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Coming from an IT background, I've been involved with software projects but I'm not a programmer. One of my biggest challenges is that having a lot of experience in IT, people often turn to me to manage projects that include software development. The projects are usually outsourced and there isnt a budget for a full time architect or PM, which leaves me in a position to evaluate the work being performed.
Where I've managed to get through this in the past, I'm (with good reason) uneasy about accepting these responsibilities.
My question is, from a perspective of being technically experienced but not in programming, how can I evaluate whether coding is written well besides just determining if it works or not? Are there methodologies, tips, tricks of the trade, flags, signs, anything that would say - hey this is junk or hey this is pretty damn good?
Great question. Should get some good responses.
Code cleanliness (indented well, file organization, folder structure)
Well commented (not just inline comments, but variables that say what they are, functions that say what they do, etc.)
Small understandable functions/methods (no crazy 300 line methods that do all sorts of things with nested if logic all over the place)
Follows SOLID principles
Is the amount of unit test code similar in size and quality as the code base of the project
Is the interface code separate from the business logic code which in turn should be separate from the infrastructure access code (email, database, web services, file system, etc.)
What does a performance analysis tool think of the code (NDepend, NDoc, NCover, etc.)
There is a lot more to this...but this gets your started.
Code has 2 primary audiences:
The people who use it
The people who develop it
So you neeed 2 simple tests:
Run the code. Can you get it to do the job it is supposed to do?
Read the code. Can you understand the general intentions of the developer?
If you can answer yes to both of these, it is great code.
When reading the code, don't worry that you are not a programmer. If code is well written / documented, even a non-programmer should be able to see guess much of what it is intended to achieve.
BTW: Great question! I wish more non-programmers cared about code quality.
First, set ground rules (that all programmers sign up to) that say what's 'good' and what isn't. Automate tests for those that you can measure (e.g. functions less than a number of lines, McCabe complexity, idioms that your coders find confusing). Then accept that 'good coding' is something you know when you see rather than something you can actually pin down with a set of rules, and allow people to deviate from the standard provided they get agreement from someone with more experience. Similarly, such standards have to be living documents, adapted in the face of feedback.
Code reviews also work well, since not all such 'good style' rules can be automatically determined. Experienced programmers can say what they don't like about inexperienced programmers' code - and you have to get the original authors to change it so that they learn from their mistakes - and inexperienced programmers can say what they find hard to understand about other people's code - and, by being forced to read other people's code, they'll also learn new tricks. Again, this will give you feedback on your standard.
On some of your specific points, complexity and function size work well, as does code coverage during repeatable (unit) testing, but that last point comes with a caveat: unless you're working on something where high quality standards are a necessity (embedded code, as an example, or safety-critical code) 100% code coverage means you're testing the 10% of code paths that are worthwhile to test and the 90% that almost never get coded wrong in the first place. Worthwhile tests are the ones that find bugs and improve maintainability.
I think it's great you're trying to evaluate something that typically isn't evaluated. There have been some good answers above already. You've already shown yourself to be more mature in dealing with software by accepting that since you don't practice development personally, you can't assume that writing software is easy.
Do you know a developer whose work you trust? Perhaps have that person be a part of the evaluation process.
how can I evaluate whether coding is written well
There are various ways/metrics to define 'well'or 'good', for example:
Delivered on time
Delivered quickly
No bugs after delivery
Easy to install
Well documented
Runs quickly
Uses cheap hardware
Uses cheap software
Didn't cost much to write
Easy to administer
Easy to use
Easy to alter (i.e. add new features)
Easy to port to new hardware
...etc...
Of these, programmers tend to value "easy to alter": because, their job is to alter existing software.
Its a difficult one and could be where your non-functional requirements will help you
specify your performance requirements: transactions per second, response time, expected DB records over time,
require the delivery to include outcome from a performance analysis tool
specify the machine the application will be running on, you should not have to upgrade your hardware to run the app
For eyeballing the code and working out whether or not its well written its tougher, the answers from #Andrew & #Chris cover it pretty much... you want code that looks good, is easy to maintain and is performant.
Summary
Use Joel Test.
Why?
Thanks for tough question. I was about to write a long answer on merits of direct and indirect code evaluation, understanding your organisational context, perspective, figuring out a process and setting a criteria for code to be good enough, and then the difference between the code being perfect and just good enough which still might mean “very impressive”. I was about to refer to Steve McConnell’s Code Complete and even suggest delegating code audit to someone impartial you can trust, who is savvy enough business and programming-wise to get a grasp of the context, perspective, apply the criteria sensibly and report results neatly back to you. I was going to recommend looking at parts of UI that are normally out of end-user reach in the same way as one would be judging quality of cleaning by checking for dirt in hard-to-reach places.
