Spinal Test Suites for Software Product Lines

A major challenge in testing software product lines is efficiency. In particular, testing a product line should take less effort than testing each and every product individually. We address this issue in the context of input-output conformance testing, which is a formal theory of model-based testing. We extend the notion of conformance testing on input-output featured transition systems with the novel concept of spinal test suites. We show how this concept dispenses with retesting the common behavior among different, but similar, products of a software product line.Comment: In Proceedings MBT 2014, arXiv:1403.704

An automated Model-based Testing Approach in Software Product Lines Using a Variability Language.

This paper presents the application of an automated testing approach for Software Product Lines (SPL) driven by its state-machine and variability models. Context: Model-based testing provides a technique for automatic generation of test cases using models. Introduction of a variability model in this technique can achieve testing automation in SPL. Method: We use UML and CVL (Common Variability Language) models as input, and JUnit test cases are derived from these models. This approach has been implemented using the UML2 Eclipse Modeling platform and the CVL-Tool. Validation: A model checking tool prototype has been developed and a case study has been performed. Conclusions: Preliminary experiments have proved that our approach can find structural errors in the SPL under test. In our future work we will introduce Object Constraint Language (OCL) constraints attached to the input UML mode

Colored model based testing for software product lines (CMBT-SWPL)

Over the last decade, the software product line domain has emerged as one of the mostpromising software development paradigms. The main benefits of a software product lineapproach are improvements in productivity, time to market, product quality, and customersatisfaction.Therefore, one topic that needs greater emphasis is testing of software product lines toachieve the required software quality assurance. Our concern is how to test a softwareproduct line as early as possible in order to detect errors, because the cost of error detectedIn early phases is much less compared to the cost of errors when detected later.The method suggested in this thesis is a model-based, reuse-oriented test technique calledColored Model Based Testing for Software Product Lines (CMBT-SWPL). CMBT-SWPLis a requirements-based approach for efficiently generating tests for products in a soft-ware product line. This testing approach is used for validation and verification of productlines. It is a novel approach to test product lines using a Colored State Chart (CSC), whichconsiders variability early in the product line development process. More precisely, the vari-ability will be introduced in the main components of the CSC. Accordingly, the variabilityis preserved in test cases, as they are generated from colored test models automatically.During domain engineering, the CSC is derived from the feature model. By coloring theState Chart, the behavior of several product line variants can be modeled simultaneouslyin a single diagram and thus address product line variability early. The CSC representsthe test model, from which test cases using statistical testing are derived.During application engineering, these colored test models are customized for a specificapplication of the product line. At the end of this test process, the test cases are generatedagain using statistical testing, executed and the test results are ready for evaluation. Inxaddition, the CSC will be transformed to a Colored Petri Net (CPN) for verification andsimulation purposes.The main gains of applying the CMBT-SWPL method are early detection of defects inrequirements, such as ambiguities incompleteness and redundancy which is then reflectedin saving the test effort, time, development and maintenance costs

Optimizing Model-Based Software Product Line Testing with Graph Transformations

Software Product Lines (SPLs) are increasing in relevance and importance as various domains strive to cope with the challenges of supporting a high degree of variability in modern software systems.  Especially the systematic testing of SPLs is non-trivial as a high degree of variability implies a vast number of possible products.As testing every valid product individually quickly becomes infeasible, heuristics are often used to choose a representative subset of products to be tested.  MoSo-PoLiTe (Model-Based Software Product Line Testing) is a framework for SPL testing that combines and applies combinatorial (in particular pairwise) and model-based testing to SPL feature models.  In this paper, we (1) present MoSo-PoLiTe as a novel case study for graph transformations in general and Story Driven Modelling (SDM) in particular, (2) show why we consider SDMs to be ideal for rapid prototyping optimization strategies in this context, and (3) evaluate our implemented optimizations and quantify the realized improvements for MoSo-PoLiTe

