μL\u3csub\u3ef\u3c/sub\u3e, which combines modalities with feature expressions. This logic is interpreted over featured transition systems, a well-accepted model of SPLs, which allows one to reason over the collective behavior of a number of variants (a family of products). Via an embedding into the modal μ-calculus with data, underpinned by the general-purpose mCRL2 toolset, off-the-shelf tool support for μLf becomes readily available. We illustrate the feasibility of our approach on an SPL benchmark model and show the runtime improvement that family-based model checking with mCRL2 offers with respect to model checking the benchmark product-by-product.\u3c/p\u3

Facilitating Reuse in Multi-goal Test-Suite Generation for Software Product Lines

Abstract. Software testing is still the most established and scalable quality-assurance technique in practice. However, generating effective test suites remains computationally expensive, consisting of repetitive reachability analyses for multiple test goals according to a coverage cri-terion. This situation is even worse when testing entire software prod-uct lines, i.e., families of similar program variants, requiring a sufficient coverage of all derivable program variants. Instead of considering ev-ery product variant one-by-one, family-based approaches are variability-aware analysis techniques in that they systematically explore similarities among the different variants. Based on this principle, we present a novel approach for automated product-line test-suite generation incorporating extensive reuse of reachability information among test cases derived for different test goals and/or program variants. We present a tool imple-mentation on top of CPA/tiger which is based on CPAchecker, and provide evaluation results obtained from various experiments, revealing a considerable increase in efficiency compared to existing techniques

Validated Test Models for Software Product Lines : Featured Finite State Machines

Variants of the finite state machine (FSM) model have been extensively used to describe the behaviour of reactive systems. In particular, several model-based testing techniques have been developed to support test case generation and test case executions from FSMs. Most such techniques require several validation properties to hold for the underlying test models. In this paper, we propose an extension of the FSM test model for software product lines (SPLs), named featured finite state machine (FFSM). As the first step towards using FFSMs as test models, we define feature-oriented variants of basic test model validation criteria. We show how the high-level validation properties coincide with the necessary properties on the product FSMs. Moreover, we provide a mechanised tool prototype for checking the feature-oriented properties using satisfiability modulo theory (SMT) solver tools. We investigate the applicability of our approach by applying it to both randomly generated FFSMs as well as those from a realistic case study (the Body Comfort System). The results of our study show that for random FFSMs over 16 independent non-mandatory features, our technique provides substantial efficiency gains for the set of proposed validity checks. © Springer International Publishing AG 2017VR Project - EFFEMBACKKS Project - AUTO-CAA

Matching implementations to specifications: the corner cases of ioco

Contains fulltext : 204598.pdf (Publisher’s version ) (Open Access)SAC'19: 34th ACM/SIGAPP Symposium on Applied Computing, Limassol, Cyprus — April 08 - 12, 201