Download JAR files tagged by systems with all dependencies

The core of the Struts framework is a flexible control layer based on standard technologies like Java Servlets, JavaBeans, ResourceBundles, and Extensible Markup Language (XML), as well as various Jakarta Commons packages. Struts encourages application architectures based on the Model 2 approach, a variation of the classic Model-View-Controller (MVC) design paradigm. Struts provides its own Controller component and integrates with other technologies to provide the Model and the View. For the Model, Struts can interact with any standard data access technology, including Enterprise Java Beans, JDBC, and Object Relational Bridge. For the View, Struts works well with JavaServer Pages, including JSTL and JSF, as well as Velocity Templates, XSLT, and other presentation systems. The Struts framework provides the invisible underpinnings every professional web application needs to survive. Struts helps you create an extensible development environment for your application, based on published standards and proven design patterns.

The Finch HRIS API provides a unified way to connect to a multitide of HRIS systems. The API requires an access token issued by Finch. By default, Organization and Payroll requests use Finch's [Data Syncs](/development-guides/Data-Syncs). If a request is made before the initial sync has completed, Finch will request data live from the provider. The latency on live requests may range from seconds to minutes depending on the provider and batch size. For automated integrations, Deductions requests (both read and write) are always made live to the provider. Latencies may range from seconds to minutes depending on the provider and batch size. Employer products are specified by the product parameter, a space-separated list of products that your application requests from an employer authenticating through Finch Connect. Valid product names are— - `company`: Read basic company data - `directory`: Read company directory and organization structure - `individual`: Read individual data, excluding income and employment data - `employment`: Read individual employment and income data - `payment`: Read payroll and contractor related payments by the company - `pay_statement`: Read detailed pay statements for each individual - `benefits`: Create and manage deductions and contributions and enrollment for an employer [](https://god.gw.postman.com/run-collection/21027137-08db0929-883d-4094-a9ce-dbf5a9bee4a4?action=collection%2Ffork&collection-url=entityId%3D21027137-08db0929-883d-4094-a9ce-dbf5a9bee4a4%26entityType%3Dcollection%26workspaceId%3D1edf19bc-e0a8-41e9-ac55-481a4b50790b)

Jadex Rules is a small lightweight rule engine, which currently employs the well-known Rete algorithm for highly efficient rule matching. Jadex rules is therefore similar to other rule engines like JESS and Drools. Despite the similarities there are also important differences between these systems: * Jadex Rules is very small and intended to be used as component of other software. Even though rules can be specified in a Java dialect as well as (a small variation of) the CLIPS language its primary usage is on the API level. Jadex Rules is currently the core component of the Jadex BDI reasoning engine. * Jadex Rules cleanly separates between state and rule representation. This allows the state implementation as well as the matcher to be flexibly exchanged. Some experiments have e.g. been conducted with a Jena representation. Regarding the matcher, it is planned to support also the Treat algorithm, which has a lower memory footprint than Rete. * Jadex Rules pays close attention to rule debugging. The state as well as the rete engine can be observed at runtime. The rule debugger provides functionalities to execute a rule program stepwise and also use rule breakpoints to stop the execution at those points.

Java Prolog Interface (JPI) is an Application Provider Interface (API) for interaction between Java and Prolog programming languages. Is a bidirectional interface that communicate Java applications with Prolog program or database and Prolog procedures with Java class and methods. JPI is an abstraction layer over concrete prolog drivers over Prolog Engines. This API define all mechanism to interact with any Prolog Engine and maintain the application independent to a specific underlying engine. JPI have several connectors to open source prolog engines like SWI, YAP, XSB native engines and tuProlog, jTrolog, jLog Java based prolog engines. JPI study all related Java-Prolog integration libraries and take the betters features from each solution with the propose to achieve a common integration interface. The last feature allows switch the under laying Prolog Engine driver and the application code still be the same. JPI run over any Java Virtual Machine that support Java SE 5 or above. The project was tested over HotSpot, Open J9 and JRockit Virtual Machines over Operating Systems like Windows (7,8,10), Linux (Debian, Ubuntu) and Mac OS X. Can be deployed on Servlets Containers like Jetty, Tomcat or Glassfish Application Server. JPI can be include in any Java Project using the commonest Java Integration Development Enviroment (IDE) like Eclipse, Netbeans, IntelijIDEA and so on. JPI is developed and maintained by Prolobjectlink Project an open source initiative for build logic based applications using Prolog like fundamental Logic Programming Language in the persistence layer and application programming.

Jadex Rules is a small lightweight rule engine, which currently employs the well-known Rete algorithm for highly efficient rule matching. Jadex rules is therefore similar to other rule engines like JESS and Drools. Despite the similarities there are also important differences between these systems: * Jadex Rules is very small and intended to be used as component of other software. Even though rules can be specified in a Java dialect as well as (a small variation of) the CLIPS language its primary usage is on the API level. Jadex Rules is currently the core component of the Jadex BDI reasoning engine. * Jadex Rules cleanly separates between state and rule representation. This allows the state implementation as well as the matcher to be flexibly exchanged. Some experiments have e.g. been conducted with a Jena representation. Regarding the matcher, it is planned to support also the Treat algorithm, which has a lower memory footprint than Rete. * Jadex Rules pays close attention to rule debugging. The state as well as the rete engine can be observed at runtime. The rule debugger provides functionalities to execute a rule program stepwise and also use rule breakpoints to stop the execution at those points.