Towards Statistical Prioritization for Software Product Lines Testing

Software Product Lines (SPL) are inherently difficult to test due to the combinatorial explosion of the number of products to consider. To reduce the number of products to test, sampling techniques such as combinatorial interaction testing have been proposed. They usually start from a feature model and apply a coverage criterion (e.g. pairwise feature interaction or dissimilarity) to generate tractable, fault-finding, lists of configurations to be tested. Prioritization can also be used to sort/generate such lists, optimizing coverage criteria or weights assigned to features. However, current sampling/prioritization techniques barely take product behavior into account. We explore how ideas of statistical testing, based on a usage model (a Markov chain), can be used to extract configurations of interest according to the likelihood of their executions. These executions are gathered in featured transition systems, compact representation of SPL behavior. We discuss possible scenarios and give a prioritization procedure illustrated on an example.Comment: Extended version published at VaMoS '14 (http://dx.doi.org/10.1145/2556624.2556635

A systematic review of quality attributes and measures for software product lines

[EN] It is widely accepted that software measures provide an appropriate mechanism for understanding, monitoring, controlling, and predicting the quality of software development projects. In software product lines (SPL), quality is even more important than in a single software product since, owing to systematic reuse, a fault or an inadequate design decision could be propagated to several products in the family. Over the last few years, a great number of quality attributes and measures for assessing the quality of SPL have been reported in literature. However, no studies summarizing the current knowledge about them exist. This paper presents a systematic literature review with the objective of identifying and interpreting all the available studies from 1996 to 2010 that present quality attributes and/or measures for SPL. These attributes and measures have been classified using a set of criteria that includes the life cycle phase in which the measures are applied; the corresponding quality characteristics; their support for specific SPL characteristics (e. g., variability, compositionality); the procedure used to validate the measures, etc. We found 165 measures related to 97 different quality attributes. The results of the review indicated that 92% of the measures evaluate attributes that are related to maintainability. In addition, 67% of the measures are used during the design phase of Domain Engineering, and 56% are applied to evaluate the product line architecture. However, only 25% of them have been empirically validated. In conclusion, the results provide a global vision of the state of the research within this area in order to help researchers in detecting weaknesses, directing research efforts, and identifying new research lines. In particular, there is a need for new measures with which to evaluate both the quality of the artifacts produced during the entire SPL life cycle and other quality characteristics. There is also a need for more validation (both theoretical and empirical) of existing measures. In addition, our results may be useful as a reference guide for practitioners to assist them in the selection or the adaptation of existing measures for evaluating their software product lines. © 2011 Springer Science+Business Media, LLC.This research has been funded by the Spanish Ministry of Science and Innovation under the MULTIPLE (Multimodeling Approach For Quality-Aware Software Product Lines) project with ref. TIN2009-13838.Montagud Gregori, S.; Abrahao Gonzales, SM.; Insfrán Pelozo, CE. (2012). A systematic review of quality attributes and measures for software product lines. Software Quality Journal. 20(3-4):425-486. https://doi.org/10.1007/s11219-011-9146-7S425486203-4Abdelmoez, W., Nassar, D. 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Multi-objective Optimal Test Suite Computation for Software Product Line Pairwise Testing

Lopez-Herrejon, R. E., Chicano F., Ferrer J., Egyed A., & Alba E. (2013). Multi-objective Optimal Test Suite Computation for Software Product Line Pairwise Testing. 2013 IEEE International Conference on Software Maintenance, Eindhoven, The Netherlands, September 22-28, 2013. 404–407.Software Product Lines (SPLs) are families of related software products, which usually provide a large number of feature combinations, a fact that poses a unique set of challenges for software testing. Recently, many SPL testing approaches have been proposed, among them pair wise combinatorial techniques that aim at selecting products to test based on the pairs of feature combinations such products provide. These approaches regard SPL testing as an optimization problem where either coverage (maximize) or test suite size (minimize) are considered as the main optimization objective. Instead, we take a multi-objective view where the two objectives are equally important. In this exploratory paper we propose a zero-one mathematical linear program for solving the multi-objective problem and present an algorithm to compute the true Pareto front, hence an optimal solution, from the feature model of a SPL. The evaluation with 118 feature models revealed an interesting trade-off between reducing the number of constraints in the linear program and the runtime which opens up several venues for future research.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Austrian Science Fund (FWF) project P21321-N15 and Lise Meitner Fellowship M1421-N15. Spanish Ministry of Economy and Competitiveness and FEDER under contract TIN2011-28194 and fellowship BES-2012-055967

