Every developer must understand two things: Architecture design is necessary.
Other programs in the suite include demonstration clients usable as code models and various diagnostic tools. GPSD is widely deployed on laptops, smartphones, and autonomous vehicles including self-driving automobiles and robot submarines.
It features in embedded systems used for navigation, precision agriculture, location-sensitive scientific telemetry, and network time service. It's even used in the Identification-Friend-or-Foe system of armored fighting vehicles including the M1 "Abrams"main battle tank.
The core team has been stable at about three developers, with semi-regular contributions from about two dozen more and the usual one-off patches from hundreds of others. GPSD has historically had an exceptionally low defect rate, as measured both by auditing tools such as splint, valgrind, and Coverity and by the incidence of bug reports on its tracker and elsewhere.
This did not come about by accident; the project has been very aggressive about incorporating technology for automated testing, and that effort has paid off handsomely.
GPSD is sufficiently good at what it does that it has coopted or effectively wiped out all of its approximate predecessors and at least one direct attempt to compete with it.
By the time you finish this chapter you should understand why. See [ Ray ] for a detailed discussion; in particular, you'll learn there about the vagaries of NMEA the sort-of standard for GPS reporting packets and the messy pile of poorly documented vendor protocols that compete with it.
If applications had to handle all this complexity themselves the result would be huge amounts of brittle and duplicative code, leading to high rates of user-visible defects and constant problems as hardware gradually mutated out from under the applications. GPSD isolates location-aware applications from hardware interface details by knowing about all the protocols itself at time of writing we support about 20 different onesmanaging serial and USB devices so the applications don't have to, and reporting sensor payload information in a simple device-independent JSON format.
GPSD further simplifies life by providing client libraries so client applications need not even know about that reporting format. Instead, getting sensor information becomes a simple procedure call.
The GPSD developers cooperate closely with the ntpd project in improving the network time service. We are presently mid working on completing support for the AIS network of marine navigational receivers.
In the future, we expect to support new kinds of location-aware sensors—such as receivers for second-generation aircraft transponders—as protocol documentation and test devices become available.
To sum up, the single most important theme in GPSD's design is hiding all the device-dependent ugliness behind a simple client interface talking to a zero-configuration service.
Thus, the API exposed to clients can remain the same even as the protocol grows new features for new sensor types. Other programs in the suite include a utility for low-level device monitoring gpsmona profiler that produces reports on error statistics and device timing gpsprofa utility for tweaking device settings gpsctland a program for batch-converting sensor logs into readable JSON gpsdecode.
Together, they help technically savvy users look as deeply into the operation of the attached sensors as they care to. Of course, these tools also help GPSD's own developers verify the correct operation of gpsd.
The single most important test tool is gpsfake, a test harness for gpsd which can connect it to any number of sensor logs as though they were live devices. With gpsfake, we can re-run a sensor log shipped with a bug report to reproduce specific problems.
One of the most important lessons we think we have for future projects is that it is not enough for a software suite to be correct, it should also be able to demonstrate its own correctness.
We have found that when this goal is pursued properly it is not a hair shirt but rather a pair of wings—the time we've take to write test harnesses and regression tests has paid for itself many times over in the freedom it gives us to modify code without fearing that we are wreaking subtle havoc on existing functionality.
The Software Layers There is a lot more going on inside GPSD than the "plug a sensor in and it just works" experience might lead people to assume. We'll describe these from the bottom up. Software layers The drivers are essentially user-space device drivers for each kind of sensor chipset we support.
The key entry points are methods to parse a data packet into time-position-velocity or status information, change its mode or baud rate, probe for device subtype, etc. Auxiliary methods may support driver control operations, such as changing the serial speed of the device.At Microsoft Ignite, one of the announcements was for Azure SQL Database Hyperscale, which was made available in public preview October 1st, in 12 different Azure regions.
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The CWE/SANS Top 25 Most Dangerous Software Errors is a list of the most widespread and critical errors that can lead to serious vulnerabilities in software. Azure Application Architecture Guide This guide presents a structured approach for designing applications on Azure that are scalable, resilient, and highly available.
It is based on proven practices that we have learned from customer engagements.