No, I’m not talking about Coors Light. I”m talking about that phrase you hear bandied about in software development circles, “There is no silver bullet.”
Wikipedia describes the meaning of the phrase thusly:
The term has been adopted into a general metaphor, where "silver bullet" refers to any straightforward solution perceived to have extreme effectiveness. The phrase typically appears with an expectation that some new technology or practice will easily cure a major prevailing problem.
Historically it comes from a 1986 paper by Fred Brooks. Again from Wikipedia:
Brooks argues that "there is no single development, in either technology or management technique, which by itself promises even one order of magnitude [tenfold] improvement within a decade in productivity, in reliability, in simplicity." He also states that "we cannot expect ever to see two-fold gains every two years" in software development, like there is in hardware development.
Accidental complexity relates to problems that we create on our own and can be fixed — for example, the details of writing and optimizing assembly code or the delays caused by batch processing. Essential complexity is caused by the problem to be solved, and nothing can remove it — if users want a program to do 30 different things, then those 30 things are essential and the program must do those 30 different things.
Brooks distinction between accidental and essential complexity is not what most people have in mind when they invoke “no silver bullet.” Typically they are directing the statement toward some developer or manager who is in the throes of excitement over a new technology or practice. The statement seems to mean, “there’s no reason to get excited. Your new tool will have its own problems. It’s not really a step forward. You’re just naive.” It is this usage that I have a problem with.
The reason it bothers me is because it’s often me that is excited by some new technology or process. And every time it happens, I get “there is no silver bullet” tossed in my direction from someone. Fred Brooks is right, we’re not going to see the kinds of gains in software productivity that we see in hardware productivity. However, to all those that use “no silver bullet” to kill excitement, I must disagree.
There is a silver bullet to solving software problems. Are you ready? Do you want to know what it is? What company distributes it? How much it costs?
It’s your brain. You distribute it, and the cost is the effort of constantly learning new and better ways to accomplish your tasks. It doesn’t matter what language you use, what platform you write for, how you set up your environment. All of that is just the car—it still needs a driver. And no matter how great the car, if the driver is only holding the gas at 25mph, you’re only going to go 25mph.
You didn’t learn a single percent of what you need to know in college. You have to think critically about everything you’ve ever been taught. You have to look at the software you find and ask archeological questions such as “Why did the original developer structure the code this way? What problems was s/he trying to solve? Was this a good solution? Can I think of alternatives? Is this the best solution?” You have to ask these questions about software written by everyone, including yourself, even if you just finished typing it in.
If you adopt as a principle the idea that you should see every line of code you write as an opportunity for improvement, you will start making small improvements to your code. At first, you’ll start renaming variables to more clearly communicate intent. Then you’ll start extracting functions into smaller and smaller functions until most of them are only a few lines long. After awhile, these improvements will simply become second nature and your overall code-base will be clearer to you. In the clearer code-base, you’ll start to see other things that you can improve—things that were hidden from you before, much like a hole in the wall can be hidden by a pile of laundry. Historically, most software becomes a vicious cycle of layering hack on top of hack until the software atrophies and dies and has to be rewritten. Rinse and repeat. You can reverse the direction of that cycle—make it a virtuous cycle—by layering small improvement on top of small improvement, so that it will prosper and flourish.
On the surface, your job is to write software that solves a specific problem within a certain timeframe. But your job is also to make sure that that software will survive in the face of change. The first part is what they can teach in college. The second part is much harder. Learn it.
Read the blogs of other developers. Read books about the profession. Listen to podcasts about technology. Become active-minded about your profession. And next time some developer is excited because s/he’s found some better way of doing things, don’t say “there’s no silver bullet.” Say, “great job—how can I use that?”
Often as a software engineer my team is faced with a choice between two or more options for how to solve a particular problem. What will ultimately end up being the correct choice depends on information we may not have at the time we have to choose an option.
The arguments for and against the various alternatives are usually made along the lines of complexity, flexibility, and time to develop. The simpler solutions take less time to develop, but will be less flexible in the face of potential changes. More flexible solutions are great, except that they take more time to develop. If the expected changes never happen, the extra time to develop the feature is wasted effort.
