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Dryuf Concurrent is enhancement over original Java Concurrent Future design. Apart from providing ListenableFuture functionality, it provides flexibility how to handle cancel() operations, can delay the notifications. It allows various types of notification listeners, distinguishing among successful end, failure and end due to cancel request. Last but not least, it has very low memory footprint and excellent performance, even outperforming JDK Future without listener support.

fastutil extends the Java Collections Framework by providing type-specific maps, sets, lists, and queues with a small memory footprint and fast operations; it provides also big (64-bit) arrays, sets, and lists, sorting algorithms, fast, practical I/O classes for binary and text files, and facilities for memory mapping large files. This jar (fastutil-core.jar) contains data structures based on integers, longs, doubles, and objects, only; fastutil.jar contains all classes. If you have both jars in your dependencies, this jar should be excluded.

Programmatically generate, load, modify, and convert Excel .xlsx spreadsheets in your Java applications. GrapeCity Documents for Excel (GcExcel) is a cross-platform high-speed, small-footprint spreadsheet API library that requires no dependencies on Excel. The powerful calculation engine supports 450+ Excel Functions and custom functions to perform complex calculations. GcExcel is 2x+ faster and uses less memory than Apache POI and allows you to save to XLSX, PDF, HTML, CSV, JSON and Images. Deploy your applications to the cloud, Windows, Mac, or Linux. If you'd like to remove the trial watermark and other trial limitations, please email [email protected] to request your 30-day evaluation key.

zlib is designed to be a free, general-purpose, legally unencumbered -- that is, not covered by any patents -- lossless data-compression library for use on virtually any computer hardware and operating system. The zlib data format is itself portable across platforms. Unlike the LZW compression method used in Unix compress(1) and in the GIF image format, the compression method currently used in zlib essentially never expands the data. (LZW can double or triple the file size in extreme cases.) zlib's memory footprint is also independent of the input data and can be reduced, if necessary, at some cost in compression.

Mbassador is a fast and flexible event bus system following the publish subscribe pattern. It is designed for ease of use and aims to be feature rich and extensible while preserving resource efficiency and performance. It provides non-blocking iterators and minimal write contention with low memory footprint. Some features: declarative handler definition via annotations, sync and/or async event delivery, weak or strong references, configurable event filters,

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.

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.

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.