การวจยเชงคณภาพ เปนเครองมอสำคญอยางหนงสำหรบทำความเขาใจสงคมและพฤตกรรมมนษย การวจยแบบการสรางทฤษฎจากขอมล กเปนหนงในหลายระเบยบวธการวจยเชงคณภาพทกำลงไดรบความสนใจ และเปนทนยมเพมสงขนเรอยๆ จากนกวชาการ และนกวจยในสาขาสงคมศาสตร และศาสตรอนๆ เชน พฤตกรรมศาสตร สงคมวทยา สาธารณสขศาสตร พยาบาลศาสตร จตวทยาสงคม ศกษาศาสตร รฐศาสตร และสารสนเทศศกษา ดงนน หนงสอเรอง “ConstructingGrounded Theory: A Practical Guide through Qualitative Analysis” หรอ “การสรางทฤษฎจากขอมล:แนวทางการปฏบตผานการวเคราะหเชงคณภาพ” จะชวยใหผอานมความรความเขาใจถงพฒนาการของปฏบตการวจยแบบสรางทฤษฎจากขอมล ตลอดจนแนวทาง และกระบวนการปฏบตการวจยอยางเปนระบบ จงเปนหนงสอทควรคาแกการอานโดยเฉพาะนกวจยรนใหม เพอเปนแนวทางในการนำความรความเขาใจไประยกตในงานวจยของตน อกทงนกวจยผเชยวชาญสามารถอานเพอขยายมโนทศนดานวจยใหกวางขวางขน

Constructing Grounded Theory: A Practical Guide through Qualitative Analysis

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

Readings in information retrieval.

Laser-induced incandescence: Particulate diagnostics for combustion, atmospheric, and industrial applications

Context: Scientists have become increasingly reliant on software in order to perform research that is too time-intensive, expensive, or dangerous to perform physically Because the results produced by the software drive important decisions, the software must be correct and developed efficiently Various software engineering practices have been shown to increase correctness and efficiency in the development of traditional software It is unclear whether these observations will hold in a scientific contextObjective: This paper evaluates claims from software engineers and scientific software developers about 12 different software engineering practices and their use in developing scientific softwareMethod: We performed a systematic literature review examining claims about how scientists develop software Of the 189 papers originally identified, 43 are included in the literature review These 43 papers contain 33 different claims about 12 software engineering practicesResults: The majority of the claims indicated that software engineering practices are useful for scientific software development Every claim was supported by evidence (ie personal experience, interview/survey, or case study) with slightly over half supported by multiple forms of evidence For those claims supported by only one type of evidence, interviews/surveys were the most common The claims that received the most support were: "The effectiveness of the testing practices currently used by scientific software developers is limited" and "Version control software is necessary for research groups with more than one developer" Additionally, many scientific software developers have unconsciously adopted an agile-like development methodologyConclusion: Use of software engineering practices could increase the correctness of scientific software and the efficiency of its development While there is still potential for increased use of these practices, scientific software developers have begun to embrace software engineering practices to improve their software Additionally, software engineering practices still need to be tailored to better fit the needs of scientific software development

/pdf/claims-about-the-use-of-software-engineering-practices-in-449tuyd09q.pdf

Claims about the use of software engineering practices in science

The elderly experience difficulties when using design-for-all user interfaces. Moreover, their age-related issues increase over time. In the digital age, the mobile phone is most popularly used by the elderly to support their daily living and help them live more independently. However, mobile user interface guidelines customized for specific elderly groups are lacking. Cognitive load is one of the crucial factors that software developers and designers should consider when developing user interfaces for the elderly. To understand these aspects in more detail, we need to review the current literature and identify existing research gaps. This study investigates what are the focuses of mobile user interface design for the elderly by using a systematic mapping review method. Currently, this research presents a generic view, classification type, and new cognition aspects of overall user interface designs for the elderly. The findings show that this topic deserves more attention than it has received.

A Systematic Mapping Review: Mobile User Interface Design Guidelines for the Elderly with Cognitive Impairments

Software startups are currently very popular in Thailand, and existing information reveals an increase in the number of participants and investors in software startup businesses. Moreover, widespread events have been held to showcase the products and services these businesses have contributed. Software startups primarily develop innovations in the form of software produced from limited resources within a limited time. This software must be able to contribute to a sustainable business, and must be adjustable to each business size. Previous research indicates that both attention and emphasis must be placed on the importance of studying software startups in the form of empirical research. This will assist decision-making for those who are interested in initiating software startups and those who want to support them. Research has scarcely studied software startups in Thailand, and therefore, we are interested in Thai startups’ current situation as well as the startup ecosystem. This study clarifies that software startups in Thailand are defined as newly emerging businesses anticipated to help businesses grow quickly. Each software startup is in search of a different business model, as current software startups in Thailand have been created to help and support particular businesses. However, software startups rarely invent their own unique, exotic business models or apply advanced technologies and research in their startups.

Thailand’s Software Startup Ecosystem

Determinants of Social Networking Usage and Regret in Two Cultural Settings: France and Thailand.

Recently, reverse engineering has been widely adopted as a valuable process for extracting system abstractions and design information from existing software systems. The proposed research will focus on ForUML, a reverse engineering tool developed to extract UML diagrams from modern, objectoriented Fortran code, which are still used by scientists and engineering application developers. The first version of ForUML produces only UML class diagrams, which provide a useful window into the static structure of a program, including the make-up of each class and the relationships between classes. Rather than visualizing class diagrams, the developers need to understand class behavior and interactions between classes. UML sequence diagrams provide such important algorithmic information. Therefore, we proposed rules for transforming object-oriented Fortran into UML sequence diagrams with the goal to extend the ability of ForUML. The proposed rules were designed by Atlas Transformation Language. We believe that the contribution of this work would enhance the development, maintenance practices, decision processes, and communications in the scientific software community worldwide.

Modern Fortran Transformation Rules for UML Sequence Diagrams

Fortran finds widespread use in scientific and engineering communities that embraced computing early, including weather and climate science and mechanical, nuclear, and aerospace engineering. Over its lifetime, Fortran has evolved to support multiple programming paradigms, including Object-Oriented Programming (OOP). Despite the recently burgeoning ecosystem of tools and libraries supporting modern Fortran, there remains limited support for generating common Object-Oriented Design (OOD) diagrams from Fortran source code. ForUML partially fills this need by reverse engineering Unified Modeling Language (UML) class diagrams from object-oriented (OO) Fortran programs. Class diagrams provide useful information about class structures and inter-relationships, but class diagrams do not convey the temporal information required to understand runtime class behavior and interactions. UML sequence diagrams provide such important algorithmic details. This paper proposes to extend ForUML to extract UML sequence diagrams from Fortran code and to offer this capability via a widely used open-source platform. The paper argues that the proposed capability can raise the level of abstraction at which the computational science community discusses modern Fortran.

Aziz Nanthaamornphong

Papers

A Systematic Mapping Review: Mobile User Interface Design Guidelines for the Elderly with Cognitive Impairments

Thailand’s Software Startup Ecosystem

Determinants of Social Networking Usage and Regret in Two Cultural Settings: France and Thailand.

Modern Fortran Transformation Rules for UML Sequence Diagrams

Generating sequence diagrams for modern Fortran: WIP