技術選型

新技術不斷地冒出,這意味著機會並伴隨著風險,如何評估是否採用呢?

Hype Driven Development: https://blog.daftcode.pl/hype-driven-development-3469fc2e9b22

Good practices

So if we can’t rely on what the internet says and opinions of other people, then how to make clever decisions? Here come some good practises:

Test and research before you decide:

Spikes — learn about your technology not from blogs, but from experience. Take 1 or 2 days to build a prototype of a new functionality in the new technology, before you make the decision. Let the team analyse pros and cons. You might take a couple of competitive technologies and let different parts of the team builds prototypes with different technology.

Hackathon is a great way to build awareness of a team on tradeoffs of different technologies. Take 1 or 2 days for the whole team to hack all the technologies that are on the rise and look tempting to use. That will allow the team to make clever decisions on its own and take decisions based on their own experience.

When to go?

In principle when the return on investment is huge. Most technologies are created to solve a particular problem. Do you have that problem? Is it a big problem? Will it save a lot of time? Will the use of the technology pay back the cost of the entrance curve and rewriting? What if we initially slow down development by the factor of two? Or four? Is it still worth it?

Great teams are allowed more — some teams are just faster than others at delivering the value. They get bored with what they do more easily. These teams can introduce new technologies more often. That’s no excuse not to use spikes and do hackathons. On the other hand, if the team has troubles delivering — proceed with caution.

Hire the right people:

Strong technical background is your friend — people who know different paradigms, understand the theory of programming (e.g. algorithms, concurrency) and have good engineering culture tend to hype less.

Experience — hype is stronger with young developers. With years people who have seen many technologies and been in troubles many times tend to get more balanced views of picking technology.

程式語言編年史

程式語言編年史原文 下面這張圖片描繪了整個程式語言的歷史。包括各種程式語言的發明人、程式語言的特點和適用領域、被什麼網站或公司使用等 (檢視 完整高清圖 )。 之所以會有那麼多不同的程式語言是因為設計程式語言的初衷不同、對語言學習曲線的追求不同、不同程式之間的執行成本差異...