SUMMARY: QuantiNemo 2 is a stochastic simulation program for quantitative population genetics. It was developed to investigate the effects of selection, mutation, recombination and drift on quantitative traits and neutral markers in structured populations connected by migration and located in heterogeneous habitats. A specific feature is that it allows to switch between an individual-based full-featured mode and a population-based faster mode. Several demographic, genetic and selective parameters can be fine-tuned in QuantiNemo 2: population, selection, trait(s) architecture, genetic map for QTL and/or markers, environment, demography and mating system are the main features. AVAILABILITY AND IMPLEMENTATION: QuantiNemo 2 is a C++ program with a source code available under the GNU General Public License version 3. Executables are provided for Windows, MacOS and Linux platforms, together with a comprehensive manual and tutorials illustrating its flexibility. The executable, manual and tutorial can be found on the website www2.unil.ch/popgen/softwares/quantinemo/, while the source code and user support are given through GitHub: github.com/jgx65/quantinemo. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A Dynamic Malware Analysis System (D-MAS), often called a sandbox, is a controlled environment in which malicious software (malware) is executed in order to identify the actions it is performing (e.g., creating processes, sending emails) when infecting computer systems. One of the most important features of security devices such as IDSs, AVSs and D-MASs, is how accurately they identify and document threats. By nature, these security devices are difficult to test since they are test systems themselves. The attackers are the testers trying to find test cases that cannot be identified by these systems. Consequently, thorough testing models are required by developers to assess the accuracy of D-MASs, an area in which very little theoretical and empirical work exists. In this paper, we lay out the basis of D-MASs accuracy assessment and we present an evaluation of eight of these systems. We propose test coverage criteria, oracle types and specifications to assess the accuracy of D-MASs. Results show that our approach is efficient at identifying accuracy problems in several D-MASs.