The following top ten list collects some important things I have learned in the last eighteen years as IT professional. It is a very personal selection and doesn’t necessarily reflect the opinion of a software engineering organisation.
There is no strict ranking in the list – though I tried to put the more important things to the top.The technical and business know-how is more important for young software engineers and the soft skills getting increasingly relevant for senior software engineers.
Almost all of us work with a lot of people. In my first year after university, I had the opportunity to work on a clear big task without any customer and the need to talk a lot with peers. It was pure haven! Just do a complex task and have fun with the compiler. Later the trouble started with more complex tasks, increasing responsibilities and the need to work with people I didn’t liked at all.
During my professional life, I attended some so called soft skill courses. In these lesions I learned a lot about communication techniques, negotiation strategies and team dynamics. All this have been mechanical tools or psychological theories. Good to know, but the concept of Emotional Intelligence is something different.
The Wikipedia definition of Emotional intelligence starts with the sentence “Emotional intelligence (EI) is the ability to identify, assess, and control the emotions of oneself, of others, and of groups.”  The important key word in this sentence is emotions. Emotional intelligencedescribes the role of emotions in our lives.
Some years ago, I attended a project meeting with some senior management and the boss of my boss said something to me which sounded like “Hey Markus, you forgot to give me the information XYZ in time!”. I felt embarrassed, like a culprit and explained him that he was not right. The result was that I won the discussion with him and form that day I lost an important supporter in the company. My reaction was stupid and worthless.
Yes, I won one battle, but lost the war.
The root cause of this disaster was an automatic reaction on my site and a reciprocal effect between this senior management guy and me. With better sens of self and self-regulation, I would have been able to manage the situation in a better way.
If you leave sometimes a meeting and say to your self “Oh shit! Why did I say this?”, maybe it would be a good idea to learn something about Emotional Intelligence and yourself.
My favorite breakdown of emotional intelligence is:
- Intrapersonal intelligence describes the ability to have positive relationships and/or good communication between people. This means that you understand what people fell and need. The key competences of intrapersonal intelligence are:
- Sense of Self:
– recognize the own feelings, emotions and reactions
– mindfulness to get a better awareness
– controlling the current inner state
– bring own automatic reactions to mind and interrupt
- Personal leadership
– know and lead the parts of your own personalty
– care about own strengths and weaknesses
- Interpersonal intelligence describes the introspective and self-reflective capacities. Know your self, your emotions and what your weaknesses or strengths are, being able to control your own reactions. The key competences of interpersonal intelligence are:
– recognize the feelings and emotions of others
– express sympathy in anappropriate way
- Reduction of Automatic Reciprocal Effects
– bring automatic reactionswith othersto mind and interrupt (if needed)
- Creating Relationships
– create mid- and long-term relations with others
How can you design and implement good software without deep understanding of the purpose or use? The answer is easy: “If you don’t know the WHAT, you can’t decide about the HOW.” A deep understanding of your customer’s and/or users’sbusinesswill lead tobetter requirements, designs, implementations and tests.Most of the software’s functionality creates no business value. The challenge is to select the functionality which creates business value. The better you know the business the higher is the probability to implement the best system.
3) Minimum One Programming Language for each Mainstream Development Paradigm
The discussion what is the best programming language has a religious character, it’s more a question of belief. I don’t like to preach my personal belief about the bestlanguageshere, but one thing is important: “Learn more programming languages, at least one for each mainstream development paradigms.”
- procedural programming languages (C, COBOL, PL/I, FORTAN, etc.)
- object-oriented programming languages (Smalltalk, Java, C++, etc.)
- functional programming languages (Erlang, Clojure, F#, etc.)
- declarative programming languages(SQL, XSLT, regular expressions, etc.)
Its a good idea to know at least one multi-paradigm programming languages like Python, Java, C++ or C#. You find many listsof programming languages by type or other categoriesin the web .
Dependent of your industry, personal preferences and daily tasks you should select your individual top 1o list of programming languages. Learn them and try to use at least 3 of them on a regular base. The old saying “If your only tool is a hammer, all your problems will look like nails” is particularly true for development paradigms.
4) Know your Tools
There is a huge number of tools specializing indifferent disciplines like: requirements management, software & database design, software configuration management, build & deploy, continuous integration, development, debugging, profiling, code analysis or testing.
It should be mentioned that specialist from infrastructure/operations have also toolboxes with interesting capabilities, e.g. network monitoring, network analysis, operation system analytics, penetration testing, log file analysis, database performance tuning.
A software engineer can’t know all tools in detail, but he/she should know the key concepts and underlying technologies. Knowing the right tool and how to use can increase the productivity and quality.Spend some time to learn about tools.
5) Standard Data Structures, Algorithms and Big-O-Notation
When I stated to develop software it was absolutely necessary to know a lot about data structures and algorithms. The reason for that was the missing availability of standard implementations. Today most languages have comprehensive libraries for container, sorting and other operations.
