Tools that can help with Identity Management:
Almost any web application would require a user to sign in so that the application can know and keep track of the activities taken by the user. When the users are in the range of hundreds of millions, identity becomes important software in itself. As software engineers take care of maintaining the code base and the processes associated with the release of improvements to the software, they will frequently rely on tools and tests.  The following are some of the tools that can help with this tremendous responsibility.
First, a web application such as this will rely heavily on backend services that may work exclusively for specific purposes such as phone contact information lookup, address information lookup, authentication and auditing, utilities such as issuing tokens for logged in users and many others. Each of these services may also be hosted in different environments that are used to prepare and test the code prior to its release to production. Consequently, these services could very well be counted as a dependency for the software. In order that we keep track of the dependencies and for troubleshooting issues with the software, we could consider command line tools that enable Application Programming Interface (API) calls to the service alone. These tools help use the service in isolation while also provide a command line convenience to gain information on individual resources such as an account or a number lookup. While curl – a popular command line tool can be used to call services via APIs hosted over the HTTPS, most enterprise services are secured and some of these APIs often require a pre-amble where one api called before another.  These tools can come in helpful for this purpose. These tools come in helpful for triage and to work in isolation from the tests and code. Moreover these tools are for the convenience of getting data or setting state and not for operations or monitoring which generally have their own infrastructure based on impact radius.
Second, the entire software consuming the dependencies regardless of its organization may also be considered a service with its own APIs. Writing command line convenience tools to drive this software with an api or a sequence of apis can become very useful for diagnostics and automation. Consider the possibility of writing automations with scripts that are not restricted to writing and testing code. Automation has its own benefits but not having to resort to code widens the audience. Along the lines of automation, we mentioned convenience but we could also site security and policy enforcement.  Since the tools are designed to run independently and with very little encumbrance, they can participate in workflows previous unimagined with existing codebase and processes.
Conclusion: While testing and coding are primary activities for software development in any organization, they can be improved with empowering the individuals who are engaged in these activities. These tools help fill this gap.

#codingexercise

We were discussing finding closest numbers between the elements of three sorted integer arrays. 

Another usage of finding the closest numbers in these arrays to a given input value is to discover overlapping range of sorted numbers. In order to do this on number line, we could choose max(start1,start2,start3) and min(end1,end2,end3) for (start,end) pair for every array. But by finding the closest of the min and max values, we can determine the overlapping range projection on any one of three arrays. Then we can choose the projection with the smallest number of elements 

Determining the overlapping region projections helps shrink the search space for any operations involving all three arrays. It may not be useful for sum, average, mode or median but it is helpful for partitioning the number line to determine the presence of a number in any array. If the number is not in the overlapping range then we exclude one of the arrays and binary search for it outside the projections in other two arrays.

Separation of range helps not only for looking up a number but also in performing similar operations on the overlapping projections in each array. For example, finding the average of  projections just got a whole lot more easier and accurate. And if the numbers are all positive, their product also became easier to approximate.

We continue discussing the personal coder. The personal coder can also become the personal recommender.The recommender is a personal advisor who can use intelligent correlation algorithms. For example, it can perform collaborative filtering using the owner's friends as data point. In this technique, the algorithm finds people with tastes similar to the owner and evaluates a list to determine the collective rank of items. While standard collaborative filtering uses viewpoints from a distributed data set, the recommender may adapt it to include only the owner's friends. 
 The recommender might get geographical location of the user, the time of the day and search terms from the owner. These are helpful to predict the activity the owner may take. The recommender does not need to rebuild the activity log for the owner but it can perform correlations for the window it operates on. If it helps to build the activity log for year to date, then the correlation can become easier by translating to queries and data mining over the activity log. The recommender does not have to take any actions. Whether the owner chooses to act on the recommendations or publish it on Facebook is entirely her choice. This feedback loop may be appealing to her friends and their social engineering application and it is a choice for the friends to participate The recommender is also enabled to query trends and plot charts to analyze data in both spatial and temporal dimensions. It could list not only the top 5 in any category but also the items that remained in the top 5 week-after-week. These and such other aggregation and analysis techniques indicate tremendous opportunity for the recommender to draw the most appealing and intuitive information layer over any map.  A recommender can query many data sources over the web. For example, it can query credit card statements to find patterns in spending and use it to highlight related attractions in a new territory. Wouldn’t it be helpful to have our login pull up restaurants that match our eating habits instead of cluttering up the map with all those in the area? Similarly, wouldn't it be helpful to use our social graph to annotate venues that our friends visited? The recommender may be uniquely positioned to tie in a breadth of resources from public and private data sources. Many web applications such as del.icio.us and Kayak make data available for browsing and searching.  

