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

The status of augmented reality in laparoscopic surgery as of 2016.

http://www.diva-portal.org/smash/get/diva2:833967/FULLTEXT01

A systematic literature review on the industrial use of software process simulation

Filling forms is an activity, which finds its use in several day-to-day functions of any organization. The system of the present invention proposes the abstraction of the knowledge required to fill forms into a hierarchy containing three levels including form, process and domain knowledge. Such an abstraction caters to a variety of users with varying expertise, from the novice form-filling user to the expert. By encapsulating knowledge in this manner, the system of the present invention removes the complexity involved in the process of form-filling. Further, methods are proposed within the present invention to automatically fill and verify forms, used for a variety of end-uses.

Method and system for knowledge-based filling and verification of complex forms

A method for supporting a preparation of medical report for a patient. The method comprises acquiring one or more medical imaging studies and/or medical records which are related to the patient, automatically matching a report template to the one or more medical imaging studies and/or medical records according to at least one characteristic thereof, presenting the matched report template to allow a user to provide a diagnosis of the one or more medical imaging studies and/or medical records, and embedding the diagnosis in the matched report template.

Method and system for medical imaging reporting

A method and system for generation and validation of clinical reports with built-in automated measurement and decision support is provided. XML templates may be used for ensuring report data quality. The template data may include static, dynamic, calculated data, and others. The validation method may be based on formal logical constraint specifications. The constraint descriptions may include data types, cardinality, order, co-occurrence, Boolean logic, read-only data, regular expression patterns, etc. The method can be used to validate collected data on-the-fly based on constraint specifications without human interaction.

Method and system for generating and validating clinical reports with built-in automated measurement and decision support

A software-producing organization is a complex system. An interactive simulation that allows playful exploration and experimenting can enhance the understanding of such complex systems. Therefore, a simulator concept is presented that lets its user act in the role of a software-producing organization's top-level manager. In this role, business measures must be monitored and investment decisions need to be made.



The model is developed as a feasibility investigation with the premise of maximal abstraction, using concepts of the Capability Maturity Model Integration (CMMI) and balanced scorecards: 15 process areas deduced from CMMI serve as states and investment fields and 27 business performance indicators form the outputs.



Simulations of different scenarios illustrate that the model is capable of reflecting underlying strategies for advancing or maintaining an organization's processes. Moreover, the iterative and interactive investment approach and the graphical and historical result presentation can give valuable insight into complex process dependencies.



Therefore, the simulator can serve as a tool to playfully enhance the appreciation of software engineering practices. It can be used by all stakeholders involved in software development to better understand the various aspects of software engineering, their interdependencies, and the resulting complex dynamics of the software-producing organization's operations. Copyright © 2005 John Wiley & Sons, Ltd.

An interactive software management simulator based on the CMMI framework

This paper presents a systematic approach to develop and configure a process simulation model that relates process capabilities to business parameters in order to support process improvement projects within Siemens. The research work focuses on the systematic set up of a validated and acknowledged model that matches the company's process improvement needs by involving experts to adapt an existing mathematical framework and simulation application. The methodology consists of three complementary steps: An approved conceptual model is used as structural skeleton, quantitative parameters are derived by a prospective expert survey, and final adaptation and customization is facilitated in order to be useable for process experts themselves (instead of model developers).

Deriving a valid process simulation from real world Experiences

Each process improvement project must prioritize and select the areas or aspects to focus on. Moreover, each such selection needs to be communicated, motivated, and justified to all stakeholders (management as well as participating or affected parties). For both challenges, a conceptual framework and tool set is presented in this paper which is based on a quantitative model of the relations between improvement efforts and outcomes. These relations are represented as weighted dependency graph with extensions for time dynamics as well as uncertainties. The graph can be used for a goal-driven search of strategies as well as for simulation analysis of specific scenarios. The development of the graph basically requires a systematic documentation of the expectations or experiences in the respective context. The framework is outlined at the example of agile process fragments based on a knowledge base of evidential data.

A Framework for Systematic Evaluation of Process Improvement Priorities

Software process improvement needs guidance in proposing, assessing, and selecting a right set of steps and measurements. Often, a process model or a specific methodology is used for this purpose, e.g. the V-Modell, RUP, or agile process methodologies. Each such model or methodology consists of certain activities, procedures, or methods, i.e. a set of process fragments. Debates usually focus on the choice among these models or methodologies as a whole, but not on the specific, quantitative contributions of the distinct process fragments with respect to the particular goals of the organization. Such a simplification misses important chances for adaptation and motivation in diversified system development environments. Therefore, a conceptual framework and tool set is presented in this paper to search for sets of process fragments, which are able to meet actual objectives in an optimal way.

Christoph Dickmann

Papers

Method and system for generating and validating clinical reports with built-in automated measurement and decision support

An interactive software management simulator based on the CMMI framework

Deriving a valid process simulation from real world Experiences

A Framework for Systematic Evaluation of Process Improvement Priorities

Goal-driven evaluation of process fragments using weighted dependency graphs