Robert Love Quotes

A good engineering interview will include some set of difficult problems to solve. It might even require that the candidate write a short program. In addition, it will test the candidate's knowledge of the tools she uses in great depth.

Learn when and how to use different data structures and their algorithms in your own code. This is harder as a student, as the problem assignments you'll work through just won't impart this knowledge. That's fine.

Beyond basic mathematical aptitude, the difference between good programmers and great programmers is verbal ability.

I grew up as a computer scientist, and I've always been fascinated by algorithms.

C++ is designed to allow you to express ideas, but if you don't have ideas or don't have any clue about how to express them, C++ doesn't offer much help.

I think everyone should get a little exposure to computer science because it really forces you to think in a slightly different way, and it's a skill that you can apply in life in general, whether you end up in computer science or not.

It would've been amazing [to work as programmer]. You're good at numbers, you're good with people, you like to wear shorts in the summertime.

When somebody has learned how to program a computer ... You're joining a group of people who can do incredible things. They can make the computer do anything they can imagine.

Pretty much, you point to a problem and good reasoning about why people are doing what they are doing and what constraints they face in terms of how others will behave, and you're looking at a problem that could be improved upon by game-theoretic reasoning.

An approximate answer to the right problem is worth a good deal more than an exact answer to an approximate problem.

I was always pretty good at designing things.

What good does it do to be afraid? It doesn't help anything. You better try and figure out what's happening and correct it.

In my daily work, I work on very large, complex, distributed systems built out of many Python modules and packages. The focus is very similar to what you find, for example, in Java and, in general, in systems programming languages.

I'm a great coder. But I am not pushing that so much anymore because there are thousands of great coders.

Clearly, programming courses should teach methods of design and construction, and the selected examples should be such that a gradual development can be nicely demonstrated.

There are ways that women absorb situations, and I think women are different kinds of listeners. They're different in terms of how they parse out problem solving.

We just think it's important that everybody have some technical training and background. Even though not everybody is coding but even our deals team and our designers all have GitHub accounts and they go into the code base.

To solve the Cube, you need special skills and understanding. For example, pattern recognition is very important to solve the Cube.

It's something special being able to build a program up.

Even if you're going into a field that has nothing to do with computer science, just having that way of analytical thinking and being able to process information and break it down is important no matter what you're doing. Having that knowledge of code is something that you can apply to your daily life.

Everyone on the founding team ought to invest the time in a coding bootcamp.

During the process of stepwise refinement, a notation which is natural to the problem in hand should be used as long as possible.

[Computer science] is not really about computers and it's not about computers in the same sense that physics is not really about particle accelerators, and biology is not about microscopes and Petri dishes... and geometry isn't really about using surveying instruments.

I think that great programming is not all that dissimilar to great art. Once you start thinking in concepts of programming it makes you a better person...as does learning a foreign language, as does learning math, as does learning how to read.

I will, in fact, claim that the difference between a bad programmer and a good one is whether he considers his code or his data structures more important. Bad programmers worry about the code. Good programmers worry about data structures and their relationships.