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We introduced the concept of mental models in 2. Different people have different mental models of a given activity or process, but they rarely imagine them in terms of the detailed mechanics of how computers function. Each user naturally forms a mental image about how the software performs its task. The mind looks for some pattern of cause and effect to gain insight into the machine s behavior. For example, in a hospital information system, the physicians and nurses have a mental model of patient information that derives from how they think about patients and treatment. It therefore makes most sense to find patient information by using names of patients as an index. Each physician has certain patients, so it makes additional sense to filter the patients in the clinical interface so that each physician can choose from a list of her own patients, organized alphabetically by name. On the other hand, in the business office of the hospital, the clerks there are worried about overdue bills. They don t initially think about these bills in terms of who or what the bill is for, but rather in terms of how late the bill is (and perhaps how big the bill is). Thus, for the business office interface, it makes sense to sort first by time overdue and perhaps by amount due, with patient names as a secondary organizational principle.

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For many things, more is better. In the world of interaction design, the contrary is true. We should constantly strive to reduce the number of elements in user interfaces without reducing the capabilities of the products we are creating. To do this, we must do more with less; this is where careful orchestration becomes important. We must coordinate and control the power of the product without letting the interface become a gaggle of windows and dialogs, covered with a scattering of unrelated and rarely used controls. It is very common for user interfaces to be complex but not very powerful. Products like this typically segregate functionality into silos and allow a user to perform a single task without providing access to related tasks. When the first edition of this book was published in 1995, this problem was ubiquitous. Something as common as a Save dialog in a Windows application failed to provide the ability for users to also rename or delete the files they were looking at. This required users to go to an entirely different place to accomplish these very similar tasks, ultimately requiring applications and operating systems to provide more interface. Thankfully, contemporary operating systems are much better at this sort of thing. Because they have started to offer appropriate functionality based upon a user s context, users are less

Hello (RID = 1.1.1.1 Neighbors = 0) Hello (RID = 2.2.2.2 Neighbors = 1.1.1.1) Hello (RID = 1.1.1.1 Neighbors = 2.2.2.2)

Task placement versus task invocation. The placement of a task on a particular node does not necessarily mean that it will be invoked. The invocation depends on the satisfaction of firing rules on that node. For instance, in a fire monitoring application, each node could host a task that is responsible for sending an alarm message containing the location of a fire detected in the node s neighborhood. The placement annotation for this task will specify that it should be instantiated on all nodes. The firing rule for this task will indicate that it should be invoked only when certain conditions are satisfied. In a data-driven programming model like ATaG, this condition will typically be the presence of a data object that is produced by one or more other tasks on the node or on the neighboring nodes only when the result of the collaborative computation on temperature reading indicates the likelihood of a fire. Although the alarm notification task is placed on each node of the network, only a small fraction of the tasks may actually be executed in the lifetime of the sensor network. This distinction between placement and invocation, along with the fact that the former does not necessarily imply the latter, is therefore important. Task placement versus code placement. Another related issue is that of task placement versus code placement. The abstract task of an ATaG application is a

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