I recently found out about the book Developer Testing – Building Quality Into Software by Alexander Tarlinder, and I immediately wanted to read it. Even though I am a developer at heart, I have always been interested in software testing (I even worked as a tester for two years).
I think the subject of the book, developer testing, is timely. There seems to be a broad trend where more and more responsibility for testing is given to developers. It follows from the move towards micro services, dev ops and the “you built it, you run it” principle. Another driving force is the prevalence of developer testing frameworks that started with JUnit and now includes many more. These frameworks encourage and help developers write automatic tests.
Despite this trend of increasing developer testing, my feeling is that many developers still don’t test their programs well enough. For example, they may test the “happy path”, but not the different error handling cases. That is why I was excited about this new book explicitly addressing developer testing. Continue reading
Last month we finished reading “The Effective Engineer” by Edmond Lau in the book club at work. It is a great book full of practical advice on how to get more done as a software developer. In fact, it is one of the three books I think all programmers would benefit from reading (the other two are Code Complete and The Pragmatic Programmer).
In the book club at work, we recently finished reading Release It! by Michael T. Nygard. It is a book I have been meaning to read for a long time, but somehow I never got around to it until now. It was written in 2007, and it is starting to show its age in several respects. Despite this, there is still a lot of relevant advice on how to make software work well in production.
I finally got around to reading Clean Code by Robert C. Martin (Uncle Bob). It is often high on lists of the best books for software development, and for good reason. Clean Code is an excellent book that all programmers should read. Here is what I liked and didn’t like about it. Continue reading
I recently finished the Coursera course Computational Investing Part 1 by professor Tucker Balch at Georgia Tech. The focus of the course is on portfolio analysis and selection. Almost all the analysis uses the daily closing prices of stocks as the starting point. The concepts are not particularly difficult, and the programming exercises give you good hands-on experience with the different analysis techniques. The assignments are in Python using several tool kits for time series analysis (NumPy, Pandas and the QuantSoftware ToolKit). Continue reading
I recently finished the Coursera course Algorithms: Design and Analysis, Part 2 by Professor Tim Roughgarden of Stanford. I’ve already reviewed part 1, and here are my thoughts on the second part.
The main theme of part 1 was the divide and conquer paradigm. In the second part the main themes were greedy algorithms, dynamic programming and NP-Complete problems. The lectures were excellent, with clear and easy to follow algorithm development and proofs. At six weeks, it was one week longer than part 1, and I found it quite a bit harder than part 1. Here’s more on each part. Continue reading
When I found out about the book “How Google Tests Software“, it didn’t take long until I had ordered a copy. I find it quite fascinating to read about how Google does things, whether it is about their development process, their infrastructure, their hiring process, or, in this case, how they test their software. I am a developer at heart, but I have worked for a few years as a tester, so testing is also dear to me.
It’s quite an interesting book, and it makes some great points about the future of testing. However, despite the phrase “Help me test like Google” on the cover, it is not as useful as I had hoped when it comes to improving your own testing. Continue reading