#codingexercise

We were discussing finding closest numbers between the elements of three sorted integer arrays. 

Another usage of finding the closest numbers in these arrays to a given input value is to discover overlapping range of sorted numbers. In order to do this on number line, we could choose max(start1,start2,start3) and min(end1,end2,end3) for (start,end) pair for every array. But by finding the closest of the min and max values, we can determine the overlapping range projection on any one of three arrays. Then we can choose the projection with the smallest number of elements 

Determining the overlapping region projections helps shrink the search space for any operations involving all three arrays. It may not be useful for sum, average, mode or median but it is helpful for partitioning the number line to determine the presence of a number in any array. If the number is not in the overlapping range then we exclude one of the arrays and binary search for it outside the projections in other two arrays.

We continue with our discussion of the personal coder. We browse our email inbox from any computer and kiosk. Interacting with our own personal assistant on any speech recognition medium may just be as easy to bring up as that. With the standardization of the protocol between a speech recognizing hardware and the personal assistant, the two can be separately and allowed to vary independently giving rise to the notion of personal assistant conjured up on the kiosk. 

The personal assistant can also improve human interactions with the help of emotions and feelings. Personal robots such  as the retail available Jibo already demonstrate this but we have cited a deeper and broader set of skills in our write-up so far. If the form and the functionality as described here can be combined, it will lead to pervasive use of the personal assistant. 

Personal assistant can not only be interactive, humorous and informative, it can also help with visualization and drawing with verbal commands using the help of a projector lamp and a wall. This capability is often touted in movies but not facilitated on the personal assistant device. 

Personal assistant might also be paired with a virtual reality handset so that the assistant and the owner can be following the same canvas. This helps the owner to share with the assistant for replay on the projector mentioned above. Both the projector and the canvas are specialized functions of the personal assistant and not necessarily something that needs to be taken out of a notebook or desktop. However, enabling a tracking device with the assistant improves a whole lot more possibilities other than the owner's commands.  

There are two advantages of having the personal assistant maintain an activity log: 

First, the personal assistant is uniquely positioned to be a trusted confidential passive associate 

Second, the collection of activities helps boost different traits and habits of the owner leading to positive lifestyles.  

Together the personal assistant and the owner might achieve singularity as man and machine increasing the impact that the individual makes. 

#codingexercise

We were discussing finding closest numbers between the elements of three sorted integer arrays. We don't have to sweep all three arrays if we need to determine the relative range of each array. We take the sentinel values of a given array and find its closest numbers in the other arrays. Then we compare the sentinels of the other arrays with the closest numbers found in that array. This gives us a comparison of how wide or narrow the other arrays are compared to one of them.It gives us an idea of the relative positioning of the arrays within each other whereas we could only tell their position on the number line with the sentinels. 

Another usage of finding the closest numbers in these arrays to a given input value is to discover overlapping range of sorted numbers. In order to do this on number line, we could choose max(start1,start2,start3) and min(end1,end2,end3) for (start,end) pair for every array. But by finding the closest of the min and max values, we can determine the overlapping range projection on any one of three arrays. 
finally we can choose the projection with the smallest number of elements 

