timm commented 8 years ago

After review, relabel to 'reviewTwo'. After second review, relabel to 'EditorsComment'.

tomFr commented 8 years ago

Review template

Title of chapter

Learning lessons over lessons learnt: liftoff with continuous experimentation towards rapid value delivery

URL to the chapter

https://github.com/ds4se/chapters/blob/master/muench/Chapter_Muench.md

Message?

What is the chapter's clear and approachable take away message?

Continuous experimentation helps to develop a successful software product

Accessible?

Is the chapters written for a generalist audience (no excessive use of technical terminology) with a minimum of diagrams and references? How can it be made more accessible to generalist?

The chapter is accessible to a generalist audience with respect to the message that data science in the form of continuous experimentation is important to build a successful product. However, it stays at a very high level, which makes it difficult to have an actionable take away for the reader. What's missing a bit are more concrete examples or details. For instance, by providing some concrete details on experiments or hypotheses, or possibly by giving one example that is used to exemplify the idea behind the continuous experimentation, the reader could take a lot more away from it.

One minor comment I have is that the quote on "If we are not solving the right problem, the project fails." seems a bit out of place at the current location, maybe one paragraph up might be better.

Size?

Is the chapter the right length? Should anything missing be added? Can anything superfluous be removed (e.g. by deleting some section that does not work so well or by using less jargon, less formulae, lees diagrams, less references).? What are the aspects of the chapter that authors SHOULD change?

The chapter has the right length. I suggest cutting a bit of the problem / motivation section on "most ideas fail to show value" and instead provide more details later to make it more concrete, either with an example or some specific advice.

Gotta Mantra?

We encouraged (but did not require) the chapter title to be a mantra or something cute/catchy, i.e., some slogan reflecting best practice for data science for SE? If you have suggestion for a better title, please put them here.

Experiment continuously to avoid failing.

Best Points

What are the best points of the chapter that the authors should NOT change?

I think the idea is good, but being more concrete could make it much stronger and tie it better to "data science in SE".