Since we are not omniscient, we cannot know a priori which design alternative will ultimately be correct. Because we need to make a choice right now, we need some kind of guiding principle to help make a decision.
This idea was recently expressed in a Team Leadership Google Group I read by Charlie Poole on this thread on pair programming:
If I saw a pair debating the best approach for more than three minutes I’d
probably ask them to decide which approach to try first. This leads to useful
considerations, like "Will it be easier to refactor from A to B, or from B to A, if we
change our minds later?" When reminded that the goal is to decide what to do in the
next 5 minutes, not what is "best" in some absolute sense, most pairs move on…
When I talked about this post with my girlfriend Emily, she said “When hanging a picture, it’s better to drill a pilot hole sized to the screw first. If you drill into a stud, no harm done. If you start with a hole sized for an anchor and drill into a stud, you have patching, sanding, and painting to do.” (A stud finder helps in these situations too, but you get the idea.) I’m sure you all have similar examples.
This idea integrates nicely with the principles of YAGNI and Last Responsible Moment. Software, by nature, will change. We are unable to predict how and in what way it will change. Well designed software is not over-engineered software. If we tried to write software that would be malleable in the face of any kind of change, ever, we would never finish. There are simply too many possibilities. It would be an expensive waste of time. The alternative is not to write software that cannot change (otherwise it would no longer be soft-ware), but to make intelligent choices about which axes of change we will support.
In the face of two similar alternatives, we should choose the one that will be easier to change. This will usually be the one that commits the fewest resources, imposes the weakest restrictions, and takes the least time.
I was reading last night on NoodleFood on the Complexity of the Conceptual Mind. Diana reposts a blog about problems of concentration. The original author starts by giving an example of how a seemingly simple task can spiral into a long sequence of related tasks. The end result of this process is often a failure to accomplish the original task. The ability to focus on long and short-term goals at the same time is a key component of project success.
Joel Spolsky has a recent post entitled Capstone projects and time management. His article begins by discussing the failure of universities to prepare students for real-world software projects, and ends with this comment:
I’ve been blaming students, here, for lacking the discipline to do term-length projects throughout the term, instead of procrastinating, but of course, the problem is endemic among non-students as well. It’s taken me a while, but I finally learned that long-term deadlines (or no deadlines at all) just don’t work with professional programmers, either: you need a schedule of regular, frequent deliverables to be productive over the long term. The only reason the real world gets this right where all-student college teams fail is because in the real world there are managers, who can set deadlines, which a team of students who are all peers can’t pull off.
Regular frequent deliverables? That sounds like the agile value of short iterations to me. What’s important here is that two separate needs of the human mind are met by small processes. The first is a need to see how what you’re doing fits into the larger project or task you’re trying to accomplish. The second is to aid your ability to concentrate on the task at hand.
TDD
I find this discussion of time-management to be very interesting. Since I’ve adopted agile programming methodologies, I’ve noticed an increase in my productivity. Some of the productivity gains stem from my increased mastery of good design practices. But I think the major factor is my focus on short deliverable iterations. Writing unit tests is a way of maintaining the context of what I need to get done. Often I’ll be writing a test for feature-A, which I’ll discover depends on feature-B that I haven’t written yet. I can stop working on test-A and go write feature-B, building tests for feature-B as I go. When I’m done with feature-B, I still have the failing test for feature-A to remind me what remains to be done. On a day to day basis, the tests allow me to branch into sub-tasks at will without too much mental strain. TDD, in addition to its other virtues, is an aid to concentration.
Refactoring
Disciplined refactoring can also be an aid to concentration. In Martin Fowler’s Refactoring: Improving the Design of Existing Code, he discusses in detail many of the ways code can be changed. He starts with examples as simple as renaming a variable. Over the course of the examples, it becomes clear that larger refactorings are composed of smaller ones. The main takeaway for me was that in order to be successful with large refactorings, I have to break the task into smaller ones and complete each small refactoring before moving on to the next one.
