What, when, and how is your IDE telling you?

A programmers.stackexchange question basically asks if there’s an ideal frequency to compile your code. Surely not, as it completely depends on what kind of work you’re doing and how much focus you need at any given moment; breaking to ask for feedback is not necessarily a good idea if you’re plan is solid and you’re in the zone.

But a related topic is more interesting to me: What’s the ideal form of automated information flow from IDE to programmer?

IDEs can now potentially compile/lint/run static analysis on your code with every keystroke. I’m reminded of that when writing new Java code in NetBeans. “OMG the method you started writing two seconds ago doesn’t have the correct return type!!!” You don’t say. And I’ve used an IDE that dumped a huge distracting compiler message in the middle of the code due to a simple syntax error that I could’ve easily dealt with a bit later. I vaguely remember one where the feedback interfered with my typing!

So on one side of the spectrum the IDE could be needling you, dragging you out of the zone, but you do want to know about real problems at some point. Maybe the ideal notification model is progressive, starting out very subtle then becoming more obvious as time passes or it becomes clear you’re moving away from that line.

Anyone seen any unique work in this area?

Stepping back to the notion of when to stop and see if your program works, I think the trifecta of dependency injection, sufficiently strong typing, and solid IDE static analysis has really made a huge difference in this for me. Assuming my design makes sense, I find the bugs tend to be caught in the IDE so that programs are more solid by the time I get to the slower—and more disruptive to flow—cycle of manual testing. YMMV!

On Frameworks

Building any non-trivial app, one of the toughest decisions to make is which development framework to base your work on. And there’s no way around this decision once you realize there’s no such thing as “not using a framework.”

Even if you’re just binding together 3rd party components, a framework will be born out of any development work, and it will have its own tradeoffs to consider.

  • Will it be documented?
  • Will it be tested?
  • Will it have a community of people working on/within it?
  • Will it have a plugin architecture encouraging code reuse?
  • Will you have access to plugins written by people outside your team?
  • Will configuration be easy/reusable?
  • Will it address code/UX scenarios you hadn’t considered?
  • Will you get free bug fixes/features from outside developers?
  • Will it securely handle password and protection against XSS, CSRF, etc.?
  • Will other developers be able to jump into the project?

Developers, plugins, sub-frameworks, tools, and shops all form an ecosystem around a framework that tends to build value as it grows. A strong ecosystem can make up for product weaknesses; a trip through the Drupal and WordPress codebases will have some seasoned developers shuddering at some architectural choices made (long ago), yet that code runs great due to the work of tons of people over time. And, thanks to the wealth of plugins available, and to the continual transfer of knowledge from one developer to the next, devs who are experienced on those platforms can build impressive systems quickly.

On the flip side, there are properties of mature frameworks that are important to consider:

  • They can be slow to change, which may mean maintaining a separate git branch with your own fixes.
  • They rarely bend to support the use cases of individual sites.
  • They tend to have older code that may be harder to integrate with the latest practices.
  • They can be large; any framework that solves a lot of problems out-of-the-box will be. Microframeworks can be a great choice, but their value tends to be limited to plumbing.

Thankfully the ideal framework needn’t be chosen first. You may be better off prototyping something as quickly as possible—by any means—then rebuilding after the requirements are clearer. The danger is the temptation to ship prototypes as production systems, where they grow to become liabilities over time.

Events with Dynamic Handlers, Simplified

Elgg’s event systems are based on registering callables to handle certain event names. As the codebase is still heavily procedural, most event handlers in the core and 3rd party plugins are global functions. Since I’m firmly in the static-code-is-evil camp, I’d much prefer handlers be dynamic method calls, but this introduces some complexity:

  1. Nice plugins allow their event handlers to be unregistered, but dynamic callbacks make this a bit awkward; any plugin that wanted to unregister another plugin’s handler would have to first get a reference to the other plugin’s object. Kind of messy.
  2. This requires proactively creating lots of objects—and loading lots of code—you don’t need in order to create the callbacks.

