Mutation testing has been found to be an efficient technique in order to assess the quality of a test suite. The use of Simulink models is increasing in both industry and academia to model and simulate complex systems such as Cyber-Physical Systems (CPSs). An advantage of Simulink is its ease to integrate software and control algorithms with complex mathematical models that typically represent continuous dynamic behaviors. In addition to that, the increasing trend of industry in adopting product line engineering methods to efficiently support the variability that their products demand is resulting in configurable Simulink models. Consequently, many configurations can be employed to test the configurable system. Each of these configurations will have a set of mutants, which will be in accordance with the configuration characteristics (i.e., features). However, manually generating and configuring mutants for each of the configurations is a time-consuming and non-systematic process. To deal with this problem, we propose a methodology supported by a tool that automatically generates mutants for configurable Simulink models.
Autores: Aitor Arrieta / Urtzi Markiegi / Leire Etxeberria /
Palabras Clave: Cyber-Physical Systems - Feature Modeling - MATLAB/Simulink - Mutation testing - Product Line Engineering
Prodevelop A Test Automation Case Study: From academic research to the real-world tool chain
Autores: Ismael Torres / Tanja Vos / Urtzi Markiegi / Ernesto Calás / Fernando Pastor / Leire Etxeberria / Iñigo Aldalur / Xabier Valencia /
Palabras Clave: GUI Test automation - Industrial case study - Knowledge transfer - Testing traceability
Variability modeling is demanded by industrial companies to support customization of their products. However, not all the software tools include variability modeling mechanisms. IBM Rhapsody is one of the leading environments for modeling complex industrial systems. In this paper we present Delta Rhapsody, a tool for modeling variability in IBM Rhapsody models employing the delta modeling paradigm.
Autores: Xabier Perez / Oskar Berreteaga / Leire Etxeberria / Aitor Arrieta / Urtzi Markiegi /
Palabras Clave: Delta Modelling - Rhapsody - Variability
Artículo relevante publicado en 2018 en el ISTContext: Software Product Line (SPL) testing is challenging mainly due to the potentially huge number ofproducts under test. Most of the research on this field focuses on making testing affordable by selecting arepresentative subset of products to be tested. However, once the tests are executed and some failures revealed,debugging is a cumbersome and time consuming task due to difficulty to localize and isolate the faulty featuresin the SPL.Objective: This paper presents a debugging approach for the localization of bugs in SPLs.Method: The proposed approach works in two steps. First, the features of the SPL are ranked according to theirsuspiciousness (i.e., likelihood of being faulty) using spectrum-based localization techniques. Then, a novel faultisolation approach is used to generate valid products of minimum size containing the most suspicious features,helping to isolate the cause of failures.Results: For the evaluation of our approach, we compared ten suspiciousness techniques on nine SPLs of differentsizes. The results reveal that three of the techniques (Tarantula, Kulcynski2 and Ample2) stand out over the rest,showing a stable performance with different types of faults and product suite sizes. By using these metrics, faultswere localized by examining between 0.1% and 14.4% of the feature sets.Conclusion: Our results show that the proposed approach is effective at locating bugs in SPLs, serving as a helpfulcomplement for the numerous approaches for testing SPLs.
Autores: Aitor Arrieta / Sergio Segura / Urtzi Markiegi / Goiuria Sagardui / Leire Etxeberria /
Palabras Clave: Debugging - Feature Models - software product lines - Spectrum-based fault localization