For example, let’s say I need to split a class into two smaller classes. I can introduce the new class and immediately move all members from class A that I think belong in class B. If I do this, I’ll immediately break large pieces of the system. I’ll have to deal with all the various compile-errors and redirection points all at once, and this before I have a chance to verify that this is really what I want to do. On the other hand, I could create class B and begin my exposing it as a property of A. I could then move one property or method at a time from A to B, correcting the compile-errors as I went. When I have A an B looking the way I want I can simply remove the property from A, completing the separation.
Again, at any time during the refactoring it is only necessary to be attentive to a few issues at once.
Long Term Tasks
Not every task can be finished in a few hours. For longer-term tasks I have to break my work into milestones that are meaningful to me. I’ve started using an online tool called Zen to keep track of these things. I discovered agilezen in a recent .NET Rocks episode. I’ve been using it for awhile now and find it to be exactly what I need to keep track of the larger details of my work.
Conclusion
To run a successful project you must break long-term goals into shorter-term goals. This is for the same reason that a successful architecture requires that you break your project into smaller components, components into smaller classes, and classes into smaller functions. Software development is like any other task in life. You have to adapt your development and task-tracking methods to facilitate success. There’s only so much you can hold in your mind at once, but agile development methods allow you told tend the trees as you grow the forest.
While waiting on vm installations of Ubuntu and Debian Linux, I discovered ninite.com via gizmodo. Ninite will bulk-install a range of different free apps on Windows systems. As I’ve just upgraded my laptop to Windows 7, I’m happy to find this time saver!
The way it works
On the main page, you select the apps you wish to install, and ninite builds a custom installer based on your selections. This is a file that you download, so it is transferrable to other machines. If you have other free products you’d like to see as part of the ninite installer, you can recommend them to the site.
When I first tried executing the custom installer on Windows 7, I got an unspecified error. Running the installer as Administrator seems to have resolved that issue. In addition, Ninite was smart enough to detect which software was already installed.
My choices
Windows Messenger and Google Talk
iTunes and Hulu Desktop
Flash Player for IE and other browsers and Silverlight
I took the opportunity to suggest Kantaris as another media player, and Virtual Clone Drive for DVD image software. I used to use Deamon Tools Lite but I haven’t been able to get it to work in 64-bit Windows 7.
Original Gizmodo link: http://gizmodo.com/5388680/ninite-helps-you-upgrade-to-windows-7-by-installing-up-to-58-great-apps-at-once
The best thing I learned this week was a good way to use MVVM in connection with modal dialogs.I spent a good deal of time scouring the internet for a good answer to this problem. Most of the answers I found involved a lot of code to get up. The issue I have with those kinds of solutions is that if I integrate them into a production project, I’m responsible for supporting them whether I understand all of the code involved or not. I’m sure that over time I’ll acquire the mastery of WPF to be able to create those kinds of solutions, but I don’t have that level of mastery of WPF right now.
The aha moment came with I read this thread: http://social.msdn.microsoft.com/Forums/en-US/wpf/thread/0befde65-27e0-43ab-bd9f-6b1df38b7ab3 If you scroll down to the Sergey Pikhulya post (October 8, 2009, 6:42 PM) you’ll find the post I mean. Sergey suggested creating an Interface for IModalViewService, and injecting the an implementation that relies specifically on WPF Windows at run time. In this manner, you can create dummy implementations of IModalViewService for unit-testing your ViewModel.
Honestly, I felt kind of stupid for not thinking of this before. My application already supports injection of configured data services at run time. This is really exactly the same problem with the same solution—just on the presentation/UI layer instead of the data layer.
I thought of a few other solutions to the problem as well.
- Use events. Create events for each time a visual request needs to be made to the user.
- Pros: Easy.
- Cons: you have to create an event for each kind of prompt (message, OK/Cancel, Input).
- Doesn’t easily support specialized data templates for specialized dialogs.
- Leads to an explosion of code as you add new kinds of EventArgs sub-classes.
- You have to write a lot of glue code to make the interaction between MVVM and Xaml happen.
- Create command properties on the ViewModel and assign them in the Xaml.
- Pros: Easy
- You gain good separation because the VM doesn’t need to know how to execute the command, and the use of the dialog is encapsulated in the right layer.
- Cons: You still have a testability problem. If the command logic is complex, you are putting a lot of untestable code in the UI layer.
