Wednesday, January 03, 2018

Book review: Algorithms to live by

https://www.amazon.com/Algorithms-Live-Computer-Science-Decisions/dp/1627790365 Algorithms to Live By: The Computer Science of Human Decisions is a book that puts together the domains of computer science and real life. The ensemble of topics being touched is wide. The book treats deterministic algorithms such as optimal sorting, but then moves on to more context-dependent strategies for caching and scheduling. The last chapter even get to model identification, (tractable and intractable-made-tractable) optimization problems, stochastic algorithms and game theory.

All the while, computer science concepts are compared to conscious and unconscious human processes. For example, caching and the memory hierarchy have great parallels with how the human brain recollects memories of recent events, and how we can augment our brain with external, slower supports like paper. Scheduling is useful not only to allocate processes on CPU cores, but also to make an explicit choice of strategy when prioritizing the tasks that you or your team face. Up to the more extreme examples of game theory and mechanism design, when the incentive system becomes more important than the individual agents (manage the system, not the people rings a bell?)

If you like viewing the world throughout the lens of algorithms and see how the strategies of humans and computer compare with each other, I would strongly recommend this book as it will make for an entertaining read and some principles to take away for real life usage (I hope sorting socks will be easier now). Skip it if you have a very wide knowledge of computer science, operations research, Nash equilibria... but even if I was familiar with the technical part, I was missing the connection to different domains or everyday, real world problems. I listened to the audiobook version, which lasts about 12 hours. You may find it easier to skim through some chapters if you are more (or less) interested in some topics. The problem with audiobooks is that I can't easily take notes, while highlighting on an e-book reader is quick and lets me recollect all important gotchas later into a text file.

New role: Software Engineer in Tools and Infrastructure

After working on eLife's testing and deployment infrastructure in 2016, in the last year my responsibilities in the technical team have shifted towards the domain of engineering productivity. Testing is one phase of the development process that is often a bottleneck, but there are many more areas like code reviews, monitoring and infrastructure itself (being it servers or services):
In summary, the work done by the SETs naturally progressed from supporting only product testing efforts to include supporting product development efforts as well. Their role now encompassed a much broader Engineering Productivity agenda. -- Ari Shamash on the Google Testing Blog
Moreover, the team starts from a high level of coverage and design on many projects, to the point that my focus has always been on the provisioning and automation of testing environments, and on large-scale end2end testing.

What seems just a letter on a job title (from SET to SETI) is in fact an alignment of responsibilities so that I am not accidentally mistaken for "the QA guy" but always seen as a problem solver instead.
https://en.wikipedia.org/wiki/Pulp_Fiction
Solving problems and propagating the solution, so that you don't have to solve them over and over again
Roles are always an approximation in a team of generalizing specialist that also distributes and collaborate on some roles such as that of architecture. But it's helpful in a cross-functional team to have someone dedicated to the task of productivity, whether it is reached through automation, tooling, or continuous improvement.

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