Perfection is achieved, not when there is nothing more to add, but when there is nothing left to take away. – Antoine De Saint Exupery

The approach to programming is concerned with finding the best ways to translate programmer’s intention into the good system design and code.

The programming is communication. The programmer continuously add, change and refine ideas in the code. Source code has two important goals: tell a computer what to do and tell people what the computer should do. The program code is the only true medium for storing and communicating ideas about the software system behavior. Quality of the ideas expression in the code directly affects overall quality of the system.

So, what are characteristics of the good code?

1. clear - easier to work with ideas;
2. minimal - less effort to understand and change ideas;
3. testable - easier to validate ideas.

These are 6 top reasons for bad design and code:

1. lack of expertise
2. unrestrained technical curiosity and creativity
3. missing big picture: system purpose and customer goals
4. blindly following popular methods and over-using technology
5. sloppiness; lack of attention to details
6. over-complicating design to have more work or increase job security

The programmer can write better code (and avoid most of these problems) by improving programming style and approach.

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“I made this program longer than usual because I lack the time to make it shorter.” – paraphrasing Blaise Pascal

The Elements of Pragmatic Programming Style is the collection of rules for pragmatic programmers. This collection doesn’t pretend to be comprehensive guide how to program. Rather it concentrates on fundamentals: how any programmer can build better software for the customer. Some of the rules are obvious, but, surprisingly, many programmers don’t even think about them. They make same mistakes over and over again. I hope this post will inject a healthy dose of pragmatism into your programming style and make it a bit better .

Style Components:

• Intention - understand your task and how to get it done
• Approach - basic principles of writing code
• Composition - organization of code
• Expression - expressing ideas in code
• Object Oriented Pragmatic Style

The goals of Pragmatic Programming Style are

1. Building reliable software fast.
2. Delivering maximum value for the customer.
3. Writing code that is easy to understand, change and share.

Intention

“Everyone hears only what he understands.” – Johann Wolfgang von Goethe

Understand your task and how to get it done

Sidereal
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Can in-house software programmers become extinct?

Companies spend millions dollars  on in-house software development. There is no easy escape for business – they must use software in today world. Companies need in-house programmers for specific for their businesses applications and pay hefty ransom. But will it continue forever? Companies are not happy. And there are few trends that can put in danger a large population of in-house programmers:

• customizable commercial and open-source software for conventional needs as accounting, CRM, CMS, etc.
• outsourcing  to specialized consulting software companies
• growth of domain specific languages and workbenches  that allow business experts to build software.
• development of AI that can replace programmers, e.g. neural networks, expert systems, evolutionary computation.

Thought experiment

Lets imagine the worst scenario. Suppose the dark day came – somebody invented a machine that can program. Non-programmers can use the machine for building software for their business needs. Technical knowledge and programming skills are no longer needed – just tell machine what you want and get a software program. Will it be the end of in-house programmer’s era?         Read full post >>

No man is an island unto himself every man is a part of the whole – John Donne

It is possible to program a web page or small application with little knowledge of programming. Use Google to search for examples and if you are lucky, you will find ready code and your are almost done. Even experienced programmers often retreat to search to save time and effort for finding solutions for their problems.

Modern effective programming is unthinkable without using search, the  Internet and collective intelligence. Therefore, search skills are becoming primary for an effective programmer.

Now we don’t need to know and remember how to solve many programming problems – we can use search. We are becoming more effective, productive and able to solve wider range of problems. But does it mean that good search skills are enough for building software? This post will review the role of search skills in forming programmer knowledge and how to use search effectively.

Types of knowledge and how it grows in programmer’s brains.

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I can’t wait to share this simple secret with you right now.

The Secret: Effective Software Systems are the systems that easy to understand and operate with human brains.

Programmers are more productive with effective software systems. Programmers can better learn and grow these system. Programmers have less problems, work faster and make better decision with them.

Now, you can avoid spending time reading this post if you already know this secret and you know how to avoid building the software system that:

• almost impossible to understand in reasonable time
  
• has confusing and convoluted swamp of logic and structure
• scary to change as nobody has any clue what will be broken, but sure that it will be broken
  

If you are still interested, lets find out what makes software systems effective.

Software Development is a pure mental endeavor (except typing on keyboard) that includes 3 main activities:

• Understand - learn and know system concepts and implementation
• Evolve - build, modify and support growth of the system ideas in the code
  
• Share - communicate and exchange ideas about the system

Programmers should care about 7 areas to make the system better suited for our brains:

1. Knowledge Creation and Retention – parsing, memorization and comprehension of the system ideas
   
2. System Organization – elements, relations and structure in the system
   
3. Sustaining Emerging Order – support evolution of the system and gain control over chaos
   
4. Minimize Noise and Purify – avoid adding unnecessary stuff to the system
   
5. System Discovery and Learning – making sense of the system
   
6. Mental Models – our internal explanations for how things are working in the real system
   
7. Shared Knowledge – ideas exchange, reconciliation of opinions and creation of mutually enhanced knowledge.

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Who are the perfect programmers?

