Disclaimers: I received a free copy of this book to review from O’Reilly. I work at Google, as do the authors, but this review reflects my views only and not necessarily those of Google.
One thing I have learned over my three years of professional software development is that you really are writing code for other people to read, not for the compiler. This dual nature of programming, the precise, exacting specifications that run on the computer, and the imprecise, ambiguous human factor, is fascinating to me. Ben Collins-Sussman and Brian W. Fitzpatrick, two of the engineers behind the SVN version control system, currently working at Google, have written Team Geek, a book that aims to impart lessons learned in creating better software through better people skills and teamwork.
Programmers tend to lionize the lone programmer, like Linus Torvalds of Linux fame. In some rare cases, geniuses do manage to accomplish incredible things on their own. But in most cases, great software is a collaborative effort performed by a team of people of varying skills, backgrounds, and communication styles. There are many books which help improve your technical proficiency, but this is one of the few I’ve encountered that addresses the importance of working effectively with teammates.
I won’t reiterate all of the content of the book but there are a few themes that occur throughout that I’d like to touch on.
The first is that it is crucial to spread the knowledge throughout the team rather than keeping it siloed in the heads of a few people. They whimsically refer to this as the “bus factor” – how many people would it take to be hit by a bus (or be otherwise incapacitated) before the project would fall apart?
One way of increasing this shared knowledge is through the use of communication channels that are easily archivable and searchable rather than through point to point communication. For instance, it is better to ask questions of the team via an IRC channel or mailing list than to ask someone directly, because that exchange can be easily found in the future. It also gives other team members visibility and input into the decision making process.
The culture of the team is also frequently discussed. In the previous example, archiving technical discussions would do no good if no one bothers to search and try to find answers by themselves prior to asking someone for the answer. The shared values of the team are crucial to its effectiveness.
Another main theme of the book is focus, or “saying no to all the distractions.” Part of an effective team, the authors say, is a manager who can shield engineers from the chaos inherent in the organization. This is a form of avoiding distractions at a high level – working on things which do not actually matter for your project. One relevant quote I’ve found in this regard is
There is nothing so useless as doing efficiently that which should not be done at all — Peter Drucker
One way the authors suggest to maintain focus is to decide on a mission statement. It might sound cheesy, but they offer a compelling argument as to its efficacy. They relate an example of how they used this technique on one of their projects and it became clear that many of the senior engineers had very different goals and ideas of what the product should do. Had they not forced the team to clearly specify what they were trying to accomplish and what the non-goals of the project were, there would have been significant wasted effort by people working at cross purposes. They use the analogy of a cart being pulled by different team members in different directions – by not working towards one goal, the cart will not move forward as quickly as it would if all were pulling together.
At a lower level, distractions abound as well. While programming, it takes significant concentration and effort to get engrossed in the task at hand and to ‘load’ the program structure into one’s head. Context switching is very bad for productivity because the cost of reloading this state is so high. Sometimes these context-switching distractions come from other team members, such as when someone interrupts to ask a question. The authors suggest that the team come up with a strategy for minimizing these disruptions, both to increase productivity and decrease frustration. For instance, in one team the authors led, any time Alice needs something from Bob, Alice would make her presence known, Bob would verbally acknowledge Bob but not stop what he was doing, finish what he was doing, and only then stop and talk to B.
While much of the book is generalizable to any sort of team environment, the authors do give some coding specific advice. There are discussions on handling code reviews effectively, dealing with people who constantly dig their heels in and criticize others’ technical solutions, and ways to avoid ego while coding.
I thoroughly enjoyed this book, reading it cover to cover over two legs of an international flight. Much of the advice in the book is common sense but there are also many specific, concrete ideas that I had never considered before. I would recommend this book without reservation to anyone working on a team that writes software.
Very interesting article on techniques for simplifying 3d surfaces, including an interactive WebGL demo comparing the various techniques. Simplifying 3d surfaces is important for maintaining frame rate in interactive applications when objects are far away; it is a way of managing level of detail in an automated fashion.
To briefly recap, our goal is to render large volumetric environments. For the sake of both efficiency and image quality, we want to introduce some form of level of detail simplification for distant geometry. Last time, we discussed two general approaches to level of detail — surface and volumetric — focusing primarily on the former. Though volumetric terrain is not exactly the same as height-map based terrain, we can draw an imperfect analogy between these two problems and the two most popular techniques for 2D terrain rendering: ROAM and geometry clipmaps.
ROAM vs. Clip Maps
ROAM, or Realtime Optimally Adapting Meshes, is in many ways the height-field equivalent of surface based simplification. In fact, ROAM is secretly just the simplification envelopes algorithm applied to large regular grids! For any viewing configuration and triangle budget, ROAM computes an optimally simplified mesh in this sense. This…
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