Well, and then it struck me: what is the end goal? In most, but very few edge cowboy-coding scenarios, as a result of the audit you’re likely to discover that the code is better than junk, but certainly not damn good, maybe just slightly below the good enough mark. And then what is next? There are probably going to be a few choices:
Changing the supplier.
Insisting on the code being re-factored.
Leaving things as they are and from that point on demanding better code.
Unfortunately, none of the options is ideal or very good either. Having made an investment changing supplier is costly and quite risky: part of the software conceptual integrity will be lost, your company will have to, albeit indirectly, swallow the inevitable cost of the new supplier taking over the development and going through the learning curve (exactly opposite to that most suppliers are going to tell you to try and get their foot in the door). And there is going to be a big risk of missing the original deadlines.
The option of insisting on code re-factoring isn’t perfect either. There is going to be a question of cost and it’s very likely that for various contractual and historical reasons you won’t find yourself in a good negotiation position. In any case re-writing software is likely to affect deadlines and the organisation what couldn’t do the job right the first time is very unlikely to produce much better code on the second attempt. The latter is pertinent to the third option I would be dubious of any company producing a better code without some, often significant, organisational change. Leaving things as they are not good either: a piece of rotten code unless totally isolated is going to eventually poison the rest of the source.
This brings me to the actual conclusion, or in fact two:
Concentrate on picking the right software company in a first place, since going forward options are going to be somewhat constrained.
Make use of IT and management knowledge to pick a company that is focused on attracting and retaining good developers, that creates a working environment and culture fit for production of good quality code instead of relying on the post factum analysis.
It’s needless to expand on the importance of choosing the right company in the first place as opposed to summative evaluation of delivered project; hopefully the point is already made.
Well, how do we know the software company is right? Here I fully subscribe to the philosophy evangelised by Joel Spolsky: quality of software directly depends on quality of people involved which as it has been indicated by several studies can vary by an order of magnitude. And through the workings of free markets developers end up clustered in companies based on how much a particular company cares about attracting and retaining them.
As a general rule of life, best programmers end up working with the best, good with good, average with average and cowboy coders with other cowboy coders. However, there is a caveat. Most companies would have at least one or two very good developers they care about and try their hardest to retain. These devs are always put on a frontline: to fire fight, to lure a customer, to prove the organisation potential and competence. Working amongst more than average colleagues, overstretched between multiple projects, and being treated as royalty, sadly, these star programmers very often loose touch with the reality and become prima donnas who won’t “dirty” their hands with any actual programming work.
Unfortunately, programming talent doesn’t scale and it’s unlikely that the prima donna is going to work on your project past the initial phase designed to lure and lock in you as a customer. At the end the code is going to be produced by a less talented colleague and as a result you’ll get what you’ll get.
The solution is to look for a company there developer talents are more consistent and everyone is at least good enough to produce the right quality of code. And when it comes to choosing such an organisation that’s where Joel Test comes mighty handy. I believe it’s especially suitable for application by someone who has no programming experience but good understanding of IT and management.
The more points company scores on the Joel Test the more it’s likely to attract and retain good developers and most importantly provide them with the conditions to produce quality code. And since most great devs are actually in love with programming all the need is to be teamed up, given good and supportive work environment, a credible goal (or even better incredible) and they’ll start chucking out high quality code. It’s that simple.
Well, the only thing is that company that scores full twelve points on the Joel’s Test is likely to charge more than a sweatshop that scores a mere 3 or 5 (a self-estimated industry average). However, the benefits of having the synergy of efficient operations and bespoke trouble-free software that leverage strategic organisational goals will undoubtedly produce exceptional return on investment and overcome any hurdle rates by far outweighing any project costs. I mean, at the end of the day the company's work will likely be worth the money, every penny of it.
Also hope that someone will find this longish answer worthwhile.
We are developing software with pattern recognition in video. We have 7 mathematicians who are creating algorithms. Plus we have 2 developers that maintain / develop the application with these algorithms. The problem is that mathematicians are using different development tools to create algorithm like Matlab, C, C++. Also because they are not developers the don't give much concerns for memory management or multi-threading. This one of the reason why the app. has a lot of bugs.
If in your company you have similar situation, how do you deal with it? What's the best tools you can recommend to create algorithms? What communication supposed to be between mathematicians and developers? What's in your opinion the most effective to work with high-level tools?
I am not sure whether you devs are rewriting the mathematician's stuff or if you just have to interface to it so I am not sure if my answer is of any use.
However: I work together with a bunch of phd candidates and postdocs on a machine learning library and am a student myself. In that process, I came to translate a lot of algorithms from python/numpy to C++/blas.
This process can be quite tedious - especially with numerical and stochastic algorithms, it is hard to find bugs.
So here is what I did: Get some sample inputs and calculate the results with the python code. Generate unit tests out of these for C++ and then start coding them in C++.
Checking concrete sample inputs with the outputs is essential in this setting.
I agree with Makach.
