Kode Vicious Reloaded
A koder with attitude, KV answers your questions. Miss Manners he ain’t.
Although he is loath to admit it, Kode Vicious thrives on dispensing free advice to koders in need. But without your continuous stream of queries, he begins to wither or, worse, behave in a reckless and dangerous manner that, quite frankly, scares the heck out of us. And so, we beseech you, help us keep him at bay by sending your koding questions to firstname.lastname@example.org. His wisdom (and acerbic wit) awaits...
I’ve been working on a program in C++ to handle some simple data analysis at my company. The program should be a small project, but every time I start specifying the objects and methods it seems to grow to a huge size, both in the number of lines and the size of the final program. I think the problem is that there are just too many things in the system to analyze and each one needs a special case, which requires just a bit more code, or another subclass to be created. Help!
Driven to Abstraction
One of the biggest problems when people use an object-oriented language is that when they realize how easy it is to create yet another class, they do. Instead of figuring out where the rubber meets the road, they instead find where the rubber meets the sky.
Of course without looking at your code—and given your description I really don’t want to look at your code—I can’t give you a pat answer. I also charge heavily for pat answers.
When I find someone I work with spending days specifying class after class without writing any implementation code, I first take a long walk around the building. My therapist says that screaming at people helps no one. I don’t agree with him, but for now, I am playing along.
I have a few pieces of advice when you find that something you think should be simple starts to take up a huge amount of time and space. The first suggestion is to switch from a compiled language, such as C++, to something interpreted, such as BASIC. Oh, wait, sorry, not BASIC. I meant Python, my current scripting language of choice. The reason I suggest Python is because it, too, is object-oriented, and it’s easier to move an idea built in one OO language to another. You may even find that Python suits your needs perfectly and you won’t have to move to a compiled language, but that decision is further off.
I suggest a scripted language because of my second piece of advice. Try to solve a smaller part of the problem. Programmers and engineers often try to bite off more than they can chew. We’re a strangely optimistic lot, unless we’re talking to a marketing person. In that case solving an equation such as 2 + 2 seems to require millions of dollars in investment, a colo full of machines, high-speed network links to everyone’s house, and six weeks of paid vacation in Barcelona if you come up with a correct result. Maybe you don’t handle your marketing people that way, but I can’t suggest it strongly enough.
With a scripting language you can take smaller bites of the problem and play with them. If you can solve a part of the problem and get some output to work with, you can then probably figure out the next five or six things to do and do them and so on. The nice thing about working in smaller chunks is that you wind up with a result a lot sooner, and that’s a lot more satisfying than having reams of UML diagrams and hand waving and a promise of a brave new world when you’re done, which, at the rate you’re going, you probably never will be.
So, get your tires out of the clouds, put them on the road, and implement a few things, instead of trying to solve everything at once.
I work for a company that builds all kinds of different Web applications. We do everything from blogs and news sites to mail and financial systems. It depends on what the customer wants.
Right now our biggest problem at work is the number of bugs we have that relate to input validation. These bugs are totally maddening because each time one of them is fixed, some other problem pops up in the same code, and the checking code is getting very close to spaghetti. Is there any way out of this tangle without some mythical technology, such as natural language understanding?
You’ve come across one of the biggest programming problems since the day we stupidly let non-engineers (i.e., users) touch our nice toys. Of course, computers aren’t really very useful if they don’t do something for actual people, but it is a pain. Systems would be so much cleaner without people. Alas, user input is a fact of life, and one that we all have to work with every day. User input is also one of the biggest sources of security holes in software, as any reader of the BugTraq mailing list can tell you.
The first rule of handling user input is, “TRUST NO ONE!”, in particular your users. Although I’m sure 90 percent of them are perfectly nice people who go to their religious shrine of choice at the appointed time every week, or whatever it is perfectly nice people do (I don’t actually know any perfectly nice people, but I have heard about them), there are the usual minority of thieves, jerks, and just plain idiots who will look at your nice Web form as a place to steal money, play tricks, and generally cause havoc. The rest of the people, the perfectly nice ones whom I’ve never met, won’t actually attack your system; they’ll just use it in a way they think is logical, and if their logic and your logic do not match, kaboom! Kode Vicious hates kabooms. They mean late nights, and complaints from my doctor about alcohol and caffeine intake. I can’t help it if he’s stingy with the prescription meds, but let’s not get into that now.
The second rule is, “DON’T TRUST YOURSELF!” This is another way of saying that you should check your results to make sure you’re not missing anything. Just because you sent something to the users does not mean that they didn’t do something a bit odd to it before it came back to you. A quick example is a Web form: if you depend on the data you sent in a Web form to users, you had better check the whole form, and not just the parts you expected the users to change with their browsers. It’s a simple trick to exploit an error in form submission code by sending a slightly changed form with proper user input.
A whitelist, unsurprisingly, is the opposite of a blacklist. Whitelists contain only the things that are allowed, and are often very short. An example is, “Accept only ASCII alphabetic characters.” Whitelists can be very restrictive but they have a distinct advantage over blacklists in that the only time you have to change a whitelist it to make it more permissive. A blacklist is, by default, mostly permissive, with the few exceptions that are the entries in the list.
My recommendation is to switch to using whitelists and to be very restrictive in what the user can give to you. Initially this seems a bit draconian, but it’s probably the best way to protect your code, both from users and from turning into spaghetti.
KODE VICIOUS, known to mere mortals as George V. Neville-Neil, works on networking and operating system code for fun and profit. He also teaches courses on various subjects related to programming. His areas of interest are code spelunking, operating systems, and rewriting your bad code (OK, maybe not that last one). He earned his bachelor’s degree in computer science at Northeastern University in Boston, Massachusetts, and is a member of ACM, the Usenix Association, and IEEE. He is an avid bicyclist and traveler who has made San Francisco his home since 1990.
© 2005 ACM 1542-7730/05/0300 $5.00
Got a question for Kode Vicious? E-mail him at email@example.com—if you dare! And if your letter appears in print, he may even send you a Queue coffee mug, if he’s in the mood. And oh yeah, we edit letters for content, style, and for your own good!
Originally published in Queue vol. 3, no. 2—
see this item in the ACM Digital Library
Follow Kode Vicious on Twitter
Have a question for Kode Vicious? E-mail him at firstname.lastname@example.org. If your question appears in his column, we'll send you a rare piece of authentic Queue memorabilia. We edit e-mails for style, length, and clarity.
Tyler McMullen - It Probably Works
Probabilistic algorithms are all around us--not only are they acceptable, but some programmers actually seek out chances to use them.
Kate Matsudaira - The Science of Managing Data Science
Lessons learned managing a data science research team
Phelim Dowling, Kevin McGrath - Using Free and Open Source Tools to Manage Software Quality
An agile process implementation
Ivar Jacobson, Ed Seidewitz - A New Software Engineering
What happened to the promise of rigorous, disciplined, professional practices for software development?