One way to work around the second issue would be to register callbacks on a proxy objects that lazy-load the real objects on the first method call. This adds complexity, could lead to typehint failures if the proxy gets accessed directly, and doesn’t solve the first issue at all. So I think the event system needs to be extended in a simple way:

We could allow callback strings of the form "service->method" where service is the name of a pre-registered (and lazy-loading) service on Elgg’s DI container. Essentially the event trigger would call $dic->service->method().

This would allow trivially (un)registering these handlers, as well as efficiently lazy-loading the objects without the complexity of proxies.

I’d also suggest never actually binding to the service. This way you could replace a whole set of handlers by replacing the service on the DI container.

Dependency Injection: Ask For What You Need

Despite the scary name, the concept is simple: Your class or function should ask for dependencies upfront. It should not reach out for them. This gives you a few powerful advantages:

1. In unit tests you can pass in mock dependencies to verify/fake behavior.

Imagine your class depends on a database. You really don’t want to require a live database to run your tests, but also you want to be able to test a variety of responses from the database without running a bunch of setup queries. What if your logic depends on the time being around 3AM? You can’t reliably test this if your object pulls time from the environment.

2. Your API doesn’t lie to users about what’s really required to use it.

Imagine if you started cooking a recipe and step 7 read, “Go buy 10 mangos now.” Imagine a Skydive class whose jump() method waited 10 seconds then executed Backpack.getInstance().getParachute.deploy(). “Umm, I’m in the air and the Skydive class didn’t tell me I’d need a backpack…”. Skydive should have required a parachute in the constructor.

3. Your API behaves more predictably.

Imagine a function getNumDays(month). If I pass in February, I usually get 28, but sometimes 29! This is because there’s a hidden dependency on the current year. This function would be useless for processing old data.

Baking the dependencies in

Note that the same principles apply to functions (fine for this exercise, but you should avoid global functions/static methods for all sorts of reasons). Consider this function for baking peanut butter cookies:

function makePBCookies(AlbertsonsPB $pb) {
  // ... 20 lines of setup code
  $egg = new LargePublixEgg();
  $sugar = new DixieSugar('1 cup');
  $chef = Yelp::find('chef');
  // create an oven
  // mix and bake for 10 min
  return $cookies;

From the argument list, it isn’t clear you’ll need a large Publix egg on hand. What if you don’t have a Publix in your area? What if you want less sugary cookies? Let’s refactor:

function makePBCookies(Egg $egg, Sugar $sugar, PB $pb) {
  // ... 20 lines of setup code
  $chef = Yelp::find('chef');
  // create an oven
  // mix and bake for 10 min
  return $cookies;

Now it’s immediately clear at the top what ingredients you’ll need; you can use any brands you want; and you can even change amounts/sizes to yield all kinds of flavors. This is really flexible, but we can make it even better:

function makePBCookies(Egg $egg, Sugar $sugar, PB $pb, Oven $oven, Chef $chef) {
  $mix = $chef->mix(array($egg, $sugar, $pb));
  return $chef->bake($oven, $mix);

In case it wasn’t obvious, it’s now clear we’ll need a chef and oven, and it makes good sense to outsource the oven design because this logic isn’t really specific to peanut butter cookies. A sign that our refactoring is going well is that the function body is starting to read more like a narrative.

Let’s build the ultimate cookie-making function:

function makeCookies(BakeList $list, Chef $chef, Oven $oven, Decorations $decs = null) {
  // BakeList is a composite of recipe & ingredients
  $mix = $chef->mix($list->getIngredients(), $list->getRecipe());
  $cookies = $chef->bake($oven, $mix);
  if ($decs) {
    $cookies = $chef->decorate($cookies, $decs);
  return $cookies;

We’ve refactored into several easy-to-test components, each with a specific task. This function is also easy to test because we just need to verify how the dependencies are passed and what methods are called on them. If we wanted to go even further we might notice that cookies come out differently in Denver vs. NYC (there’s a hidden dependency on altitude).

But that’s all dependency injection is: asking for what you need and not relying on sniffing dependencies from the environment. It makes code more flexible, more reusable, and more testable. It’s awesome.

