Should have committed earlier

Lots of changes:
- Article about IPC
- New TUWF release
- New ncdu release
- Atom feeds for the bug tracker
- Bug tracker switch to sqlite

dat/dump-insbench

@@ -20,7 +20,7 @@ precise). My goal wasn't to benchmark the performance of different
 implementations, so I simply chose two implementations that I suspect are among
 the fastest. The vector implementation in the benchmarks is my own creation:
 L<vec.h|http://g.blicky.net/globster.git/tree/src/util/vec.h?id=2c11d2a> from
-the L<Globster|http://dev.yorhel.nl/globster> code base.
+the L<Globster|https://dev.yorhel.nl/globster> code base.
 
 B<Source code:> L<ins-bench.c|http://p.blicky.net/r746e>
 
@@ -39,7 +39,7 @@ search. Actual performance will be thus be a bit worse, depending on whether
 the final application needs that binary search or whether it can assume its
 input to be already sorted.
 
-L<[img graph insbench-bench-thumb.png ]|http://dev.yorhel.nl/img/insbench-bench.png>
+L<[img graph insbench-bench-thumb.png ]|https://dev.yorhel.nl/img/insbench-bench.png>
 
 Gnuplot script: (The awk(ward) part can likely be done natively in gnuplot as
 well, but I was too lazy to figure out how)
@@ -63,7 +63,7 @@ be a more accurate simulation of some real-world applications. This time I'm
 not cheating with the vector implementation, a binary search is performed in
 order to insert the items in the correct location.
 
-L<[img graph insbench-rand-thumb.png ]|http://dev.yorhel.nl/img/insbench-rand.png>
+L<[img graph insbench-rand-thumb.png ]|https://dev.yorhel.nl/img/insbench-rand.png>
 
   set terminal png size 1000, 1500
   set output "bench-rand.png"