Nicely organized list of competencies.

Very thoughtful note on programming language syntax: what's important for readability, expressiveness, redundancy, etc. "Suffice to say, syntax matters."

Hash tables that are deterministic across application invocations can make an application vulnerable to maliciously chosen inputs that evoke the hashing algorithm's worst case behavior (e.g., falling back to linear probing). So, maybe, don't do that.

A variety of ways in which you can be awesome during an interview.

"You are given an n-sided die where side i has probability pi of being rolled. What is the most efficient data structure for simulating rolls of the die?" A well-written exposition leading up to a very efficient algorithm/data-structure.

"You see, Feature Toggling is not just a different way to achieve feature branching. It is an architectural choice that, sure, helps with maintaining mainline development but the power is that it hands back control of what features should be enabled and when to the business. And it is there, ready for you to harness. No extra steps required. As awesome as Git is, you just cannot compete with something that allows you to not only control what features go into a release but what features are live at any one time."

Branch by abstraction, some discussion about feature toggles and other alternatives.

Another write-up of BBA. Slightly more direct; includes some discussions of DVCS and the BBA model. Also comparison to feature switches and other things.

For doing big changes, introduce a layer of abstraction, swap-out the lower layers incrementally. Some nice pictures, and updates over time.

By Debasish Ghosh · Justin Sheehy · Kresten Krab Thorup · Steve Vinoski.
"In this
paper, we first present a history of programming languages
and distributed systems, and then explore several alternative
languages along with modern systems built using them. We
focus on language and application features, how problems of
distribution are addressed, concurrency issues, code brevity,
extensibility, and maintenance concerns."

Focus on solving the problems with learning programming. Spaced-repetition plus some nice heuristics for when to add facts and how to gain more knowledge. Tim Ferriss would be proud. /via reddit

RT @maggadora: On how to make good sw projects and not to try saving the one that are lost

A somewhat long discussion of the Y combinator, but pretty readable, especially if one thinks back to 6.001. However, it does pop back and forth between lazy and strict evaluation, which I think may be more confusing than not to someone who doesn't know what that is.

An excellent exposition of bottom types and why you might like to have them in your type system.

Fabulous exposition of Monads, with detailed examples in Scala.

"Pick up the source code for a program and three highlighter markers, one green, one yellow, and one red. Go through the source. If you don’t understand what something does, mark it in red. If you understand it, but it has everything to do with the accidental difficulty of the implementation and nothing to do with the inherent difficulty of the problem, mark it in yellow. And finally, if something seems to express the problem and its solution fairly directly in an manner you understand, mark it in green."

Lots of useful portable sh tricks

Lessons and more for how to teach computer science concepts without a computer.

Great overview of typing. Equates the need for TDD with dynamic types.

Ah, the power of Old Spice, er I mean, JDK 7.

Lots of code and detailed examples.

Passion yes, coding in spare time no.

Thinking about programming and how to prioritize things like functionality versus maintainability versus elegance.

This is, I think, the full text of the ORA book. Looks like definitely worth reading.

An open-source framework, hosted at github, based on Ruby, for developing cross-mobile platform apps.

Teaching non-programmers the best practices of programming.
A proposal for revamping an existing course into a specific problem-driven one.

Jeff Dean says, "Do your back of the envelope calculations." "Don't prematurely scale." And more.

"Cappuccino is an open source application framework for developing applications that look and feel like the desktop software users are familiar with." Runs on JavaScript, and you write code in something called Objective-J which looks like Objective-C. Sometimes it is scary what you can do in JS.

If you're not in computer science, you typically receive no training in how to write good programs--part science, part art, part engineering. This blog has many posts about what you want to think about in terms of developing good code. Probably takes a bit more work up front but will pay off for your science in the long run.

What one person thinks you need to get productive pair-programming coders. Looks like a good list to me.

Nice detailed write-up on canonical pthread usage.

A stack-based language (with variables) designed to write (complex) programs in the fewest number of characters. Basically, all functions are a single ascii character.

List of tiny programming languages (e.g., small runtimes, tiny compilers, etc.)

'These pages are a record of the in-class discussions for the graduate class "Advanced Functional Programming" given at Harvard University in the Fall of 2006.' - seem largely Haskell focused, but maybe the cool part is the reading list and exercises.

Defines "lenses" that go from one data format to another. Based on a subset of OCaml.

Instead of continuation passing, nested lambdas?

From Object Computing, Inc. - Java News Brief - March 2009, by R. Mark Volkmann. A single-page, rapid in-depth overview of Clojure. Language features, code snippets, etc.

(Yet another) new programming language, aiming to be clean and explore ideas related to mixins. JIT-based (for x86, x86_64), should integrate well with C. Based on Lua VM.

By designer of C++ STL, most notably for me so far, a set of very detailed notes on programming (in C++) and the kinds of pitfalls, etc ... deals somewhat with types and mapping abstractions with underlying mathematical/algebraic concepts, impact of implementation on performance, ...

Code review tool from Google! Compare to ReviewBoard. Appears to provide also a public service (codereview.appspot.com).

Common problems and potential workarounds when running make in parallel.

Lots of examples on why it's good but how it can cause trouble if you're not careful.

Notes on how to learn how to build a compiler!

April 2006 comparison of various VCS systems (git, mercurial, monotone, darcs).

A set of Xen-hosted machines with step-by-step puzzles/instructions for learning basic techniques of the hacker world.

10 things done in OS X to improve performance: filesystem optimizations mostly for better file location, read-ahead, caching, etc. Includes list of useful OS X debugging tools for developers.

Links to docs about major programmable web technologies (AJAX, SOAP, REST, etc.)
Main website also has blog and database of mashups.

Python based packet assembly and dissection toolkit

A complete look at how Skype protects itself and how to defeat those protections. Concludes with a view of how you can turn Skype into your very own bot-net, probing proxy.

A Django/Rails debate in Chicago.

Use special calls for I/O to effectively 'yield' to a different "thread".

python implemention of delicious API