I highly recommend Miško Hevery’s 2008 talks about dependency injection and testability, which really solidified the concepts and their importance for me. [This is an improved version of an article I wrote around that time hosted elsewhere.]

San Francisco, do you want to be Manhattan?

Another day, another article on S.F.’s crazy real estate market. Except it’s perfectly rational behavior: The secret is out that S.F. is an awesome place to live with plenty of very high-paying jobs, but also land is scarce and there are lots of development restrictions.

If no policies change, prices—both housing and general commodities—will continue to go up until S.F. is basically another Manhattan; if you want to live there you either must be in the upper class or able to live in a shoebox. The good news is that California is wonderful and people can live happily outside S.F. The city would just need to beef up its transportation infrastructure for an enormous commuting class, and the Bay Area will suffer the environmental implications of that.

If, however, you think there’s value in having residents from a wider range of incomes, you have to be willing to build a ton of new, and very dense, housing, including bulldozing some old areas—not every inch of the city can be treated as a historic artifact. Unfortunately plenty of lefties think that anything that’s good for rich developers must be bad for everyone else, and it just ain’t so. I highly recommend reading Matt Yglesias’s bite-sized ebook The Rent Is Too Damn High, which makes very convincing arguments that loosening development restrictions is a great idea for everyone. Lots of people want to live in S.F., and we should let them. Density is great for the economy and for decreasing the environmental impact of cars and commutes.

Renters are already living very densely packed in “single family” homes, so it’s pretty clear there would be plenty of demand for new apartments in a variety of sizes. The natural opposition to this is going to be existing owners that benefit from rising prices, but certainly a motivated majority (renters) could successfully push for expanded development. But until they realize it’s in their interest, they’ll keep complaining about a variety of things that don’t matter while being slowly forced out of the city.

Gainesville has been increasing the density of housing around the university and it seems to be pretty great to me. Until a few years ago it seemed inevitable that there would be ever increasing sprawl and student traffic, but now a lot more students can live in walking distance.

Unpacking the Access Control Systems in Drupal and Elgg

Elgg’s access control system, which determines what content a user can view, is somewhat limited and very opinionated, with several use cases—access control lists, friends—baked into the core system. In hopes of making this cleaner and more powerful, I’ve been studying Drupal’s access system. (Caveat: My knowledge in this area of Drupal comes mainly from reading code, schema, docs, and two great overviews by Mike Potter and Larry Garfield, so please chime in if I run off the rails.) 


Drupal’s system also influences update and delete permissions, but here I’m only interested in the “view” permission. Also, although Drupal has hook_node_access()—a procedural calculation of permissions for a node (like an Elgg entity) already in memory—I’m focusing on the systems that craft SQL conditions to fetch only nodes visible to the user. This is critical to get right in the SQL, because if your access control relies on code, you can never predict the number of queries required to generate a list for browsing. In this area, Drupal’s realms/grants API (hook_node_grants()is extremely powerful.

Realms and Grants in a Nutshell

At a particular time, a user exists in zero or more “realms”; more or less arbitrary labels which may be based on user attributes, roles, associations, the current system state, time…anything. Each realm has been granted (via DB rows) the permission to view individual nodes. So to query, we build up a user’s list of realms, this is baked into the query, and the DB returns nodes matching at least one realm.

E.g., at 2:30 PM today, an anonymous visitor might be in the realms (public, time_afternoon, season_winter*), whereas Mary, who logged in, might exist in the realms (public, logged_in, user_123, friendedby_345, role_developer, team_A, is_over_30, time_afternoon, season_winter). So Mary will likely see more nodes because her queries provide more opportunity to match grant rows. *Note these realms are made up examples.

Clearly this is very expressive, but Drupal (maybe for better) doesn’t provide many features out-of-the-box, so (maybe for worse) doesn’t build in many realms; the API is mostly a framework for implementing an access control system on top of added features. Contrib modules appear up to the task of providing realms based on all kinds of things (groups, taxonomies, associations with particular nodes), but it’s hard to collaboratively build an access control system, so these modules apparently don’t work well with each other and non-access modules must be careful to tap into the appropriate systems to keep nodes protected.

