reference request – What are some advanced background topics I’ll need for distributed systems and networks research?

I am a new graduate student in Computer Science who would like to be able to read and understand modern and new distributed systems research papers. My current background / courses and understanding is in the level of undergraduate and beginner graduate level courses in:

  • Networks (TCP/IP stack and applications)
  • Distributed Systems (Graduate level course with Time (logical/vector clocks), 2PC and 3PC, Multicast and membership, election, Consistency , Consensus and Quorums (Paxos), DHTs and Overlays and some modern applications like ZooKeeper etc)
  • Undergraduate Algorithms, Discrete Mathematics and Theory of Computation (basic DFA/NFA and intro to Turing Machines with no rigorous mathematics)

However, I find this background insufficient to read modern research in networks and distributed systems and in particular, I am not aware of modern protocols like QUIC and the formal methods mentioned in the papers which I believe include some sort of model checking and the likes. Also many of the topics I have mentioned above in distributed systems – I lack the background to verify and prove correctness of these protocols and even follow the proofs that they have given.

Any suggestions on a reading list that can prepare me to be in a position to understand modern research in this area would be very helpful.

How are scientific research projects planned? In particular computer science, but possibly there exists processes for all research?

Possibly some context:
Take any research endeavor. Finding a vaccine. Going to the moon. Clean energy. I don’t have a background in these scientific areas so picking one closer to home (Comp Sci) might be better. But the idea is how to battle the Unknowns? How to do it economically? How to make progress while not getting analysis paralysis?

Some might suggest a scrum, or an agile process try to solve these questions. I’m not certain that they address the same level or kinds of Unknowns.

Are there previous experiences that work, and those that don’t work? And why? The questions grows on the way forward through unknowns, and by definition the Unknown doesn’t exactly have a road map, and new context is developed regularly.

This maybe simply the question of the ‘meta’ variety: Is there research on comp sci research? If so does Comp Sci research have approaches or techniques that they rely on?

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at.algebraic topology – What is the current state of research in Chern-Simons theory?

I’m a PhD student in mathematical physics looking for some orientation. As asked in the title, I would like to know the current state of research in Chern-Simons theory. More specifically, what are some of the directions that people are currently pursuing in this field.

I did not ask for more general topological field theories, but this is largely due to personal interests. Of course, answers related to other TFTs are more than welcome.

I feel this question has been asked before. But since this is a question about the current state of research, I think it deserves an update.

Thank you very much.

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research – Should there be more square and round shaped buttons than there are at the moment in the main part of webpages and apps?

References regarding optimal and minimum contact area or touch target size on mobile devices (also similar question previously on UXSE here) suggest that the contact area should fit the rough size and contact point on a thumb.

Weighing up the pros and cons for a square or round shaped button or call-to-action, it doesn’t seem like there is enough square or round shaped buttons because of the amount of body text and length of characters used on labels and the typical way layouts are structured on webpages that focus a lot more on the width than height.

However, when we look at the proliferation of cards and tiles being used on many mobile apps and website home pages, it seems to suggest that they are more useful in certain types of contexts.

Also, in game interface designs where there is less emphasis on reading text (e.g. in dialogues) and more focus on interactions, buttons don’t tend to be rectangular shaped but have shapes that seem to be more fit for the purpose of optimizing the touch area.

With the more common use of voice-as-an-interface and also with more traffic now coming directly from mobile devices, is there any particular reason that there are not more square or round-shaped buttons on user interfaces? Is this a trend that we would expect to see more on the body of a webpage rather than just on the areas of the screen that are more condensed (e.g. menu headers and toolbars)?

user research – Best Practice for video start image

Personally, I don’t think you should always pick an image from the video. It actually depends on the situation.

I’ve got an example from my recent UX review: a product site with a short video, demonstrating product features, etc.

This video was surrounded with a text, describing the main product idea. And the start image for this video was a random image from the video itself, but, as we all know, picture worth a thousand words, so I suggested to get an refined image describing the main product idea and place it as video start image.

Now we have a text, an illustration for that text and a demo video combined together.

Another example is about an image from the movie itself. There is a local online tv-series streaming service which I use every day. It has a lot of titles, which are grouped by seasons and for every season there is a single page with all episodes. And every episode has a start image taken from the episode itself. It’s okey, until start image is a spoiler image, i.e. something I don’t really expect to see before I watch the epicode by myself!

From the other hand, at YouTube I wish to have a video starting image taking from the video itself so I can decide whatever it’s a right video to watch (there are a lot of music videos with a different video track, etc).

So, it actually depends on the situation.

"Are you sure?" Request for confirmation modal usability research

  1. A user is about to delete a crucial object with no undo.
  2. The designer puts an “Are you sure?” modal confirmation.
  3. The user says “Yeah yeah yeah do it”
  4. Immediately the user regrets his/her decision and panics.

Clearly Undo would be great. But sometimes that is impractical.


  • What public usability studies are there on this topic?
  • Do users REALLY think about the question or do they just click Yes without thinking?

Thank you.

machine learning – How to extract an open research question from text with Natural Language Processing?

Researchers often broadly state one or several research problems as an “open research question” or an “open research problem”, a “research gap” or “desideratum” or often make “suggestions for further research”. The same terms are used across disciplines. Some disciplines are referring to categories of research gaps like an “evidence gap” (commonly used in medical research). There are probably less than a dozen terms used to describe the same thing.

As long as you are dealing with quantitative research (from natural to social sciences) these open research questions are mostly asked or at least repeated in the “conclusion”, “future research” or “discussion” section of an article. There are a very limited number of phrases used to introduce a desideratum like “further research… (is needed to/will show etc.)…”, “it remains to be seen, if…”. One could prepare a quite comprehensive list of such phrases rather quickly. Often these phrases also signify the beginning of the statement, which should be helpful.

In other words, you know what keywords and phrases to look for and have a measure of relevance by there position in the document. Also many open research problems are directly phrased as a question.

There has to be an element of human curation (aided by further NLP analysis), since it will be difficult to extract the exact statement and the statement has to be validated as non-redundant and preferably categorized (if applicable as “evidence gap”, “method gap” “sample gap” etc.)

Assuming you have a database of full-text articles (most pre-print servers give full access to content and meta-data), others give you free access to metadata and scientometric data. What methods, algorithms and software solutions (open source or SaaS) would you use or test?

API’s of science repositories and the access they give: