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This artifact provides the implementation of the L* learning algorithm described in the paper "Learning Regular Sets from Queries and Counterexamples" (https://doi.org/10.1016/0890-5401(87)90052-6) by Dana Angluin including variations and optimizations thereof such as the versions based on "On the Learnability of Infinitary Regular Sets" (https://dx.doi.org/10.1006/inco.1995.1070) by Oded Maler and Amir Pnueli or "Inference of finite automata using homing sequences" (http://dx.doi.org/10.1006/inco.1993.1021) by Ronald L. Rivest and Robert E. Schapire.

This artifact provides the implementation of the model checker presented in the paper "M3C: Modal Meta Model Checking" (https://dx.doi.org/10.1007/978-3-030-00244-2_15) by Bernhard Steffen and Alnis Murtovi. The paper is based on "Model Checking for Context-Free Processes" (https://link.springer.com/chapter/10.1007/BFb0084787) by Olaf Burkart and Bernhard Steffen. Note that this implementation requires a runtime dependency to a specific ADDLib backend (see https://add-lib.scce.info/), which is not explicitly included in this artifact due to packaging reasons.

This Lutra submodule provides a common framework that other submodules in Lutra use and extend. It includes an implementation of OTTR's data model with classes for templates, instances, types, etc.; a system for handling results and error messages; core interfaces and abstract classes for streamed pipelines for parsing and writing templates and instances; as well as implementation of the TemplateStore, a container for templates, with algorithms for checking correctness of templates and expanding and checking correctness of instances. Lutra is the reference implementation of the OTTR framework. For more information about OTTR, see http://ottr.xyz.

Maltcms, short for "Modular Application Toolkit for Chromatography Mass-Spectrometry" is an application framework mainly suited for developers working in the domain of bioinformatics for metabolomics and proteomics. Its aim is to provide reusable, efficient datastructures, abstracting from the various low-level data-formats like netcdf (ANDIMS), mzXML, mzData and mzML and providing consistent access to data features like mass spectra, chromatograms and metadata. Furthermore, Maltcms provides a platform for the implementation and execution of processing pipelines. New and existing algorithms can be easily implemented or included and executed together with existing processing elements.

This open source software is a reference implementation, consisting of software and related files, for the OMG specification called the Semantics of a Foundational Subset for Executable UML Models (fUML). The reference implementation is intended to implement the execution semantics of UML activity models, accepting an XMI file from a conformant UML model as its input and providing an execution trace of the selected activity model(s) as its output. The core execution engine, which is directly generated from the normative syntactic and semantic models for fUML, may also be used as a library implementation of fUML in other software.

COBYLA2 is an implementation of Powell's nonlinear derivative free constrained optimization that uses a linear approximation approach. The algorithm is a sequential trust region algorithm that employs linear approximations to the objective and constraint functions, where the approximations are formed by linear interpolation at n + 1 points in the space of the variables and tries to maintain a regular shaped simplex over iterations. It solves nonsmooth NLP with a moderate number of variables (about 100). Inequality constraints only. The initial point X is taken as one vertex of the initial simplex with zero being another, so, X should not be entered as the zero vector.

This module contains library classes for accessing the ThreadFix REST API. The ThreadFix IDE plugins use this library to retrieve application and vulnerability marker information, and in the ThreadFix scanner plugins to get endpoint information and upload scans to ThreadFix applications. The easiest way to start using the library is with the PluginClient or ThreadFixRestClient classes. Both have constructors that take a PropertiesManager instance, which holds the ThreadFix API key and url information. The default PropertiesManager implementation stores these properties in threadfix.properties, but the ThreadFix plugins extend the default PropertiesManager class to override this behavior for the target platform.

1) This module contains various Zookeeper recipe implementations. 2) The recipe directory name should specify the name of the recipe you are implementing - eg. zookeeper-recipes-lock. 3) It would be great if you can provide both the java and c recipes for the zookeeper recipes. C recipes go in to zookeeper-recipes/zookeeper-recipes-[recipe-name]/src/c Java implementation goes into zookeeper-recipes/zookeeper-recipes-[recipe-name]/src/java. 4) The recipes hold high standards like our zookeeper c/java libraries, so make sure that you include some unit testing with both the c and java recipe code. 5) Also, please name your c client public methods as zkr_recipe-name_methodname (eg. zkr_lock_lock in zookeeper-recipes-lock/src/c) 6) To run the c tests in all the recipes, - make sure the main zookeeper c libraries in zookeeper-client-c are compiled. Run autoreconf -if;./configure; make. The libraries will be installed in {top}/src/c/.libs. - run autoreconf if;./configure;make run-check in zookeeper-recipes/$recipename/src/c