Still it makes sense to know more. There are two main reasons:
- correct use of the standard libraries and
- some times you need individual solutions.
You should be able to analyse your own or others code. TheBig-O-Notation is the standard method to describe the expected consumption of time or memory depending from the number of data. 
If a manual analysis is to difficult, just make a micro benchmark and measure with test data of different size. Draw it in a plot and find a good fit of a possible model function. This is always better than nothing.
6) Don’t Trust Code without Adequate Test
Ten years ago, I trusted my code. Why not? After 8 years C++ with excellent skills and a lot of experiences. I just coded, tested and everything was working well. But over the years I made and saw a lot of errors. Because of these errors, I lost the trust in my own and others code.
Today, I don’t trust code until it passed:
- unit test,
- integration & system tests,
- checks of performance and memory with real world data,
- static code analysis,
- measure code coverage of test,
- load & stress tests and
- peer review.
This sounds over engineered, but you have to spend the time either during development or during maintenance. I favor to do the work once with good quality and not to spend my time withtroubleshooting.
7) Basics of Project Management, Lean Management and Agile Concepts
Even you don’t like to work as a project manager, you work in teams and at least have to organize your own work. To get along with technical leads you should understand their wording and way of thinking. Today everybody can work as project manager, scrum master or technical lead. Spend time to learn about management, because sometimes you should manage these guys.
A good example is effort estimation. My personal experiences say, that if you ask a software engineer about the effort of a task you get in 80% of the cases a dramatic underestimation of the effort. A software engineer tends to estimate just the good case without unexpected problems. This causes delays and/or poor quality because quite often the unexpected problems just happen.An other problem is the Definition of Done. The project manger means everything is done and often the developer estimates just the technical stuff.
Last week I had such a case. The developer estimated just one week of work. And after a complete planning, we saw several months effort. The developer estimated the time for implementation and forgot to estimate documentation, security concept, data protection issues, alignment with workers councils, reviews, project management efforts, deployment, etc.
8) Key Metrics of Software Development
Know what happens in your software, process, team and your own work. It is very difficult to control something what you can’t count. I encourage you to have question and try to find a real world measure as answer. Then you can have target values, do your work and find out if it worked out. Important is the word “real world measure”.
In software engineering we find a lot of obscure measures and/or derived metrics. E.g. the so calledmaintainability index (MI) :
MI = 171 – 5.2 x ln(avgHV) – 0.23 x avgCC(g‘) – 16.2 x ln (avgLOC) + 50 x sin (sqrt(2.4 x perCM))
where HV is the Halstead Volume, CC is the Cyclomatic Complexity, LOC is the lines of code and perCM is the percentage of comment lines. This is not what I call a real world measure and I don’t understand this.
My advice is easy: “Never use a measure and/or metric you don’t understand 100%. Some times it is enough to take some glasnuggets and count them (see also How Lean IT helps to reduce waste due to interruptions in software development?).”
9) The Root Cause of the Last Defect
Maybe your last error was not as severe, but to learn more about the root cause and negative effects you should analyse it.
- What was the root cause?
- In what development phase came the error in the software?
- How could it be detected earlier?
- Would a tool help to avoid it?
- Would a rule help to avoid it?
- Was it a qualification problem?
- Is the working environment (lot of interruptions, etc.) the root cause?
- Is it an documentation problem? Or maybe a communication problem?
- What are the costs to fix it?
- Are in the affected component more errors?
- Are the test cases good/complete enough?
You see a lot of question and the list is still not complete. The most important point is, to find the root cause to get better over the time. This works for your own qualification and way of working. And it works for your team. You just have to ask some question.
10) Understand the Infrastructure
I spend the my first 10 years in IT without thinking more than a minute about infrastructure. It was not necessary, because I didn’t work in an enterprise environment. At the moment I work for a bank (sorry for these Lehman Brothers stocks, nobody asked me). In a bank you have a lot of these infrastructure people. They are really different form software engineers. But, I don’t like to discuss here the differences and possibilities to get along with them.
Important is their language. Infrastructure peoples talk in “Information Technology Infrastructure Library (ITIL)”. Spend at least some days to learn this ITIL terminolgy. Some terms are completely different uses as developers do.
The second important thing is, that in infrastructurethe people are much more specialized than developers. Sometimes a developer has just one question and needs five infrastructure guys for the answer. The ITIL stuff is maybe the glue between the people ininfrastructure.
This guide will introduce you to the world of Software Architecture!
This 162 page guide will cover topics within the field of software architecture including: software architecture as a solution balancing the concerns of different stakeholders, quality assurance, methods to describe and evaluate architectures, the influence of architecture on reuse, and the life cycle of a system and its architecture. This guide concludes with a comparison between the professions of software architect and software engineer.