How has Japan become a major economic power, a world leader in the automotive and electronics industries? What is the secret of their success? The consensus has been that, though the Japanese are not particularly innovative, they are exceptionally skilful at imitation, at improving products that already exist. But now two leading Japanese business experts, Ikujiro Nonaka and Hiro Takeuchi, turn this conventional wisdom on its head: Japanese firms are successful, they contend, precisely because they are innovative, because they create new knowledge and use it to produce successful products and technologies. Examining case studies drawn from such firms as Honda, Canon, Matsushita, NEC, 3M, GE, and the U.S. Marines, this book reveals how Japanese companies translate tacit to explicit knowledge and use it to produce new processes, products, and services.

The knowledge-creating company : how Japanese companies create the dynamics of innovation

From the Book:
“Clean code that works” is Ron Jeffries’ pithy phrase. The goal is clean code that works, and for a whole bunch of reasons:
Clean code that works is a predictable way to develop. You know when you are finished, without having to worry about a long bug trail.Clean code that works gives you a chance to learn all the lessons that the code has to teach you. If you only ever slap together the first thing you think of, you never have time to think of a second, better, thing. Clean code that works improves the lives of users of our software.Clean code that works lets your teammates count on you, and you on them.Writing clean code that works feels good.But how do you get to clean code that works? Many forces drive you away from clean code, and even code that works. Without taking too much counsel of our fears, here’s what we do—drive development with automated tests, a style of development called “Test-Driven Development” (TDD for short). 
In Test-Driven Development, you:
Write new code only if you first have a failing automated test.Eliminate duplication.

Two simple rules, but they generate complex individual and group behavior. Some of the technical implications are:You must design organically, with running code providing feedback between decisionsYou must write your own tests, since you can’t wait twenty times a day for someone else to write a testYour development environment must provide rapid response to small changesYour designs must consist of many highly cohesive, loosely coupled components, just to make testing easy

The two rules imply an order to the tasks ofprogramming:
1. Red—write a little test that doesn’t work, perhaps doesn’t even compile at first
2. Green—make the test work quickly, committing whatever sins necessary in the process
3. Refactor—eliminate all the duplication created in just getting the test to work


Red/green/refactor. The TDD’s mantra.

Assuming for the moment that such a style is possible, it might be possible to dramatically reduce the defect density of code and make the subject of work crystal clear to all involved. If so, writing only code demanded by failing tests also has social implications:
If the defect density can be reduced enough, QA can shift from reactive to pro-active workIf the number of nasty surprises can be reduced enough, project managers can estimate accurately enough to involve real customers in daily developmentIf the topics of technical conversations can be made clear enough, programmers can work in minute-by-minute collaboration instead of daily or weekly collaborationAgain, if the defect density can be reduced enough, we can have shippable software with new functionality every day, leading to new business relationships with customers


So, the concept is simple, but what’s my motivation? Why would a programmer take on the additional work of writing automated tests? Why would a programmer work in tiny little steps when their mind is capable of great soaring swoops of design? Courage.
Courage
Test-driven development is a way of managing fear during programming. I don’t mean fear in a bad way, pow widdle prwogwammew needs a pacifiew, but fear in the legitimate, this-is-a-hard-problem-and-I-can’t-see-the-end-from-the-beginning sense. If pain is nature’s way of saying “Stop!”, fear is nature’s way of saying “Be careful.” Being careful is good, but fear has a host of other effects:
Makes you tentativeMakes you want to communicate lessMakes you shy from feedbackMakes you grumpy

None of these effects are helpful when programming, especially when programming something hard. So, how can you face a difficult situation and:
Instead of being tentative, begin learning concretely as quickly as possible.Instead of clamming up, communicate more clearly.Instead of avoiding feedback, search out helpful, concrete feedback.(You’ll have to work on grumpiness on your own.) 

Imagine programming as turning a crank to pull a bucket of water from a well. When the bucket is small, a free-spinning crank is fine. When the bucket is big and full of water, you’re going to get tired before the bucket is all the way up. You need a ratchet mechanism to enable you to rest between bouts of cranking. The heavier the bucket, the closer the teeth need to be on the ratchet.

