Developed programmes that apply genetic algorithms to blocks of code/circuits/ideas, instead of starting from a crude framework and building on top of that. Fascinating, logical, and apparently works. in Popular Science
Ward Cunningham, creator of the wiki, said the power of collaborative development has only just begun to be realized, and open-source software will continue to spur more collaboration and more innovation.
The GNU C compiler apparently still permits this, and the VC++ 2005 compiler permits it too, though it issues a Level-4 warning if it’s C code, and a Level-2 warning if it’s C++ code.
blog entry about static code analyzers such as Checkstyle, PMD, FindBugs etc. and focuses on some of the issues that they spot in code. (PDM is great also for C++)
Target the parts of your applications that take the most time, by Martyn Honeyford "Improving the performance of your applications is rarely a wasted effort, but it's not always clear which functions the program is spending most of its execution time on. Learn how to pinpoint performance bottlenecks using gprof for both user-space and system calls on Linux®."
by Steven M. LaValle. Presents a unified treatment of many different kinds of planning algorithms. The subject lies at the crossroads between robotics, control theory, artificial intelligence, algorithms, and computer graphics.