Popular blogger Alex Iskold answers in Top 10 Traits of a Rockstar Software Engineer:

1. Loves To Code
2. Gets Things Done
3. Continuously Refactors Code
4. Uses Design Patterns
5. Writes Tests
6. Leverages Existing Code
7. Focuses on Usability
8. Writes Maintainable Code
9. Can Code in Any Language
10. Knows Basic Computer Science

It is a solid list, but this list concentrates on the secondary traits, which are just consequences of the deeper set of qualities. And it is an idealistic list. Do you expect the same qualities from a Flash programmer for kids websites and a software engineer for B2B financial transaction services? But how can we recognize a perfect programmer in the crowd of developers?

The Ultimate Criteria for finding The Perfect Programmer: The perfect programmer delivers good software that meets client’s expectations.

Therefore, the shocking truth is that perfect programmers could know only one programming language, don’t have any idea what are design patterns and don’t program all nights in their basements creating the next Google. We cannot objectively measure the programmers perfection like you could measure diameter of your biceps. The perfect programmers are simply perfect if they deliver a quality, usable and maintainable software system [a good system] in time and meet client needs.

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“The important thing is not to stop questioning” – Albert Einstein

A typical programmer faces thousands lines of code, huge number of details and millions of situations and states during the software system execution. A programmer should understand the system, know how to modify it and support knowledge about the system with explanations, justifications and answers. How can a software developer gain, maintain and operate this knowledge and make sense of these volumes of information and complex logic changing every day?

The ways how our memory works could give us few hints.

Our Human Memory Architecture

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davisayer

Thomas J. Bing and Edward F. Redish of University of Maryland analyzed how physics students work on assignments using computer programs:

Symbolic calculators like Mathematica are becoming more commonplace among upper level physics students. The presence of such a powerful calculator can couple strongly to the type of mathematical reasoning students employ… Mathematica plays an active role in focusing and sustaining their thought around calculation. These students still engage in powerful mathematical reasoning while they calculate but struggle because of the narrowed breadth of their thinking. Their reasoning is drawn into local attractors where they look to calculation schemes to resolve questions instead of, for example, mapping the mathematics to the physical system at hand.

These computer tools affect thinking and how students frame and focus their work.

Can we find similarity with the way tools affect programmer’s mindset ? In essence, software programming is operation on ideas and knowledge. We translate people ideas into the source code. But we cannot do it effectively without programming platform and tools – editors, compilers, debuggers and may others. And they have profound effect how we approach and solve customer needs. Our platforms and tools could frame and alter our thinking. PHP, Visual Basic, Java, .NET, Ruby On Rails programmers with the same level of experience will build not only technologically different solutions, but in the most cases solve problems different ways.

Programmer’s platforms and tools affect our mindset in three ways:

• Tools could prevent normal flow of idea implementation. Inconvenient tools, cumbersome environments and long feedback cycles stagnate productivity and lead us to the path of the least resistance, often far from optimal.
• Tools could make ineffective implementation strategies more attractive, affecting how we frame customer ideas. For example, UI-oriented programming environments could shift programmer’s mind to think about the problem in terms of screen elements and UI events (Smart UI) instead of reflecting in the code domain concepts, relations and ideas (Domain Driven Design).
• Tools could shift focus to the implementation perspective from the big picture and broader context of the problem at hand. Narrow focus on implementation and technology has negative impact. Often redefinition of the problem, analysis of alternatives or refining of concepts could bring much better results. Inexperienced programmers (and even experienced) often get into this trap, concentrating on tools the same way as novice drivers are more concentrated on the handling a car instead of observing the road and finding the better way.

What qualities should effective programmer tools have?

• Usability – enhance flow of programmer’s ideas or at least don’t impede and interrupt this flow. Tools should be convenient, easy-to-use and aligned with the way programmers work. Programmers should put most of their mental energy to think about customer ideas and much less how to deal with these tools.
• Representation – enable easy for understanding and modification representation of the structure, ideas and domain concepts in the code. Tools should provide a convenient solution view, organization and navigation for understanding, parsing and manipulation with components, classes, relations and concepts. Modern source-based project organization could benefit from tools like Resharper. Martin Fowler blogged about more radical approaches as repository-based code and Language Workbenches. UML, MDA and code auto-generation tools didn’t prove to be useful for effective code representation.
• Agile development friendly - support evolutionary design, short delivery cycles, refactoring, unit testing and other agile practices.

What do you think? What are the best tools for the programmer to enhance concentration on the problem, unobtrusive flow of thoughts and effective implementation of ideas?

Link: Symbolic Manipulators Affect Mathematical Mindsets, Thomas J. Bing, Edward F. Redish

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Cross Talk complains that the selection of Java as the first programming language in Computer Science education weakens programmers skills and lead to decline in qualification.