Let the guys who are creating the algorithms use the tools that they are most familiar with. Because there are two separate (and equally important) tasks to work on in this project. First, there is the creating of an efficient, elegant and appropriate mathematically sound algorithm, then there is the twistedly difficult task of translating it into CPU-speak. The mathimaticians should focus on their first task, and to make it easier for them, allow them to use the toosl they are comfortable with. In terms of man hours, it is a much more efficient use of their time to write MATLAB code, than it would be to have them learn a new programming language.
Your task is to unearth the (presumably) brilliant mathematics that are buried within the gibberish code.
That part is just a perspective on the problem at hand. Here's the actual answer.
Communication, mutual respect, and teaching/learning.
Communication & Mutual Respect
You must communicate with them often. Work closely with them and ask them questions whenever you come across something you're not sure of. This is much easier when there is mutual respect, which means that if you spend all your time criticizing their coding abilities, then they will be forced to spend all their time criticizing your math abilities. Instead, try quick learning-sessions. ("Lunch & Learn" is a fairly common tactic)
Teaching/Learning
The first and most important piece of wisdom to impart to them is commenting. Have them comment the crap out of their code. Tell them that the comments are much more important than the code quality, and that as long as their comments are right, they can leave the rest up to you guys. Because they can. They don't need to have their code look beautiful, for be the fastest, they just need it to make sense to you guys.
To continue this mutual learning scenario, if you notice some very simple very common mistakes they are making, (nothing NEARLY as complicated as multithreading) just give them a quick heads up. "That way works (or doesn't) but here's a way to do it that is a little different but it will make your lives much much easier." Encourage them to reciprocate by trying to notice which nuances or parts of their algorithms which you and your team are having difficulty with and teach a little tutorial about it.
Once you guys get the communication flowing, you'll find it easier and easier to shape their coding style to what is best for your team, and they will also find it easier to understand why you don't see it the same way they do.
Also, as mentioned by Kekoav, make sure they provide a few fully loaded test cases.
That means for something like
A -> B -> C -> D -> Solution
They would provide you all the values for A, then what it looks like at B, then what it looks like at C and so on. So that you can be certain that not only is it correct at the end, but it's also correct at every step of the way. Try to have them provide examples that are regular, and also a few of them that are unusual, so that you can be certain your code covers edge cases.
I'd recommend the devs spend a few hours getting used to Matlab, especially the Matlab debugger. If their background is CS then they'll already be familiar with vectors and matrices theoretically if not practically. Other than the matrix being the default data structure, Matlab is C-like and easy enough to interpret for translation into another language.
I have been working with a physics professor lately, and have a little experience with this(although admittedly I'm no expert).
I have had to translate a lot of Matlab code into another language. It has been difficult because a lot of(most) of the operations are absent, including when it comes to precision, and working with matrices and vectors. A good math library needs to be found, or created to fit your needs.
The best way that I have found is to do the following:
Get the algorithm to work correctly in the new language.
Create some tests to verify that the algorithm is producing desired output. Have your mathematicians verify that your converted solution in fact works, and that you have covered all bases with your tests.
Then after it is working, and you can trust your tests, optimize the algorithm to be good coding style, have good design and performance characteristics. Use your regression tests to make sure you aren't breaking anything.
I normally start with a verbatim copy of their algorithms into the other language, and then work from there, regardless of if I do a lot of tests.
It is important to get a working copy first, in case the performance is really not an issue and you need to move on to other things and can come back later to make it faster.
This is your job. How you deal with this is what identifies you as a system developer.
Communicate with your colleagues. Draw and explain, have meetings, agree upon and set standards requirements, follow your plans and talk to your project manager. Make sure that your relevant colleagues are joining up on meetings. Have 1-1 talks etc etc
You cannot blame it on the mathematicians for developers creating bugs. It's their job to worry about implementation, not the mathematicians.
First let me say, I am not a coder but I help manage a coding team. No one on the team has more than about 5 years experience, and most of them have only worked for this company.. So we are flying a bit blind, hence the question.
We are trying to make our software more stable and are looking to implement some "best practices" and coding standards. Recently we started taking this very seriously as we determined that much of the instability in our product could be linked back to the fact that we allowed Warnings to go through without fixing when compiling. We also never bothered to take memory leaks seriously enough.
In reading through this site we are now quickly fixing this problem with our team but it begs the question, what other practices can we implement team wide that will help us?
Edit: We do fairly complex 2D/3D Graphics Software that is cross-platform Mac/Windows in C++.
Typically, the level of precision/exactingness in coding standards/process is directly connected to the safety level required. E.g., if you are working in aerospace, you will tightly control pretty much everything. But, on the other end of the spectrum, if you are working on a computer gaming forum site...if something breaks, no biggie. You can have slop. So YMMV, depending on your field.
The classic book on coding is Code Complete 2nd edition, by Steve McConnell. Have a team copy & strongly recommend your developers purchase it(or have the company get it for them). That will satisfy probably 70% of the stylistic questions. CC addresses the majority of development cases.
edit:
Graphics software, C++, Mac/Windows.