(Implementation oddities: The grants are done in the node_access table, which probably should’ve been called “node_grants”, especially because this table is only somewhat related to the hook called “node_access“. Less seriously—depending on your system size—each realm name (VARCHAR) is duplicated for every node/realm combination, so there’s some opportunity for normalization.)


If you squint, Elgg’s system is a bit similar. Each entity has an “access level” (a realm), with values like “public”, “logged in”, “private”, “friends”, or values representing access control lists (a group or a subset of your friends like a Google+ circle).

That an entity can have only one realm is of course the biggest (and most painful) difference, but also the implementation is significantly complicated by some realms needing to map to different tables. E.g. Elgg has to ensure “friends” maps to rows in an entities relationship table based upon the owner of the entity, while also mapping to the ACL table.

I imagine a lot of these differences come from Drupal being old as time with a lot bigger API reboots, and because Elgg’s access system was targeted to meet the needs of features like friends and user groups, which were built-in from the beginning. It’s hard to predict which schema results in faster queries, and will depend on the use case, but Drupal queries I would guess are easier to generate and safer to alter.


I think in the long run Elgg would be wise to adopt a realms/grants schema, though I would probably suggest normalizing with a separate “realms” table to hold the name and other useful bits. Elgg group ACLs and friend collections would map directly into realms, but friend relationships would need to be duplicated into realms just like groups have an ACL distinct from the membership relationship. Really I think a grants table could completely replace Elgg’s “entity_relationships” table, since both tables just map one entity to others with a name.

As for Drupal, I think the docs could more clearly describe realms and grants (unless I’ve totally got this wrong). I’m less sure of the quality of the API that populates/maintains the tables; it looks like the hooks are pretty low-level ways of asking “would you like to dump some rows into node_access?” and it’s not clear how much of the table must be rebuilt or how often this happens.

GitX for Cleaner Commits

A great way to make your pull requests easier to review is to reduce each commit to a particular purpose/functional change. In practice this often means not combining multiple feature additions in a single commit, or not including whitespace changes in a commit that makes some code change.

The command-line git add is just not great for anything but very trivial changes, so I use GitX (the active fork) when I’m on OSX.

Getting to the UI is a quick gitx in terminal and command+2 to switch to the Stage view. Here you can move changes in/out of staging via drag/drop files or by clicking on individual lines in diff views. This lets you run wild and loose during development then, with a scalpel, carefully craft your changes into a logical set of cleaner commits. E.g. if you’ve altering code, unstage all your unrelated whitespace changes and put them in the last commit, or just revert them or git stash to move them to another branch.

Is there a web app exception to the target _blank UX rules?

Experts can give you list of reasons why including target=”_blank” on links is bad for UX/accessibility and they’re mostly all right, but they tend to ignore the 5B pound gorilla in the room: Social media sites + Gmail all open external links in new windows and users (including saavy users who understand middle-click etc.) expect them to, and a huge part of UX is doing what the user expects.

My hypothesis is that users see some sites as applications (especially those that have popular app versions) that they would not generally close just to read a story. This change is also surely influenced by the fact that there is no instant way to context click on touch devices as there is with a mouse.

My point is we need to study this phenomenon with real users, who are rapidly moving to touch devices, and not let our preferences and value judgments, formed over years of desktop PC browsing, take over.

We must be willing to admit that in some scenarios the game has changed and we no longer know what is “best”. And this could be a case where what is best for UX is not best for accessibility or for promoting the understanding of browser technology. It would not be the first time.

Analyze my dreams

Kristen Schall plays an adorable tourist in a film shot in soft-focus Europe in the early 1900s. In a stunning/terrifying scene she rides a rickety ski lift contraption hundreds of feet up a mountain, with the steep path twisting and turning to follow a busy street that wraps up the mountainside.

Later: I’m in an abandoned storage unit and find an amazing 80’s drum machine made by a kitchen appliance manufacturer. It’s all black and grey plastic, has tons of knobs, most of the labels are worn off, and I need to get my hands on batteries and a cassette 4-track ASAP.