The irresistible beauty of programming consists in the reduction of complex formal processes to a very small set of primitive operations. Java, instead of exposing this beauty, encourages the programmer to approach problem-solving like a plumber in a hardware store: by rummaging through a multitude of drawers (i.e. packages) we will end up finding some gadget (i.e. class) that does roughly what we want. How it does it is not interesting! The result is a student who knows how to put a simple program together, but does not know how to program. A further pitfall of the early use of Java libraries and frameworks is that it is impossible for the student to develop a sense of the run-time cost of what is written because it is extremely hard to know what any method call will eventually execute.

Authors noticed other worrisome trends in teaching software professionals:

1. Mathematics requirements in CS programs are shrinking.
2. The development of programming skills in several languages is giving way to cookbook approaches using large libraries and special-purpose packages.
3. The resulting set of skills is insufficient for today’s software industry (in particular for safety and security purposes) and, unfortunately, matches well what the outsourcing industry can offer. We are training easily replaceable professionals.

I want to look into this problem from the broader perspective: what is the best way to become a good programmer for a beginner? There are two fundamental ways:

1. Strong theoretical foundation: learn applied math, theories of algorithms and computational complexity, read Knuth’s The Art of Computer Programming, solve problems with Turing machine, etc.
2. Shu Ha Ri – learning by experience: learn programming by solving practical problems with modern languages and platforms (Java, .Net, Ruby On Rails, PHP). Fundamental knowledge emerges from experience in solving real problems.

Definitely, there are some domains that require and intensively use CS theoretical knowledge: science, engineering, hardware and system programming. However, majority of software professionals build software for solving business, personal and other non-rocket science problems. I know a PHP programmer, who doesn’t know how to write a sort algorithm (without looking somewhere), but still have built several successful web applications. And I’m confident that there are strong computer science theorists who cannot write easy-to-use programs and make their customers happy.

So, what is the best approach? I believe any beginner should excel in following three areas:

1. Train clear logical thinking. The ultimate end result of any programming is a program (I hope it is not a surprise), which is a set of instructions for a computer. You cannot write instructions if you don’t know how to achieve end result. Any language which allows clear procedural expression of logic is fine for start (e.g. Pascal). I would add object-oriented and functional languages on later stages (e.g. Ruby and Lisp).
2. Understand modern software concepts and environments: computer architecture, networking, web, mobile, concurrent programming, cloud computing, etc. High level knowledge will give better orientation, starting points and overall understanding of software systems mechanics.
3. Learn to effectively implement customer needs. Happy customers and useful software is the end result of any healthy software project. Learning evolutionary, agile development and user experience (including communication and psychology) practices is essential for the effective software developer.

I believe that software development is empirical in nature. Math and computer science theories are great, but in many case they will be only brain exercises without practical results, especially for beginners. On the contrary, beginners will become excellent master programmers by succeeding in discussed above three fundamental areas and relentlessly learning from experience in applying them.

What do you think?

Links:
Computer Science Education: Where Are the Software Engineers of Tomorrow?, Dr. Robert B.K. Dewar and Dr. Edmond Schonberg
Is Software Development Empirical or Rational?

Wired magazine published a very interesting article about change in US military philosophy during the Iraq war. US started with idea of Network-Centric Warfare:

The US military could use battlefield sensors to swiftly identify targets and bomb them. Tens of thousands of warfighters would act as a single, self-aware, coordinated organism. Better communications would let troops act swiftly and with accurate intelligence, skirting creaky hierarchies.

The Army committed more than $230 billion to a network-centric makeover, on top of the billions the military had already spent on surveillance, drone aircraft, spy satellites, and thousands of GPS transceivers.

Advanced technology helped to achieve quick victories – the opposing forces in Iraq (and Afghanistan) were broken in matter of days. But years of struggle to establish the new order came after these victories. Seizing territory and destroying enemy forces was not enough for the success. American military have learned from these failures and started to change approach recently. They realized importance of winning trust, minds and hearts of local people to win the war.

General David Petraeus, commander of Multi-National Force in Iraq, knows all about these mind games. He oversaw the writing of the new counterinsurgency manual. The book counsels officers to reinforce the local economy and politics and build knowledge of the native culture, “an operational code’ that is valid for an entire group of people.” And the manual blasts the old, network-centric American approach in Iraq. “If military forces remain in their compounds, they lose touch with the people, appear to be running scared, and cede the initiative to the insurgents,” it says.

Sometimes software development projects are closer to military operations than to the engineering process. The situation often changes, pressure is building up and quick decisions are required. The software system is the end result of these operations and developers are in the forefront. The software system campaign is not finished after the initial development is over: people start using the system, administrators support it and developers continue evolving it over time.

What skills can developers learn to contribute to the overall success of the long software campaign beside coming with technical solutions?

We often rely on technology, new tools and smart strategies to win our software battles. But at the end, people will decide the fate of the software. Should we teach programmers how to win minds of people who use their software in addition to mastering superiority in technology solutions?