Since you're doing cross-platform work, I would recommend having an automated "compile-on-checkin" process for your Mac(10.4(maybe), 10.5, 10.6), and Windows(XP(maybe), Vista, 7). This ensures your software at the least compiles, and you know when it doesn't.
Your source control(which you are using, I assume), should support branching, and your branching strategy can reflect cross-platformy-ness as well. It's also advantageous to have mainline branches, dev branches, and experimental branches. YMMV; you will probably need to iterate on that and consult with with people who are familiar with configuration management.
Since it's C++, you will probably want to be running Valgrind or similar to know if there is a memory leak. There are some static analyzers which you can get: I don't know how effective they are at the modern C++ idiom. You can also invest in writing some wrappers to help watch memory allocations.
Regarding C++...The books Effective C++, More Effective C++, and Effective STL(all by Scott Meyers) should be on someone's shelf, as well as Modern C++ by Andrescu. You may find Lippman's book on the C++ object model useful as well, I don't know.
HTH.
There are a lot of consultants/companies who have coding rules to sell you, you should have no difficulty finding one. However, one that doesn't first ask you the field you are in (you didn't mention it in your question) is providing you with snake oil.
Test-Driven Development. TDD helps check for logic errors at the development phase.
Get everyone to read and discuss various standards and guidelines. I (as well as Stroustrup) suggest the Joint Strike Fighter coding standards. Ask your developers to classify the guidelines therein among
Already met
Could be met easily (few changes from current condition)
Should work toward in old code and follow in new development
Not worth it
Have the long technical discussions, and settle on a set for the team to adopt.
Code reviews have been shown to provide significant benefits to code quality, even more so than traditional testing. I would suggest getting in the habit of performing routine design and code reviews; the number of stages at which reviews are performed, the formality and detail of the reviews, and the percentage of work subject to review can all be set according to your business requirements. Coding standards can be useful when done right (and if everyone's code looks similar, it is also easier to review), but where you put your braces and how far you indent blocks isn't really going to affect defect rates.
Also, it's worth familiarizing yourself and your peers with the concept of technical debt and working bit by bit to redesign and improve parts of the system as you come in contact with them. However, unless you have comprehensive unit testing and/or processes in place to ensure high code quality, this may not help things.
Given that this is Stack Overflow, someone should reference The Joel Test. I like to automate as much as possible, so using Lint is also a must.
These basics are good for most any industry or team size:
Use Agile methodology (scrum is a good example).
http://www3.software.ibm.com/ibmdl/pub/software/rational/web/whitepapers/2003/rup_bestpractices.pdf
Use Test-driven development. http://www.agiledata.org/essays/tdd.html
Use consistent coding standards. Here is an example document:
http://www.dotnetspider.com/tutorials/BestPractices.aspx
Get your team familiar with good
design patterns.
http://www.dofactory.com/Patterns/Patterns.aspx
You can't go wrong with these basics. Build from there with new team members who have been there and done that. I'd strongly suggest pair programming once you've got those guys on the team. It is the best way to infect people with best practices.
Best of luck to you!
The first thing you need to consider when adding coding standards/best practices is the effect it will have on your team's morale and cohesiveness. Developers usually resent any practices that are imposed on them even if they are good ideas. The people issues have to be addressed for a big change to be successful.
You will need to involve your group in developing the standards and try to achieve consensus. That said, you will never get universal agreement on anything, so you will have to balance consensus and getting to standards. I've seen major fights over something as simple as tabs versus spaces in source.
The best book I've seen for C/C++ guidelines in complicated projects is Large Scale C++ Software Design. That book along with Code Complete (which is a must-read classic) are good starting points.
You don't mention any language, and while it is true that most of coding standards are language independent, it will also help you in your search. On most of the companies I had work they have different coding standards for different programming languages. So my advice will be:
Choose your language
Search the web since there are plenty of standards out there for your language
Gather all the standards you found
Divide your team into groups and give them a few of the documents to analyze. They should come with a list of things they think worthy to have in their new standards.
Have a meeting so each group present its findings to everybody (there will be a lot of redundancy between groups). That should be an open discussion and everybody's opinion should be accounted.
Compile a list of the standards that were selected by the majority of the coders and that should be your starting point.
Perform semi annual reviews of the standards, to add or remove things.
Now, The logic behind this is : Most of the problems from putting a coding standard from scratch is developer's acceptance. Each of us have a way of doing things and it sucks when somebody from the outside believes one way of doing things is better from another. So, if developers understand the logic and the purpose of the coding standards then you have half of the work done. The other thing is that standards should be design and created specifically for your company's needs. There will be some things that will made sense, and some that don't. With the above approach you could discriminate between those. The other thing is that standards should be able to change over time to reflect the company needs, so a coding standard should be a living document.
