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

2004아테네 올림픽대회출전 한국레슬링 대표선수의 무산소성 운동능력 및 등속성 근력

Context Secondary studies are vulnerable to threats to validity. Although, mitigating these threats is crucial for the credibility of these studies, we currently lack a systematic approach to identify, categorize and mitigate threats to validity for secondary studies. Objective In this paper, we review the corpus of secondary studies, with the aim to identify: (a) the trend of reporting threats to validity, (b) the most common threats to validity and corresponding mitigation actions, and (c) possible categories in which threats to validity can be classified. Method To achieve this goal we employ the tertiary study research method that is used for synthesizing knowledge from existing secondary studies. In particular, we collected data from more than 100 studies, published until December 2016 in top quality software engineering venues (both journals and conference). Results Our results suggest that in recent years, secondary studies are more likely to report their threats to validity. However, the presentation of such threats is rather ad hoc, e.g., the same threat may be presented with a different name, or under a different category. To alleviate this problem, we propose a classification schema for reporting threats to validity and possible mitigation actions. Both the classification of threats and the associated mitigation actions have been validated by an empirical study, i.e., Delphi rounds with experts. Conclusion Based on the proposed schema, we provide a checklist, which authors of secondary studies can use for identifying and categorizing threats to validity and corresponding mitigation actions, while readers of secondary studies can use the checklist for assessing the validity of the reported results.

/pdf/identifying-categorizing-and-mitigating-threats-to-validity-vqpi818d2w.pdf

Identifying, categorizing and mitigating threats to validity in software engineering secondary studies

In the paper Cut-free ordinary sequent calculi for logics having generalized finite-valued semantics by A. Avron, J. Ben-Naim, and B. Konikowska. (Logica Universalis, 1:41–69, 2006), a general method was developed for generating cut-free ordinary sequent calculi for logics that can be characterized by finite-valued semantics based on non-deterministic matrices (Nmatrices). In this paper, a substantial step towards automation of paraconsistent reasoning is made by applying that method to a certain crucial family of thousands of paraconsistent logics, all belonging to the class of C-systems. For that family, the method produces in a modular way uniform Gentzen-type rules corresponding to a variety of axioms considered in the literature.

/pdf/cut-free-sequent-calculi-for-c-systems-with-generalized-4quyy7pwgj.pdf

Cut-free sequent calculi for C-systems with generalized finite-valued semantics

One of the main challenges faced by teachers in education, both at K-12 and academy levels, is related to the need to attract and retain the attention and the commitment by students, and ensure they achieve the required learning outcomes. Thus, new and exciting methodologies were developed to support teachers. Many of them have been inspired by approaches devised for Agile software development. This chapter aims to review the main Agile methodologies that have inspired educational approaches and to provide a description of the features retained in the educational context. Several experiences reported in the literature are also described.

Agile Methodologies in Education: A Review

This paper examines articles published between 1999 and 2014.A total of 1107 articles were collected and 27 were studied in depth.The studies have shown an increase in productivity in the academic environment, but a decrease in an industrial scenario, when using TDD.Most of the studies (76%) have identified an increase in the internal software quality and even more (88% of the studies) identified an increase in external software quality when using TDD. Context: Test Driven Development (TDD) is an agile practice that has gained popularity when it was defined as a fundamental part in eXtreme Programming (XP).Objective: This study analyzed the conclusions of previously published articles on the effects of TDD on internal and external software quality and productivity, comparing TDD with Test Last Development (TLD).Method: In this study, a systematic literature review has been conducted considering articles published between 1999 and 2014.Results: In about 57% of the analyzed studies, the results were validated through experiments and in 32% of them, validation was performed through a case study. The results of this analysis show that 76% of the studies have identified a significant increase in internal software quality while 88% of the studies identified a meaningful increase in external software quality. There was an increase in productivity in the academic environment, while in the industrial scenario there was a decrease in productivity. Overall, about 44% of the studies indicated lower productivity when using TDD compared to TLD.Conclusion: According to our findings, TDD yields more benefits than TLD for internal and external software quality, but it results in lower developer productivity than TLD.

The effects of test driven development on internal quality, external quality and productivity

Coding Dojo is a dynamic and collaborative activity inspired in martial arts that follows a discipline in a cheerful and pleasant environment Several agile development techniques are used during the Coding Dojo, such as test driven development, pair programming and baby steps This article presents some Coding Dojo characteristics that help teaching agile development techniques Some experienced practitioners were interviewed to get qualitative information about their perception of the Coding Dojo practice An electronic survey was answered by Coding Dojo participants from several Coding Dojo groups in Brazil, which provided quantitative data This article presents Coding Dojo as a teaching technique to help developers create software with higher test coverage rates

Teaching TDD, the Coding Dojo Style

Dojo de programacao e uma atividade dinâmica e colaborativa inspirada em artes marciais que segue uma disciplina num ambiente de ensino agradavel e divertido. Tecnicas de desenvolvimento agil sao utilizadas durante o dojo de programacao, dentre elas o desenvolvimento guiado por testes, programacao em pares, passos de bebe que serao explicadas neste artigo. Apresentamos nesse artigo caracteristicas do dojo de programacao que favorecem o ensino de tecnicas de desenvolvimento agil para grupos heterogenicos.

Usando Dojos de Programação para o Ensino de Desenvolvimento Dirigido por Testes

In this paper we present an effective prover for mbC, a minimal inconsistency logic. The mbC logic is a paraconsistent logic of the family of logics of formal inconsistency. Paraconsistent logics have several philosophical motivations as well as many applications in Artificial Intelligence such as in belief revision, inconsistent knowledge reasoning, and logic programming. We have implemented the KEMS prover for mbC, a theorem prover based on the KE tableau method for mbC. We show here that the proof system on which this prover is based is sound, complete and analytic. To evaluate the KEMS prover for mbC, we devised four families of mbC-valid formulas and we present here the first benchmark results using these families.

/pdf/effective-prover-for-minimal-inconsistency-logic-1hemps0g9r.pdf

Effective Prover for Minimal Inconsistency Logic

The Agile Manifesto has been around form more than fifteen years and, all over the world, companies and researchers seek for understand their adoption stage, as well as the benefits, barriers, and limitations of agile methods. Although there are some survey studies at the global level, we know little about how the Paraguayan software community is adopting agile methods. The present work conducted a research to characterize the current stage of adoption, initial concerns and barriers on the implementation of agile methods in software development companies in Paraguay. An online survey was sent to managers of 53 Paraguayan companies. Of these, 9 (17%) managers responded. The main concern about adopting agile methods (44.44% of respondents) was the lack of reliability in product quality if developed using agile methods. The main barrier was the lack of experience (66.66%) of the companies.

Adolfo Gustavo Serra Seca Neto

Papers

The effects of test driven development on internal quality, external quality and productivity

Teaching TDD, the Coding Dojo Style

Usando Dojos de Programação para o Ensino de Desenvolvimento Dirigido por Testes

Effective Prover for Minimal Inconsistency Logic

Concerns and Limitations in Agile Software Development: A Survey with Paraguayan Companies