blogstrap.py is a simple, no frills blog content management system powered by Twitter's Bootstrap and web.py. It features most things you would come to expect from a simple blogging platform. You can browse posts by category or subcategory, see recent posts, and mark favorites. You can perform basic searches. It includes an About page. A basic tag system is implemented (popular tags are counted and shown). A simple comment system is available. A robust administrative interface is included where you can create and edit posts. You can upload images and include them on a Credits page, where you can properly attribute the original author. Comments can be set to on, off, or manual approval (moderated). Security has been a top priority since the beginning. Blogstrap.py has low resource usage and runs quickly on top of Lighttpd.
Simple Packet Sender (SPS) is a Linux packet crafting tool. It supports IPv4, IPv6 including extension headers, and tunneling IPv6 over IPv4. It does not require pcap. It features packet crafting and sending one, multiple, or flooding IPv4 and IPv6 packets of type TCP, ICMP, or UDP (or cycling through all three). All values within an Ethernet frame can be modified arbitrarily. It supports IPv4 header options, TCP header options, and TCP, ICMP, and UDP data as well, input from either a keyboard as UTF-8/ASCII, a keyboard as hexadecimal, or from a file. IPv6 support includes hop-by-hop, "first" and "last" destination, routing, authentication, and encapsulating security payload (ESP) extension headers. For those without access to a native IPv6 network, IPv6 packets can be transmitted over IPv4 (6to4). Packet fragmentation is available for IPv4, IPv6, and 6to4. The assumed maximum transmission unit (MTU) can be changed if unusual fragment sizes are needed. IP addresses and port numbers can be randomized.
Zorka is a sophisticated programmable profiling/monitoring agent for Java suitable for running with production applications. The agent integrates seamlessly with popular monitoring systems and protocols (Zabbix, Nagios, syslog, SNMP) and offers additional tracing/profiling capabilities that - along with the accompanying data collector - help with spotting performance issues and general problems. The agent also exposes JMX data to conventional monitoring systems. Platforms (more or less) supported out of the box include: JBoss 4/5/6/7, Wildfly 8, Tomcat 6/7/8, Jetty 6/7/8/9, Websphere, Weblogic, GlassFish 4.0, WSO2 ESB, Mule ESB, and Jasig CAS. There is also dedicated support for the popular Java libraries Spring, Quartz, CXF, and Axis 1.x. The agent should run on most other platforms with limited functionalities (that is, lack of support for platform-specific features). It works with JDK6, JDK7, and JDK8. JDK5 support is also possible after preprocessing the agent binary with retrotranslator. Functionality can be easily added by implementing simple BSH scripts.
g7ctrl is a daemon and a command shell that are used together with the Xtreme GM7 GPS tracker to help simplify its management and to make it possible to monitor alerts sent by the tracker. It is designed to run in the background and can be used to both receive location updates from a remote tracker and configure a tracker over USB. All received events are stored in a database and can be exported to GPX, KML, and CSV, with distances calculated. It can also execute action scripts upon receiving specific events or generate mail notifications. Extensive reference documentation (HTML and PDF) and Unix man pages are provided.
Global Paths Matching is an implementation of the global paths graph matching algorithm proposed by Maue and Sanders in "Engineering Algorithms for Approximate Weighted Matching" (WEA'07). Given a graph G=(V,E), a matching M is a set of edges without common vertices, i.e. the graph G=(V,M) has a degree of at most one. The algorithm scans the edges in order of decreasing weight (or rating), constructing a collection of paths and even length cycles. These paths initially contain no edges. While scanning the edges, the set is extended by successively adding applicable edges, which are those connecting two endpoints of different paths or two endpoints of an odd length path. Optimal solutions/matchings are computed for each path and cycle using dynamic programming.