This blog post describes a lot of the common practices of mediocre programming. These are some of the potential issues you're team is having. It includes a quick explanation of the "best practice" for each one.
One thing you should have rules about is some kind of naming standard. It just makes life easier for people while not being really invasive.
Other than that, I'd have to say it depends on the level of your team. Some need more rules than others. The better people are, the less "support" they need from rules.
If you want a complete set of coding rules to control every little detail, you're going to spend lots of time arguing about rules and exceptions to rules and what you should write rules about. I'd go with something already written instead.
If you are concerned about quality then one thing you could do that really isn't about rules, is:
Automated building and testing. This has helped me a lot. Once you find a problem, it really helps to have an environment where you can write a test to verify the problem. Fix the problem and then easily add your test to an automatic test suite that makes sure that sort of problem can't come back without being spotted.
Then make sure these run often. Preferably every time someone checks something in.
If your framework requires certain rules to function well, put those in your coding standard.
If you decide to have coding standards, you want to be very careful about what you put in. If the document is too long or focuses on arbitrary stylistic details, it will just get ignored and nobody will bother to read it. Often a lot of what goes into coding standards is just the preferences of the person that wrote the document (or some standards that have been copied off the web!). If something is in the standard, it needs to be very clear to the reader how it improves quality and why it is important.
I would argue that a large proportion of what makes code readable is to do with design rather than the layout of the code. I have seen a lot of code that would adhere to the standards but still be difficult to read (really long methods, bad naming etc.) - you can't have everything it the standards, at some point it comes down to how skilled and disciplined your developers are - do what you can to increase their skills.
Perhaps rather than a coding standards document, try to get the team to learn about good design (easier said than done, I know). Make them aware of things like the SOLID principles, how to separate concerns, how to handle exceptions properly. If they design well, the code will be easy to read and it won't matter if there are enough white lines or the curly braces are in the right place.
Get some books about design principles (see a couple of recommendations below). Maybe get the the team to do some workshops to discuss some of the topics. Perhaps get them to collectively write a document on what principles might be important for their project. Whatever you do, make sure it is the team as a whole who decides what the standards / principles are.
http://www.amazon.co.uk/Principles-Patterns-Practices-Robert-Martin/dp/0131857258/
http://www.amazon.co.uk/Clean-Code-Handbook-Software-Craftsmanship/dp/0132350882
Don't write your own standards from scratch.
Chances are there are several out there that define what you want already, and are more complete than you could come up with on your own. That said, don't worry too much if you don't agree 100% with it on minor matters, you can swap in some parts of others, or call some infraction of it an warning rather than an error - depending on your own needs. (for example, some standards would throw a warning if the length of a line is more than 80 characters long, I prefer no more than 120 as a hard limit, but would make sure there was a good reason - readability & clarity for example - if there was > 80).
Also, do try to find automated methods of checking your code against the standard - including your own minor changes as required.
Besides books already recommended, I would also mention,
C++ Coding Standards: 101 Rules, Guidelines, and Best Practices by Herb Sutter and Andrei Alexandrescu (Paperback - Nov 4, 2004)
If you're programming on VB.NET, make sure Option Explicit and Option Strict are set to ON. This will save you a lot of grief tracking down mysterious bugs. These can be set at project level so that you never have to remember to to set them in your code files
I really like:
MISRA C standard (it's a little strict tho' but the ideas hold for C++)
and Hi-Integrity's http://www.codingstandard.com/HICPPCM/index.html C++ standard which borrows heavily from MISRA
LDRA (a static analysis tool) uses these standards to grade your work (this I don't use as it's expensive) but I can vouch for running cppcheck as a good 'free/libre' static analysis checker.
I'm "just" a hobbyist programmer, but I find that as my programs get longer and longer the bugs get more annoying--and harder to track. Just when everything seems to be running smoothly, some new problem will appear, seemingly spontaneously. It may take me a long time to figure out what caused the problem. Other times I'll add a line of code, and it'll break something in another unit. This can get kind of frustrating if I thought everything was working well.
Is this common to everyone, or is it more of a newbie kind of thing? I hear about "unit testing," "design frameworks," and various other concepts that sound like they would decrease bugginess, make my apps "robust," and everything easy to understand at a glance :)
So, how big a deal are bugs to people with professional training?
Thanks -- Al C.
The problem of "make a fix, cause a problem elsewhere" is very well known, and is indeed one of the primary motivations behind unit testing.
The idea is that if you write exhaustive tests for each small part of your system independently, and run them on the entire system every time you make a change anywhere, you will see the problem immediately. The main benefit, however, is that in the process of building these tests you'll also be improving your code to have less dependencies.
The typical solution to these sort of problems is to reduce coupling; make different parts less dependent on one another. More experienced developers sometimes have habits or design skills to build systems in this manner. For example, we use interfaces and implementations rather than classes; we use model-view-controller for user interfaces, etc. In addition, we can use tools that help further reduce dependencies, like "Dependency injection" and aspect oriented programming.