- Pros: Easy
This is my first post on a new blog. My goal with this blog is to continuously improve my skills by sharing what I’ve learned, and inviting constructive criticism from the developer community.
I contract full time developing line of business applications for a local manufacturing company. I’m currently focused on developing desktop applications for machine operators in the plants which provide real-time process flow information to decision makers. I also do some part-time work on nights and weekends.
I mostly enjoy working with the Microsoft tool stack, including Visual Studio and SQL Server. Recently, I’ve fallen in love with WPF. Over the last year I’ve become compentent in WPF, WCF, Silverlight, Linq to Sql, and Entity Framework.
I’ve been dealing with Enums and databases for awhile now. I think it’s something every LOB developer faces. Enums are developer-friendly because provide context to a delimited range of options in an easy to understand way. They do come with a couple of drawbacks however.
The first is that they’re not friendly for users. That Pascal-cased identifier looks great to a developer, but users aren’t really used to reading “RequireNumericData” and making sense out it. Since this post is supposed to be more about databases than UI, I’ll provide a quick snippet of code I use to get user-friendly descriptions of enum values:
public static class EnumService { public static string GetDescription(System.Type enumType, System.Enum fieldValue) { var enumFields = from element in enumType .GetFields(BindingFlags.Public | BindingFlags.Static) select element; var matchingFields = enumFields .Where(e => string.Compare(fieldValue.ToString(), e.Name) == 0); var field = matchingFields.FirstOrDefault(); string result = fieldValue.ToString() .SplitCompoundTerm() .ToTitleCase(); if (field != null) { var descriptionAttribute = field .GetCustomAttributes(typeof(DescriptionAttribute), true) .Cast<DescriptionAttribute>() .FirstOrDefault(); if (descriptionAttribute != null) result = descriptionAttribute.Description; } return result; } public static string GetDescription<T>(T fieldValue) { var fv = fieldValue as System.Enum; var result = GetDescription(typeof (T), fv); return result; } }
I refer to two extension methods on the string class, SplitCompoundTerm() and ToTitleCase(). Here is the code for them:
public static string SplitCompoundTerm (this string source) { var chars = source.ToCharArray(); var upperChars = from element in chars where Char.IsUpper(element) select element; var queue = new Queue<char>(); upperChars.ForEach(queue.Enqueue); var newTerm = new List<Char>(); var lastChar = default(char); foreach (var element in chars) { if (queue.Count() > 0 && queue.Peek() == element) { if (lastChar != ' ') newTerm.Add(' '); newTerm.Add(queue.Dequeue()); } else { newTerm.Add(element); } lastChar = element; } var newCharArray = newTerm.ToArray(); var temp = new string(newCharArray); var result = temp.Trim(); return result; } public static string ToTitleCase(this string source) { var result = CultureInfo.InvariantCulture.TextInfo.ToTitleCase(source); return result; }
SlitCompoundTerm() bothers me a bit. All it’s doing is looking for upper-cased characters in the middle of the term and inserting a space before them. I’m sure there’s a way to do that with regular expressions, but I haven’t gotten around to figuring that out yet.
A second drawback is that you often have to decide how to store enum values in a database. Do you store the numeric value? The text? Do you create a table that contains both the numeric and text values? Would that be one table for each enum, or one master table for all enums and an addition “enum type” column? Storing the numeric value is nice because it’s easy, but it’s very hard to report on. If your enum values are binary, then a single numeric value is going to be great for searching. If you need to report on the data you really want text. Text creates its own issues because you can’t really do a search on all records with a state of “Pending | Ready” using text. All of the developers problems are more easily solved by the numeric value, and all of the reporting problems are more easily solved by descriptive text. I’m sure some of you won’t like what I’m about to propose, but here it is: I store both values. Every enum value becomes not one, but two fields on the record in the RDBMS. From a data integrity standpoint, I can get away with this because I route all my data access calls through a well-defined data access layer. My apps never manipulate the RDBMS directly. While this approach solves my problems, it does come with the cost of increased data storage. This may or may not be an issue for you. It hasn’t been one for me so far.
Happy Coding!