We continue with our discussion of the personal coder. Let us now consider the first differentiation. If the assistant is mobile, then it is likely to be classified a robot. The movement of the device is mostly with respect to an object. When we introduce motors and an ability to govern them by way of co-ordinate space, we are working with robotics. The assistant targets only the owner. It does not have to move around to translate commands into tasks. This is why we separate robotics from the capabilities an assistant has.
Second, the assistant is not an appliance but a software over an appliance. When an appliance collects and sends data over the internet, it can be considered an internet-of-things. In the case of an assistant, the data pertaining to the owner is maintained by the assistant and actively indexed and worked with. Moreover, the assistant need not be globally unique or have its own ipv6 address to do its job. This is where we differentiate from the lower level sensors and devices that are otherwise also connected to the internet.
There are two different kinds of pressure exerted in this middle layer for a "personal assistant". The pressure from the layer of IoT devices is that they can proliferate to include dedicated assistant responsibilities and may no longer require the owner to talk to one assistant only. This avoids having to relay commands and reduces the assistant from a being a single point of failure. At the same time, it makes it natural for the owner to turn to the function specific device and command in just the same way as they would an assistant for working with her data locally. This is also more intuitive for the user to know that a device by its function. Moreover, elaborate setup of applications and devices to the assistant is now avoided. In other words, the personal assistant has to remain smarter and differentiate from the device specific functions that they can specialize in. One way to do this is to provide more intelligent services over a unification platform for seamless experience, relay and consistency. If the assistant could treat these devices as plugins, the ecosystem for the assistant can grow better.
Similar arguments come from the mobile robot inclusive top layer where the assistant does not enter. The robot may assume the responsibilities of the "personal assistant" given the hardware and support it gets. Since it is mobile it is the equivalent of butler services for the customer. However, the digital assistant can continue to grow its presence by being more affordable and comprehensive in its support for taking commands from a robot as well. These kinds of improvements are easy to imbibe in the personal assistant while enjoying the power of cloud computing available on a voice activated command.
Another area of improvement in building the jargon for the personal assistant is to create associations with proper or common names for devices that are not necessarily on the internet. For example, it should be easy for the assistant to pair with a headphone over Bluetooth network and allow the user to listen to music on his headphone. The personal assistant merely has to recognize that the word headphone refers to a specific device that it can scan the Bluetooth network for and connect. Most desktop computers already have a hardware profile and can scan for hardware changes. They are also automatically able to download the necessary drivers to let the device function properly. In a way the personal assistant can become a headless desktop so long as the essence of communication continues to remain voice based. There is also a demarcation of concerns between the portable laptop and the portable personal assistant. One is general purpose computing and the other is merely customer facing. In a way, the personal assistant would benefit immensely to communicate with a desktop for all computing tasks.
Sometimes it is harder to ask if the desktop based computing is going to be demarcated from the personal assistant? The personal assistant is not the same as the desktop computer because it derives its value from being closest to the owner. It can be considered a frontend while the desktop may act as the backend. This connection between the desktop and the personal assistant is not just an extension from desktop computing but a protocol that spans different hardware, platforms and computing.
In its virtual form, a personal assistant may also be given any avatar. If we were to visualize the assistant it could be a photo frame on the desk that can show different personas as suited to the end user. By making the speech recognition software as thin as possible on the front end and backing it up with heavy duty cloud services, we can make the assistant appear differently at a time or a place.

#codingexercise

We were discussing finding closest numbers between the elements of three sorted integer arrays. We don't have to sweep all three arrays if we need to determine the relative range of each array. We take the sentinel values of a given array and find its closest numbers in the other arrays. Then we compare the sentinels of the other arrays with the closest numbers found in that array. This gives us a comparison of how wide or narrow the other arrays are compared to one of them.It gives us an idea of the relative positioning of the arrays within each other whereas we could only tell their position on the number line with the sentinels. 

We were discussing the personal coder here. In another extension of a similar idea, the assistant can also become the store for personal data – be it identity, images, video or documents. The notion that the assistant has an unlimited storage is equivalent to connecting cloud drives with the assistant to store and retrieve personal data. These include the ability to connect, save, extract, transform and load user data from a variety of stores and automatically back-up to the assistant's personal drive space for the user. 

Once we have a notion of a personal assistant, it is easy to view other roles suitable for it. For example automation in the cloud proceeds with the installation of an agent on any device even if they are cross platform or cross company. It may therefore be imagined that the assistant can also manage other devices within the premise. This is helpful to make the assistant as the point of contact for the user. 

The expansion of roles for the personal assistant leads us into robotics and computer vision space as well. From butlers to life savers, robots are popular in the imaginations presented in the movies. To some degree the addition of a simple camera on a standalone desktop personal assistant can be an improved capability rather than a voice activated assistant. We use face recognition for example with laptops to allow users to sign in. This works well as one of the options to sign in when there is sufficient visibility and light. It may not be sufficient for more complex image recognition algorithms such as Active Contour Model across images but the need to track movable objects is reduced when we have a stationary observer in addition to a listener. Moreover, the primary role of the assistant is in focusing on the owner rather than objects and other devices with which it can talk via programmability options as mentioned earlier 

There are essentially two points for consideration where we demarcate robots from assistants- the first is on the basis of whether the assistant is mobile or not. The second is whether the assistant is connected seamlessly to computing at cloud scale. In this way the assistant separates itself from robots as well as devices that claim to have connectivity via internet of things. The expansion of roles and the introduction of capabilities does not take away the identity of the assistant as someone responsible for the users' commands and their data. Eventually the need to carry a phone could be replaced with being able to summon an assistant at the nearest available device

We were discussing the argument for standard query operators here. Standard Query operators have an interesting attribute.  They are often used in Lambda expressions.  Lambda expressions are local functions that can be passed around and returned as any first-class objects of the programming world. Software developers love lambdas because it makes expressions of logic so much more fun and convenient.  They use it to create delegates and expression trees. The former treats logic as a data type and the latter represents logic in a tree like data structure where each node is an expression. Both can be compiled and run and even allow dynamic modification of executable code. 

