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J2EE integrated development framework,for the rapid build enterprise applications.Based on Struts,Spring,Hibernate constructed to provide Web systems development functions commonly used components. Simply configure can be solved the general problems in the process of developing encountered. For example,already has built in login interface,user and role management,base AOP paging,logging feature and a lot more. It's a Java package, a class library for Java programmers. It's not an application for end-users in itself, but something that programmers can embed into their products.

Stopwatch is a free, simple, highly extensible, Java API that allows developers to easily monitor whole application or any part of it. By default Stopwatch generate reports about hits, execution times (total, average, minimum, maximum) as well as load but it can be easily extended to measure anything else by providing custom engine. Out of the box Stopwatch uses an in-memory HSQL database. It is able to persist collected data using a "storage". There is "storage" provided to persist into HSQL database and custom "storage" can be easily integrated.

MyDtt-Plus is a starter of spring-boot, It is an object-oriented Java framework that helps developers increase productivity, "Domain Driven Table" is the concept of DTT, It makes you focus more on domain objects rather than tables. Aims to make it easy to automatically create DB tables based on your Java model with annotation driven. It's also support the ability of create table automatically for MyBatis what Hibernate can do and optionally export SQL to local file，Each table can be added database name concat with table name and fully comments, It can work with ORM frameworks such as MyBatis-Plus and MyBatis with little learning and usage costs. It's worth mentioning that DTT can be MyBatis-Plus is integrated in a 0-code way, just like JPA. However, MyDtt-Plus and MyBatis-Plus may be easier to expand and use than JPA. In addition to supporting the functions of JPA, DDT provides multi-table associated SQL DDL based on MyBatis operation, DTT support databases server for MYSQL, ORACLE, DB2, SQLSERVER, MARIADB, POSTGRESQL and embedded database for H2, HSQL, DERBY.

The SAP Java Connector (SAP JCo) is a toolkit that allows a Java application to communicate with any SAP system. It combines an easy to use API with unprecedented flexibility and performance. The package supports both, Java to SAP System as well as SAP System to Java calls. - All SAP Connectors are licensed without additional license fees as part of the respective solution or component license. However, please note that each connector may be used only for connecting external (non-SAP) applications to SAP Systems / SAP Solutions. Scenarios, in which two external (non-SAP) applications are integrated via an SAP Connector, are not allowed. - The redistribution of any connector is not allowed. - All SAP users accessing application functionality through the relevant connector are required to be licensed under a respective solution or component license. To use the SAP JCo with the jco-jar project, you need to either install the SAP JCo jar downloaded from SAP to your local Maven repository (variant a) or deploy it to e.g. an enterprise Maven repository like Nexus or Artifactory (variant b): (a) mvn install:install-file -DgroupId=com.github.easonjim -DartifactId=com.sap.conn.jco.sapjco3 -Dversion=3.0.11 -Dpackaging=jar -Dfile=path/to/sapjco3.jar (b) mvn deploy:deploy-file -DrepositoryId=[your.repo.id] -DgroupId=com.github.easonjim -DartifactId=com.sap.conn.jco.sapjco3 -Dversion=3.0.11 -Dpackaging=jar -Dfile=path/to/sapjco3.jar

Luzzu is a Quality Assessment Framework for Linked Open Datasets. It is a generic framework based on the Dataset Quality Ontology (daQ), allowing users to define their own quality metrics. Luzzu is an integrated platform that: - assesses Linked Data quality using a library of generic and user-provided domain specific quality metrics in a scalable manner; - provides queryable quality metadata on the assessed datasets; - assembles detailed quality reports on assessed datasets. Furthermore, the infrastructure: - scales for the assessment of big datasets; - can be easily extended by the users by creating their custom and domain-specific pluggable metrics, either by employing a novel declarative quality metric specification language or conventional imperative plugins; - employs a comprehensive ontology framework for representing and exchanging all quality related information in the assessment workflow; - implements quality-driven dataset ranking algorithms facilitating use-case driven discovery and retrieval.