Statistical prioritization for software product line testing: an experience report

Software product lines (SPLs) are families of software systems sharing common assets and exhibiting variabilities specific to each product member of the family. Commonalities and variabilities are often represented as features organized in a feature model. Due to combinatorial explosion of the number of products induced by possible features combinations, exhaustive testing of SPLs is intractable. Therefore, sampling and prioritization techniques have been proposed to generate sorted lists of products based on coverage criteria or weights assigned to features. Solely based on the feature model, these techniques do not take into account behavioural usage of such products as a source of prioritization. In this paper, we assess the feasibility of integrating usage models into the testing process to derive statistical testing approaches for SPLs. Usage models are given as Markov chains, enabling prioritization of probable/rare behaviours. We used featured transition systems, compactly modelling variability and behaviour for SPLs, to determine which products are realizing prioritized behaviours. Statistical prioritization can achieve a significant reduction in the state space, and modelling efforts can be rewarded by better automation. In particular, we used MaTeLo, a statistical test cases generation suite developed at ALL4TEC. We assess feasibility criteria on two systems: Claroline, a configurable course management system, and Sferion™, an embedded system providing helicopter landing assistance.</p

Model-based Quality Assurance of Cyber-Physical Systems with Variability in Space, over Time and at Runtime

Cyber-physical systems (CPS) are frequently characterized by three essential properties: CPS perform complex computations, CPS conduct control tasks involving continuous data- and signal-processing, and CPS are (parts of) distributed, and even mobile, communication systems. In addition, modern software systems like CPS have to cope with ever-growing extents of variability, namely variability in space by means of predefined configuration options (e.g., software product lines), variability at runtime by means of preplanned reconfigurations (e.g., runtime-adaptive systems), and variability over time by means of initially unforeseen updates to new versions (e.g., software evolution). Finally, depending on the particular application domain, CPS often constitute safety- and mission-critical parts of socio-technical systems. Thus, novel quality-assurance methodologies are required to systematically cope with the interplay between the different CPS characteristics on the one hand, and the different dimensions of variability on the other hand. This thesis gives an overview on recent research and open challenges in model-based specification and quality-assurance of CPS in the presence of variability. The main focus of this thesis is laid on computation and communication aspects of CPS, utilizing evolving dynamic software product lines as engineering methodology and model-based testing as quality-assurance technique. The research is illustrated and evaluated by means of case studies from different application domains

A Vision for Behavioural Model-Driven Validation of Software Product Lines

International audienceThe Software Product Lines (SPLs) paradigm promises faster development cycles and increased quality by systematically reusing software assets. This paradigm considers a family of systems, each of which can be obtained by a selection of features in a variability model. Though essential, providing Quality Assurance (QA) techniques for SPLs has long been perceived as a very difficult challenge due to the combinatorics induced by variability and for which very few techniques were available. Recently, important progress has been made by the model-checking and testing communities to address this QA challenge, in a very disparate way though. We present our vision for a unified framework combining model-checking and testing approaches applied to behavioural models of SPLs. Our vision relies on Featured Transition Systems (FTSs), an extension of transition systems supporting variability. This vision is also based on model-driven technologies to support practical SPL modelling and orchestrate various QA scenarios. We illustrate such scenarios on a vending machine SPL