When data is processed by logic written in lambdas they are predictable, consistent and free from resource onus. Considerations such as where the logic is deployed, how it is hosted, the topology of the resources and the chores that go with maintaining it are no longer weighing on the developer. Even the business owners appreciate when their logic is no longer held ransom to technology, infrastructure or vendors. Furthermore, with the organization or re-organization of code by way of delegates and expression trees in addition to and not excluding the well accepted object-oriented programming concepts, the business is now able to move swiftly to the market to deliver new and better proposals. 

It is also important to observe here that data technologies and processing are never in vacuum. They work within the parameters of their ecosystem by way of feedback cycle. Lambda expressions have lately demonstrated acceptance even in the cloud computing world in the form of serverless computing.  

In a database, the query optimizer something very similar to this. It decides the set of tree transformations that are applied to the abstract syntax tree after it has been annotated and bound. These transformations include  choosing join order, rewriting selects etc. It not only chooses the order in which the operations are applied but it also introduces new operators. Therefore it seems a good candidate for what we have described above. 

It’s important to note the distinction between database and serverless this way. One tries to push the computations as close to the data as possible while the other tried to distance the computations from the resources used. Traditionally databases have required to scale up at least for online processing while the alternatives have gone for scale out via batch oriented. Databases have required large memory and continued to take up as much memory as added. The alternatives have distributed the computations via  commodity servers 

#codingexercise

Yesterday we were given three sorted arrays and we wanted to find one element from each array such that they are closest to each other. One of the ways to do this was explained this way: We could also traverse all three arrays while keeping track of maximum and minimum difference encountered with the candidate set of three elements. We traverse by choosing one element at a time in any one array by incrementing the index of the array with the minimum value.

By advancing only the minimum element, we make sure the sweep is progressive and exhaustive.

We don't have to sweep for mode that spans all three arrays because we are guaranteed that the maximum and minimum difference between the three identical elements will be zero. For every such occurrence, we then count the number of identical elements in each array.

I was looking for a programmatic way to get authorization code to login with Amazon also called LWA. An authorization code is merely a first step in the authorization code grant as documented here: https://developer.amazon.com/docs/login-with-amazon/authorization-code-grant.html

However it seems the implementation for the OAuth is different from that for AWS or Alexa. When it is an OAuth for a device, the REST APIs are helpful to get  a code and a token. The implementation here is geared towards loading the Login With Amazon SDK. There is no denying that OAuth requires a user interface to accept the credentials from the user.
http://httpunit.sourceforge.net/doc/api/com/meterware/httpunit/WebResponse.html
 WebForm form = resp.getForms()[0];
 WebResponse response = form.submit();
 String atMainToken = response.getCookieValue("at-main");
at-main token is not the same as oa2.access_token but it helps especially if there is a utility for translation.
However, client interactions could also be tolerated in the absence of a user. While this may not be required from the RFC, it does provide a convenience. The client redirects the user to the authorization server with the following parameters response_type, client_id, redirect_uri, scope and state. When the authorization server is satisfied, the user is asked to login to the authorization server and approve the client, The user is then redirected to the redirect_uri along with code and state. This code can then be swapped for token by the client using the oauth endpoints.
The access token can be decoded and validated using the oauth endpoints. It can also be used to refresh the tokens. To get the access tokens, when we load the LWA SDK on a page, the page calling the SDK must be in the same domain as the redirect_uri specified. This would otherwise lead to cross domain origin and will not be allowed. Even if we set the Origin and Referer header fields with the help of an interceptor to overcome the CORS policy of the browser, the server may reject the request. Moreover, the page making the request with the Javascript SDK must be secured with https.

#codingexercise
Yesterday we were given three sorted arrays and we wanted to find one element from each array such that they are closest to each other. One of the ways to do this was explained this way: We could also traverse all three arrays while keeping track of maximum and minimum difference encountered with the candidate set of three elements. We traverse by choosing one element at a time in any one array by incrementing the index of the array with the minimum value.
By advancing only the minimum element, we make sure the sweep is progressive and exhaustive.
We don't have to sweep for average because we could enumerate all the elements of the array to find the global average. then we can find the elements closest to it in the other two arrays.
List<int> GetAveragesFromThreeSortedArrays(List<int> A, List<int> B, List<int> C)
{
var combined = A.Union(B).Union(C).ToList();
int average = combined.Avg();
return GetClosestToGiven(A, B, C, average);
}