Basics of qualitative research: Grounded theory procedures and techniques

According to W. Edwards Deming, American companies require nothing less than a transformation of management style and of governmental relations with industry. In Out of the Crisis, originally published in 1982, Deming offers a theory of management based on his famous 14 Points for Management. Management's failure to plan for the future, he claims, brings about loss of market, which brings about loss of jobs. Management must be judged not only by the quarterly dividend, but by innovative plans to stay in business, protect investment, ensure future dividends, and provide more jobs through improved product and service. In simple, direct language, he explains the principles of management transformation and how to apply them.

Out of the Crisis

https://link.springer.com/content/pdf/10.2307%2F3343168.pdf

Development as Freedom

Economic Control of Quality of Manufactured Product.

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

This paper presents a framework that draws on Structuration theory and dialectical hermeneutics to explicate the dynamics of software process improvement (SPI) in a packaged software organisation. Adding to the growing body of qualitative research, this approach overcomes some of the criticisms of interpretive studies, especially the need for the research to be reflexive in nature. Our longitudinal analysis of the case study shows SPI to be an emergent rather than a deterministic activity: the design and action of the change process are shown to be intertwined and shaped by their context. This understanding is based upon a structurational perspective that highlights how the unfolding/realisation of the process improvement (intent) are enabled and constrained by their context. The work builds on the recognition that the improvements can be understood from an organisational learning perspective. Fresh insights to the improvement process are developed by recognising the role of the individual to influence the improvement through facilitating or resisting the changes. The understanding gained here can be applied by organisations to enable them to improve the effectiveness of their SPI programmes, and so improve the quality of their software.

/pdf/software-process-improvement-as-emergent-change-a-vkcv1rigzh.pdf

Software process improvement as emergent change: A structurational analysis

This paper explores the emergence and adoption of cloud computing by small and medium-sized enterprises (SMEs) and points towards its implications for developing countries in sub-Saharan Africa. Several studies have shown the importance of technologies to SMEs and the potentials of SMEs for economic growth. Using qualitative techniques we obtained and analysed data from ten SMEs that have adopted cloud computing as an IT strategy. These SMEs span across various sectors including finance, information and communication technology (ICT), and manufacturing in Nigeria, a developing country in sub-Saharan Africa. We found that, contrary to the literature on cloud computing adoption in the global north, these SMEs are less concerned with challenges like security, privacy and data loss rather; they continue to show optimism in using the potential opportunities that cloud computing presents to them. We envisage that as cloud computing evolves, more SMEs in sub-Saharan Africa will adopt it as an IT Strategy. This could positively contribute to the successes of these SMEs and consequently contribute to the economic growth desired by these developing countries.

/pdf/cloud-computing-adoption-issues-for-sub-saharan-african-smes-2tg8l1wu9w.pdf

Cloud Computing: Adoption Issues for Sub-Saharan African SMEs

Previous work looking at software process improvement (SPI) in small organizations has highlighted difficulties faced by small organizations in implementing SPI successfully, but there is little analysis to understand why this is from an organization theory perspective. This paper presents an analysis of SPI across six software teams in the UK using a framework based on Giddens’ Structuration Theory. Using a structurational perspective helps to draw out how the process improvements are enabled and constrained by their context. By comparing these across the six situations the key similarities and differences across the cases are highlighted. This work extends the existing literature by helping to identify the areas of risk that need managing in small SPI initiatives. The study shows the issues as pertained to the six contexts and actions in each case. The paper highlights how the context influences the outcome.

/pdf/organizational-factors-shaping-software-process-improvement-r87axtg9y6.pdf

Organizational Factors Shaping Software Process Improvement in Small-Medium Sized Software Teams: A Multi-Case Analysis

Humans naturally reuse recalled knowledge to solve problems and this includes understanding the context i.e. the information that identifies or characterizes these problems. For problems in complex and dynamic environments, providing effective solutions by operators requires their understanding of the situation of the environment together with the context. Context-aware case-based reasoning (CBR) applications uses the context of users to provide solutions to problems. The combination of a context-aware CBR with general domain knowledge has been shown to improve similarity assessment, solving domain specific problems and problems of uncertain knowledge. Whilst these CBR approaches in context awareness address problems of incomplete data and domain specific problems, future problems that are situation-dependent cannot be anticipated due to lack of the facility to predict the state of the environment. This paper builds on prior work to present an approach that combines situation awareness, context awareness, case-based reasoning, and general domain knowledge in a decision support system. In combining these concepts the architecture of this system provides the capability to handle uncertain knowledge and predict the state of the environment in order to solve specific domain problems. The paper evaluates the concepts through a trial implementation in the flow assurance control domain to predict the formation of hydrate in sub-sea oil and gas pipelines. The results show a clear improvement in both similarity assessment and problem solving prediction.

/pdf/situation-awareness-in-context-aware-case-based-decision-2x4rkac9u0.pdf

Situation awareness in context-aware case-based decision support

Cloud computing can provide remote access to computing resources via the internet. It has the potential to transform economic activities considering its inherent pay-per usage model, flexibility and scalability features. This paper uses a socio-technical framework that maximizes selected development impact factors to analyze the use of Software-as-a-Service (SaaS) cloud applications in sub-Saharan Africa. Findings from this study show that there are several exciters and inhibitors to cloud computing adoption in sub-Saharan Africa. It also shows why security, privacy and trust issues as well as fear of data loss associated with cloud computing are viewed as exciters/enablers of the technology instead of inhibitors as the case is in the global north. There is equally no evidence found on regulatory or legislative policies affecting data location or protection at present. Furthermore, the findings show that these exciters and inhibitors are perceived by the users to interact associatively with each other to influence adoption. These findings will be of interest to policy makers and entrepreneurs interested in developing IS/ICT infrastructure.

Ian Allison

Papers

Software process improvement as emergent change: A structurational analysis

Cloud Computing: Adoption Issues for Sub-Saharan African SMEs

Organizational Factors Shaping Software Process Improvement in Small-Medium Sized Software Teams: A Multi-Case Analysis

Situation awareness in context-aware case-based decision support

Cloud computing adoption in sub-Saharan Africa: An analysis using institutions and capabilities