The tests in test-driven development are the teeth of the ratchet. Once you get one test working, you know it is working, now and forever. You are one step closer to having everything working than you were when the test was broken. Now get the next one working, and the next, and the next. By analogy, the tougher the programming problem, the less ground should be covered by each test.

Readers of Extreme Programming Explained will notice a difference in tone between XP and TDD. TDD isn’t an absolute like Extreme Programming. XP says, “Here are things you must be able to do to be prepared to evolve further.” TDD is a little fuzzier. TDD is an awareness of the gap between decision and feedback during programming, and techniques to control that gap. “What if I do a paper design for a week, then test-drive the code? Is that TDD?” Sure, it’s TDD. You were aware of the gap between decision and feedback and you controlled the gap deliberately.

That said, most people who learn TDD find their programming practice changed for good. “Test Infected” is the phrase Erich Gamma coined to describe this shift. You might find yourself writing more tests earlier, and working in smaller steps than you ever dreamed would be sensible. On the other hand, some programmers learn TDD and go back to their earlier practices, reserving TDD for special occasions when ordinary programming isn’t making progress.

There are certainly programming tasks that can’t be driven solely by tests (or at least, not yet). Security software and concurrency, for example, are two topics where TDD is not sufficient to mechanically demonstrate that the goals of the software have been met. Security relies on essentially defect-free code, true, but also on human judgement about the methods used to secure the software. Subtle concurrency problems can’t be reliably duplicated by running the code.

Once you are finished reading this book, you should be ready to:
Start simplyWrite automated testsRefactor to add design decisions one at a time

This book is organized into three sections.
An example of writing typical model code using TDD. The example is one I got from Ward Cunningham years ago, and have used many times since, multi-currency arithmetic. In it you will learn to write tests before code and grow a design organically.An example of testing more complicated logic, including reflection and exceptions, by developing a framework for automated testing. This example also serves to introduce you to the xUnit architecture that is at the heart of many programmer-oriented testing tools. In the second example you will learn to work in even smaller steps than in the first example, including the kind of self-referential hooha beloved of computer scientists.Patterns for TDD. Included are patterns for the deciding what tests to write, how to write tests using xUnit, and a greatest hits selection of the design patterns and refactorings used in the examples.

I wrote the examples imagining a pair programming session. If you like looking at the map before wandering around, you may want to go straight to the patterns in Section 3 and use the examples as illustrations. If you prefer just wandering around and then looking at the map to see where you’ve been, try reading the examples through and refering to the patterns when you want more detail about a technique, then using the patterns as a reference.

Several reviewers have commented they got the most out of the examples when they started up a programming environment and entered the code and ran the tests as they read.

A note about the examples. Both examples, multi-currency calculation and a testing framework, appear simple. There are (and I have seen) complicated, ugly, messy ways of solving the same problems. I could have chosen one of those complicated, ugly, messy solutions to give the book an air of “reality.” However, my goal, and I hope your goal, is to write clean code that works. Before teeing off on the examples as being too simple, spend 15 seconds imagining a programming world in which all code was this clear and direct, where there were no complicated solutions, only apparently complicated problems begging for careful thought. TDD is a practice that can help you lead yourself to exactly that careful thought.

Test Driven Development: By Example

Disclosed is an autonomous neighborhood vehicle controllable through a neighborhood social network. In one embodiment, an autonomous neighborhood vehicle can autonomously navigate to a destination specified by a user of the neighborhood social network. In one embodiment, a computer system of the autonomous neighborhood vehicle is communicatively coupled to the neighborhood social network through a wireless network to autonomously navigate to a destination specified by the user of the neighborhood social network. A navigation server provides a remote sensing capability to the autonomous neighborhood vehicle. A particular user of a third-party application is authenticated as being a verified user of the neighborhood social network having a verified residential address. An information of the particular user is communicated to the third-party application from the neighborhood social network based on a personal address privacy preference of the particular user.