All programmers make mistakes. Good and experienced programmers build their programs so that it is easier to find the mistakes and restrict their effects.
And it is a big deal for everyone. Most companies spend more time on maintenance than on writing new code.
Are you automating your tests? If you do not, you're signing up creating bugs without finding them.
Are you adding tests for bugs as you fix them? If you do not, you are signing up for creating the same bugs over and over.
Are you writing unit tests? If not, you are signing up for long debugging sessions when a test fails.
Are you writing your unit tests first? If not, your unit tests will be hard to write when your units are tightly coupled.
Are you refactoring mercilessly? If not, every edit will become more difficult and more likely to introduce bugs. (But make sure you have good tests, first.)
When you fix a bug, are you fixing the entire class? Don't just fix the bug; don't just fix similar bugs throughout your code; change the game so you can never create that kind of bug again.
Bugs are a big deal to everyone. I've always found that the more I program, the more I learn about programming in general. I cringe at the code I wrote a few years back!! I started out as a hobbyist and liked it so much that I went to engineering college to get a Computer Science Engineering major (I am in my final semester). These are the things that I have learned :
I take time to actually design what I am going to write and document the design. It really eliminates a lot of problems down the line. Whether the design is as simple as writing down a few points on what I am going to write or full blown UML modeling (:( ) doesn't matter. Its the clarity of thought and purpose and having material to look back at when I come back to the code after a while that matter the most.
No matter what language I write in, keeping my code simple and readable is important. I think that it is extremely important not to over complicate the code and at the same time not to over simplify it. (Hard learned lesson!!)
Efficiency optimizations and fancy tricks should be applied at the end, only when necessary and only if they are needed. Another thing is that I apply them only If I really know what I am doing and I always test my code!
Learning language dependant details helps me keep my code bug free. For instance I learned that scanf() is evil in C!
Others have already commented on the zen of writing tests. I would like to add that you should always do regression tests. (i.e. Write new code, test all parts of your code to see if it breaks)
Keeping a mental picture of code is hard at times, so I always document my code.
I use methods to make sure that there is a bare minimum dependence between different parts of my code. Interfaces, class hierarchies etc. (Decoupled design)
Thinking before I code and being disciplined in whatever I write is another crucial skill. I know people who don't format their code so its readable (Shudder!).
Reading other peoples source to learn best practices is good. Making my own list is better!. When working in a team, there must be a common set of them.
Don't be paralyzed by analysis. Write tests, then code, then execute and test. Rinse wash repeat!
Learning to read over my own code and combing it for mistakes is important. Improving my arsenal of debugging skills was a great investment. I keep them sharp by helping my classmates fix bugs regularly.
When there is a bug in my code, I assume its my mistake, not the computers and work from there. That is a state of mind that really helps me.
A fresh pair of eyes aids in debugging. Programmers tend to miss even the most obvious errors in their own code when exhausted. Having someone to show your code to is great.
having someone to throw ideas at and not be judged is important. I talk to my mom (who is not a programmer) , throw ideas at her and find solutions. She helps me bounce my ideas back and forth and refine them. If she is unavailable, I talk to my pet cat.
I am not so be discouraged by bugs anymore. I've learned to love removing bugs almost as much as programming.
Using version control has really helped me manage different ideas I get while coding. That helps reduce errors. I recommend using git or any other version control system you might like.
As Jay Bazzuzi said - Refactor code. I just added this point after reading his answer, to keep my list complete. All credit goes to him.
Try to write reusable code. Reuse code, both yours and from libraries. Using libraries which are bug free to do some common tasks really reduces bugs (sometimes).
I think the following quote says it best - "If debugging is the art of removing bugs, programming must be the art of putting them in."
No offense to anyone who disagrees. I hope this answer helps.
Note
As others Peter has pointed out, use Object Oriented Programming if you are writing a large amount of code. There is a limit to code length after which it becomes harder and harder to manage if written procedurally. I like procedural for smaller stuff, like playing with algorithms.
There are two ways to write error-free programs; only the third one works. ~Alan J. Perlis
The only way for errors to occur in a program is by being put there by the author. No other mechanisms are known. Programs can't acquire bugs by sitting around with other buggy programs. ~Harlan Mills
Obviously, bugs are a big deal to any programmer. Just look through the list of questions on Stack Overflow to see this illustrated.
The difference between a hobbyist and an experienced professional is that the pro will be able to use his experience to code in a more "defensive" way, avoiding many types of bugs in the first place.
All the other answers are great. I'll add two things.
Source control is mandatory. I'm assuming you're on windows here. VisualSVN Server is free and maybe 4 clicks to install. TortoiseSVN is also free and it integrates into Windows Explorer, getting around the VS Express limitations of no add-ins. If you create too many bugs, you can revert your code and start over. Without source control, this is next to impossible. Plus you can sync your code if you have a laptop and a desktop.
