Link to more resources on learning how to program.

diff --git a/examples/step-1/doc/intro.dox b/examples/step-1/doc/intro.dox
index 8e6414f3b3a1f9df0685348a8620bdb8294a0a2a..1f1e353ddd3c2abf2f822e91a895801f546674ce 100644 (file)
--- a/examples/step-1/doc/intro.dox
+++ b/examples/step-1/doc/intro.dox
@@ -176,11 +176,11 @@ that we typically train mathematicians, engineers, or scientists in but that
 is important when you start writing software of more than a few hundred
 lines. Remember: Producing software is not the same as just writing code.
 
-To make your life easier on this journey let us point to three resources that
+To make your life easier on this journey let us point to some resources that
 are worthwhile browsing through before you start any large-scale programming:
 
-- <a href="https://github.com/dealii/dealii/wiki/Frequently-Asked-Questions">
-  The deal.II FAQ</a> has a good number of answers to questions about
+- The <a href="https://github.com/dealii/dealii/wiki/Frequently-Asked-Questions">
+  deal.II FAQ</a> has a good number of answers to questions about
   particular aspects of deal.II, but also to more general questions such as "How
   do I debug scientific computing codes?" or "Can I train myself to write code
   that has fewer bugs?".
@@ -191,6 +191,16 @@ are worthwhile browsing through before you start any large-scale programming:
   specifically written for scientists and engineers, not for computer
   scientists, and has a focus on short, practical lessons.
 
+- The <a href="https://bssw.io/">Better Scientific Software
+  project</a> has a lot of resources (and interesting blog posts) that
+  cover many aspects of writing scientific software.
+
+- The <a href="https://ideas-productivity.org/">IDEAS
+  project</a> also has resources on software development, in
+  particular for parallel computing. In the "Events" section on
+  that site are recorded tutorials and webinars that cover many
+  interesting topics.
+
 - An article on <a href="http://arxiv.org/abs/1210.0530">Best
   Practices for Scientific Computing</a> that gives an introduction to
   many of the ways by which you can make sure you are an efficient