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In order to spur users to action, I would put the solution directly in their face. Tell them about heartbleed (in a calm manner) and offer them the option to change the password immediately. Why ask them to navigate all the way to wherever they can reset their password when you can bring the form to them. Wait for them to log in, and give them a simple ...


What level of security required is not a UX question. Rather it is a threat modelling exercise that will tell you how much you should demand the user changes their password. Once you have determined the degree of risk then what do you want to drive? A rational decision based on the risks. Users can do that providing they are not confused. Examples below ...


We took the transparent approach and posted a notification inside our application for all administrators - we told them we WERE running the affected version of OpenSSL, we told them what we did, when we did it and why. We also told them there is no indication of anything untoward but due to the nature of Heartbleed this is expected though we did still spend ...


Alternative to alexeypegov suggestion is having a vertical list. Again, if you are showing less than 15 elements vertical list works. However, if the design had elements Scipion examples. You could pull off an amazing list comparator. What is the main goal for the user having to view the list comparator?


Since you have two lists and there is no information on which one is primary, I think that diff like this will work good: Pros: It shows both lists unmodified It shows resulting list It highlights items which are added It shows common part of the lists Cons: Three lists instead of one Colors could be tuned up to your needs (for example, you may ...


The classical way is a Venn diagram: (Source: Wikipedia) For quantification of set similarity/dissimilarity, you can look at Sørensen–Dice coefficient or Jaccard index. Their parameterization is the Tversky index.


What you describe seems a diff-like application. You could use a similar view, two columns and the matching items hightlighted. As for the similarity algorithm, if ListA is {A} and ListB is {A,B} lists would be 50% similar, then it could be: coincidences / (ListA length + ListB length + conincidences) * 100

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