People are going to recommend many techniques like unit testing, mocking, Inversion of Control, Test Driven Development, etc. These are great practices, but don't try to cram it all into your head too quickly. You have to write code to get better at writing code, so work these techniques slowly into your code writing. You have to crawl before you walk and walk before you can run.
Best of luck in your coding adventures!
This is a common newbie thing. As you get more experience, of course, you'll still have bugs, but they'll be easier to find and fix because you'll learn how to make your code more modular (so that changing one thing doesn't have ripple effects everywhere else), how to test it, and how to structure it to fail fast, close to the source of the problem, rather than in some arbitrary place. One very basic but useful thing that doesn't require complex infrastructure to implement is to check the inputs to all functions that have non-trivial precondtions with asserts. This has saved me several times in cases where I would have otherwise gotten weird segfaults and arbitrary behavior that would have been near impossible to debug.
If bugs weren't a problem then I'd be able to write a 100,000 line program in 10 minutes!
Your question is like, "As an amateur doctor, I worry about my patients' health: sometimes when I'm not careful enough, they sicken. Is patients' health a problem for you professional doctors too?"
Yes: it's the central problem, even the only problem (for any sufficiently all-inclusive definition of 'bug').
Bugs are common to everyone -- professional or not.
The larger and more distributed the project, the more careful one must be. One look at any open source bug database (ex: https://bugzilla.mozilla.org/ ) will confirm this for you.
The software industry has evolved various programming styles and standards, which when used right, make wrong code easier to spot or limited in its impact.
Therefore, training has a very positive on code quality... But at the end of the day, bugs still sneak through.
If you're just a hobbyist programmer, learning full bore TDD and OOP may involve more time than you're willing to put in. So, going on the assumption that you don't want to put in the time on them, a few easily digestible suggestions to cut down on bugs are:
Keep each function doing one thing. Be suspect of a function more than, say, 10 lines long. If you think you can break it into two functions, you probably should. Something that will help you control this is naming your functions according to exactly what they are doing. If you find that your names are long and unwieldy then you function is probably doing too many things.
Turn magic strings into constants. That is, instead of using:
people["mom"]
use instead
var mom = "mom";
people[mom]
Design your functions to either do something (command) or get something (query), but not both.
An extremely short and digestible take on OOP is here http://www.holub.com/publications/notes_and_slides/Everything.You.Know.is.Wrong.pdf. If you get this, you've got the gist of OOP and are quite frankly ahead of a lot of professional programmers.
The prevailing wisdom seems to be that the average programmer creates 12 bugs per 1000 lines of code - depends on who you ask for the exact number, but it's always per lines of code - so, the bigger the program, the more the bugs.
Subpar programmers tend to create way more bugs.
Newbies are often trapped by idiosyncrasies of the language, and lacking experience tends towards more bugs too. As you go on, you will get better, but never will you create bug-free code... well I still have bugs, even after 30 years, but that could be just me.
Nasty bugs happen to everyone from pros to hobbyists. Really good programmers get asked to track down really nasty bugs. It's part of the job. You'll know you've made it as a software developer when you stare at a nasty bug for two days and in frustration you shout, "Who wrote this crap!?!?" ... only to realize it was you. :-)
Part of the skill of a software developer is the ability to keep a large set of interrelated items straight in his/her head. It sounds like you're discovering what happens when your mental model of the system breaks down. With practice you will learn to design software that doesn't feel so brittle. There are tons of books, blogs, etc. out there on the subject of software design. And Stack Overflow of course for specific questions.
All that said, here's a couple of things you can do:
A good debugger is invaluable. Often you have to step through your code line by line to figure out what went wrong.
Use a garbage-collected language such as Python or Java if it makes sense for your project. GC will help you focus on making things work instead of getting bogged down by maddening memory errors.
If you write C++, learn to love RAII.
Write LOTS of code. Software is somewhat of an art form. Lots of practice will make you better at it.
Welcome to Stack Overflow!
What really changed my odds against code complexity and bugs was using a coding standart - how to place brackets an so on. It may seem like just boring and useless thing but it really unifies all the code and makes it much easier to read and maintain. So do you use a coding standart?
If you're not well organized, your codebase will become your very own Zebra Puzzle. Adding more code is like adding more people/animals/houses to your puzzle, and soon you have 150 various animals, people, houses and cigarette brands in your puzzle and you realize that it just took you a week to add 3 lines of code because everything is so inter-related that it takes forever to make sure the code still executes how you want it to.
The most popular organizational paradigm seems to be Object Oriented Programming, if you can break your logic down into small units which can be constructed and used independently of each other, then you will find bugs far less painful when they occur.
