In this issue
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In this issue, we have two special sections and ten regular research papers. The first special section is on predictive models for software quality, whereas the second is on software quality in software-intensive systems. I would like to thank the guest editors for the former, Leandro Minku, Ayşe Bener and Burak Turhan as well as the guest editors for the latter, Emilia Mendes and Dietmar Winkler, for all their hard work in bringing these special sections to publication. The first five regular papers are linked by the common themes of testing, maintenance and design, whereas the next two consider quality from the users’ viewpoint. The final three papers in this issue deal with automation of language translation, security and green computing, respectively. In BMulti-device coverage testing of mobile applications^, Sergiy Vilkomir discusses how many mobile devices must be tested to effectively test mobile software applications. During a set of experiments, 15 Android applications were tested on 30 mobile devices. The author presents a number of recommendations for increasing the effectiveness of mobile software application testing without increasing costs. Turning to software maintenance, the paper BA model for estimating change propagation in software^ by Kecia A. M. Ferreira, Mariza A. S. Bigonha, Roberto S. Bigonha, Bernardo N. de Lima, Bárbara M. Gomes and Luiz Felipe O. Mendes presents a model for estimating the impact of change propagation. The model takes as input the number of modules which will be changed initially and returns the estimated number of change steps. The model will help software engineers to allocate resources during maintenance. Divergence between design and implementation can cause many problems during software maintenance. In BRound-trip engineering with the Two-Tier Programming Toolkit, A.H. Eden, E. Gasparis, J. Nicholson and R. Kazman describe a toolkit which supports re-engineering of native Java programs. The toolkit includes a visualization and design recovery tool, which generates charts from the code that can be edited to reflect the intended design. A verification Software Qual J (2018) 26:193–195 https://doi.org/10.1007/s11219-018-9411-0