Autonomous neighborhood vehicle commerce network and community

Various systems and methods are provided that display various interactive user interfaces containing interactive maps. The user may use the interactive map to perform searches for data objects, toggle different layers associated with different types of objects for display, generate heatmaps based upon a grid and/or data object shapes, copy data between different interactive maps, and/or define filters to filter the displayed data. In response to user interaction with the map at a client system, tile layers are generated using server-side components, assembled into map tiles, and transmitted to client-side components to be displayed to the user. The tile layers may include a base tile layer, vector tile layer, selection tile layer, and inactive tile layer.

Interactive geospatial map

A method, apparatus and system of map based neighborhood search and community contribution are disclosed. In one embodiment, a neighborhood communication system is described. This embodiment includes a privacy server to apply an address verification algorithm associated with each user of the online community to verify that each user lives at a residence associated with a claimable residential address of an online community formed through a social community module of the privacy server using a processor and a memory. The privacy server automatically determines a set of access privileges in the online community associated with each user of the online community by constraining access in the online community based on a neighborhood boundary determined using an algorithm of the privacy server. The privacy server may constrain the particular user to communicate through the online community only with a set of neighbors having verified addresses using the privacy server.

Map based neighborhood search and community contribution

In one embodiment, a geographical information system has an information database and a client computing system that is coupled to a web server. A web based application is operable to display a map that includes a particular geographical location, retrieve at least one of a plurality of data records from the metadata database, and display the at least one data record at the particular geographical location of the map for a user. The web based application is executable on the client computing system or on the web server using a web browser.

Geographical information display system and method

A method for processing data streams from multiple data sources comprises receiving a data stream from a data source. A data template is dynamically selected, the data template comprising at least one data template region. A data region of the data stream is selected based on one of the data template regions. At least a portion of the data region is mapped to an intermediate data store based on the data template region. The mapped portion of the data region is extracted and stored in the intermediate data store.

System and method for processing electronic data from multiple data sources

Embodiments of a system and method for an artificial cognitive neural framework are generally described herein. In some embodiments, the artificial cognitive neural framework includes a memory system for storing acquired knowledge and for broadcasting the acquired knowledge, cognitive system, including cognitive perceptrons arranged to develop hypotheses and produce information, and genetic learning algorithms and a mediator, coupled to the cognitive system, the mediator arranged to gather the developed hypotheses and the produced information, to integrate the developed hypotheses and produced information using fuzzy, self-organizing contextual topic maps and to establish proper mappings between inputs, internal states and outputs of a continuously recombinant neural fiber network, wherein the genetic learning algorithms are arranged to continuously evolve candidate solutions by adjusting interconnections in the continuously recombinant neural fiber network by correlating patterns within the candidate solutions to stochasto-chaotic constraints, and to update the memory system.

Artificial continuously recombinant neural fiber network

Self-diagnostics and prognostics in multi-agent processing systems is explored in the context of self-soothing concepts in neuropsychology. This is one of the first steps to facilitate systems-level thinking in AI. Autonomous or semi-autonomous system must be able to understand, at a system-wide level, how every part of the system is influencing the other parts of the system. This drives the need for complete self-assessment within the AI system. The use of emotional memory and autonomic nervous state recall can be used to provide contextual cognition for system-level diagnostic and prognostics in large-scale systems. The use of an artificial cognitive neural framework with intelligent information software agents can be utilized to emulate emotional learning to facilitate self-soothing, which equates to self-healing in artificial neural systems. This chapter describes the architecture and specifications of software agents that are used to provide self-soothing and self-healing constructs for intelligent systems (Flexible object architectures for hybrid neural processing systems, Las Vegas, NV, 2010).

Artificial Neural Diagnostics and Prognostics: Self-Soothing in Cognitive Systems

Research shows that generating new knowledge is accomplished via natural human means: mental insights, scientific inquiry process, sensing, actions, and experiences, while context is information, which characterizes the knowledge and gives it meaning. This knowledge is acquired via scientific research requiring the focused development of an established set of criteria, approaches, designs, and analysis, as inputs into potential solutions.

John N. Carbone

Papers

Geographical information display system and method

System and method for processing electronic data from multiple data sources

Artificial continuously recombinant neural fiber network

Artificial Neural Diagnostics and Prognostics: Self-Soothing in Cognitive Systems

The great migration: information content to knowledge using cognition based frameworks