Having been a hobbyist programmer for 3 years (mainly Python and C) and never having written an application longer than 500 lines of code, I find myself faced with two choices :
(1) Learn the essentials of data structures and algorithm design so I can become a l33t computer scientist.
(2) Learn Qt, which would help me build projects I have been itching to build for a long time.
For learning (1), everyone seems to recommend reading CLRS. Unfortunately, reading CLRS would take me at least an year of study (or more, I'm not Peter Krumins). I also understand that to accomplish any moderately complex task using (2), I will need to understand at least the fundamentals of (1), which brings me to my question : assuming I use C++ as the programming language of choice, which parts of CLRS would give me sufficient knowledge of algorithms and data structures to work on large projects using (2)?
In other words, I need a list of theoretical CompSci topics absolutely essential for everyday application programming tasks. Also, I want to use CLRS as a handy reference, so I don't want to skip any material critical to understanding the later sections of the book.
Don't get me wrong here. Discrete math and the theoretical underpinnings of CompSci have been on my "TODO: URGENT" list for about 6 months now, but I just don't have enough time owing to college work. After a long time, I have 15 days off to do whatever the hell I like, and I want to spend these 15 days building applications I really want to build rather than sitting at my desk, pen and paper in hand, trying to write down the solution to a textbook problem.
(BTW, a less-math-more-code resource on algorithms will be highly appreciated. I'm just out of high school and my math is not at the level it should be.)
Thanks :)
This could be considered heresy, but the vast majority of application code does not require much understanding of algorithms and data structures. Most languages provide libraries which contain collection classes, searching and sorting algorithms, etc. You generally don't need to understand the theory behind how these work, just use them!
However, if you've never written anything longer than 500 lines, then there are a lot of things you DO need to learn, such as how to write your application's code so that it's flexible, maintainable, etc.
For a less-math, more code resource on algorithms than CLRS, check out Algorithms in a Nutshell. If you're going to be writing desktop applications, I don't consider CLRS to be required reading. If you're using C++ I think Sedgewick is a more appropriate choice.
Try some online comp sci courses. Berkeley has some, as does MIT. Software engineering radio is a great podcast also.
See these questions as well:
What are some good computer science resources for a blind programmer?
https://stackoverflow.com/questions/360542/plumber-programmers-vs-computer-scientists#360554
Heed the wisdom of Don and just do it. Can you define the features that you want your application to have? Can you break those features down into smaller tasks? Can you organize the code produced by those tasks into a coherent structure?
Of course you can. Identify any 'risky' areas (areas that you do not understand, e.g. something that requires more math than you know, or special algorithms you would have to research) and either find another solution, prototype a solution, or come back to SO and ask specific questions.
Moving from 500 loc to a real (eve if small) application it's not that easy.
As Don was pointing out, you'll need to learn a lot of things about code (flexibility, reuse, etc), you need to learn some very basic of configuration management as well (visual source safe, svn?)
But the main issue is that you need a way to don't be overwhelmed by your functiononalities/code pair. That it's not easy. What I can suggest you is to put in place something to 'automatically' test your code (even in a very basic way) via some regression tests. Otherwise it's going to be hard.
As you can see I think it's no related at all to data structure, algorithms or whatever.
Good luck and let us know
I must say that sitting down with a dry old textbook and reading it through is not the way to learn how to do anything effectively, even if you are making notes. Doing it is the best way to learn, using the textbooks as a reference. Indeed, using sites like this as a reference.
As for data structures - learn which one is good for whatever situation you envision: Sets (sorted and unsorted), Lists (ArrayList, LinkedList), Maps (HashMap, TreeMap). Complexity of doing basic operations - adding, removing, searching, sorting, etc. That will help you to select an appropriate library data structure to use in your application.
And also make sure you're reasonably warm with MVC - i.e., ensure your model is separate from your view (the QT front-end) as best as possible. Best would be to have the model and algorithms working on their own, and then put the GUI on top. Or a unit test on top. Etc...
Good luck!
It's like saying you want to move to France, so should you learn french from a book, and what are the essential words - or should you just go to France and find out which words you need to know from experience and from copying the locals.
Writing code is part of learning computer science. I was writing code long before I'd even heard of the term, and lots of people were writing code before the term was invented.
Besides, you say you're itching to write certain applications. That can't be taught, so just go ahead and do it. Some things you only learn by doing.
(The theoretical foundations will just give you a deeper understanding of what you wind up doing anyway, which will mainly be copying other people's approaches. The only caveat is that in some cases the theoretical stuff will tell you what's futile to attempt - e.g. if one of your itches is to solve an NP complete problem, you probably won't succeed :-)
I would say the practical aspects of coding are more important. In particular, source control is vital if you don't use that already. I like bzr as an easy to set up and use system, though GUI support isn't as mature as it could be.
I'd then move on to one or both of the classics about the craft of coding, namely
The Pragmatic Programmer
Code Complete 2
You could also check out the list of recommended books on Stack Overflow.