Design build computer programs

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The culture of computer programming has developed hundreds of its own design patterns: high level patterns that affect the architecture of the whole program--forcing you to chose them in advance--and low-level patterns that can be chosen later in development. High-level patterns are baked into certain types of frameworks. Net, but that doesn't mean you have to use it for every program; some programs don't have to support random user interaction and wouldn't benefit from MVC.

MVC is well described elsewhere , so here are some of the other high-level patterns and what they're good for. This is the first pattern you learned in programming class: the program starts, asks the user for input, does something with it, prints it out and halts. It's the simplest pattern and still useful and appropriate in many situations.

It's good for utilities, housekeeping tasks and one-off programs. One of the biggest mistakes made by programmers is to get too ambitious. They start designing an MVC program, take weeks or months to code and debug it, but then it dwarfs the magnitude of the problem.

If someone wants a program that doesn't need to take its inputs randomly and interactively, then produces a straightforward output, then it's a candidate for REPL is the kicked up a notch.

Here the program doesn't halt after printing its output, it just goes back and asks for more input. But if you give the REPL the ability to maintain state between each command then you have a powerful base to build simple software that can do complex things.

The design of a REPL program should keep the session's state separate from the code that interprets commands, and the interpreter should be agnostic to the fact that it's embedded in a REPL so that you can reuse it in other patterns. Write results. This is so you can easily adapt the program to work on terminals, GUIs, web interfaces and so-on.

Input is transformed one stage at a time in a pipeline that runs continuously. It's good for problems that transform large amounts of data with little or no user interaction, such as consolidating records from multiple sources into a uniform store or producing filtered lists according to frequently changing rules.

A news aggregator that reads multiple feed standards like RSS and Atom , filters out dupes and previously read articles, categorizes and then distributes the articles into folders is a good candidate for the Pipeline pattern, especially if the user is expected to reconfigure or change the order of the stages. You write your program as a series of classes or modules that share the same model and have a loop at their core.

The business logic goes inside the loop and treats each chunk of data atomically--that is, independent of any other chunk. If you're writing your program on Unix then you can take advantage of the pipelineing system already present and write your program as a single module that reads from stdin and writes to stdout.

Some language features that are useful for the Pipeline pattern are coroutines created with the "yield return" statement and immutable data types that are safe to stream. This is similar to the Pipeline pattern but performs each stage through to completion before moving onto the next. It's good for when the underlying data type doesn't support streaming, when the chunks of data can't be processed independently of the others, when a high degree of user interaction is expected on each stage, or if the flow of data ever needs to go in reverse.

The Workflow pattern is ideal for things like processing purchase orders, responding to trouble tickets, scheduling events, "Wizards", filing taxes, etc.. You'd wrap your model in a "Session" that gets passed from module to module. A useful language feature to have is an easy way to serialize and deserialize the contents of the session to-and-from a file on disk, like to an XML file.

The user prepares the steps and parameters for a task and submits it. The task runs asynchronously and the user receives a notification when the task is done. It's good for tasks that take more than a few seconds to run, and especially good for jobs that run forever until cancelled.

Google Alerts is a good example; it's like a search query that never stops searching and sends you an email whenever their news spider discovers something that matches your query. Yet even something as humble as printing a letter is also a batch job because the user will want to work on another document while your program is working on queuing it up. Your model is a representation of the user's command and any parameters, how it should respond when the task has produced results, and what the results are.

You need to encapsulate all of it into a self-contained data structure like " PrintJobCriteria " and " PrintJobResults " classes that share nothing with any other object and make sure your business logic has thread-safe access to any resources so it can run safely in the background. When returning results to the user you must make sure you avoid any thread entanglement issues. You can combine high-level patterns into the same program, but you will need to have a very good idea of what the user's problem is because one model will always be more dominant than the others.

If the wrong model is dominant then it'll spoil the user's interaction with the program. For example, it wouldn't be a good idea to make the Pipeline dominant and implement in one of its modules because you'll force the user to interact excessively for each chunk of data that goes through the pipeline.

This is exactly the problem with the way file management is done in Windows: you start a pipeline by copying a folder full of files, but an intermediate module wants user confirmation for each file that has a conflict. It's better to make dominant and let the user define in advance what should happen to exceptions in the pipeline.

A complete discussion of UI patterns would be beyond the scope of this tutorial, but there are two meta-patterns that are common between all of them: modal and modeless. Modal means the user is expected to do one thing at a time, while modeless means the user can do anything at any time. A word processor is modeless, but a "Wizard" is modal.

Regardless of what the underlying architectural pattern is, the UI needs to pick one of these patterns and stick to it. Some programs can mix the two effectively if the task lends itself, like tax-filing software because it lets you jump to points randomly in the data entry stage, but doesn't let you move onto proofing and filing until the previous stage is complete.

Almost all major desktop software is modeless and users tend to expect it. To support this kind of UI there are two mechanisms supported by most toolchains; event-driven and data binding. Sometimes called "call-backs", but when they're called "Events" it's usually because they've been wrapped in a better abstraction. You attach a piece of code to a GUI control, and when the user does something to the control click it, focus it, type in it, mouse-over it, etc your code is invoked by the control.

The call-back code is called a handler and is passed a reference to the control and some details about the event. Event-driven designs require a lot of code to examine the circumstances of the event and update the UI. The GUI is dumb, knows nothing about the data, needs to be spoon-fed the data, and passes the buck to your code whenever the user does something.

This can be desirable when the data for the model is expensive to fetch, like when it's across the network or there's more than can fit in RAM. Events are an important concept in business logic, overhead and models, too.

The "PropertyChanged" event is very powerful when added to model classes, for example, because it fits so well with the next major UI mechanism below:. Instead of attaching code to a control you attach the model to the control and let a smart GUI read and manipulate the data directly. You can also attach PropertyChanged and CollectionChanged events to the model so that changes to the underlying data are reflected in the GUI automatically, and manipulation on the model performed by the GUI can trigger business logic to run.

This technique is the most desirable if your model's data can be retrieved quickly or fit entirely in RAM. Data binding is complemented with conventional event-driven style; like say your address-book controls are bound directly to the underlying Address object, but the "Save" button invokes a classic Event handler that actually persists the data.

Data binding is extremely powerful and has been taken to new levels by technologies like Windows Presentation Foundation WPF. A substantial portion of your program's behavior can be declared in data bindings alone. For example: if you have a list-box that is bound to a collection of Customer objects then you can bind the detail view directly to the list-box's SelectedItem property and make the detail view change whenever the selection in the list-box does, no other code required.

A perfectly usable viewer program can be built by doing nothing more than filling the model from the database and then passing the whole show over to the GUI. Or like MVC without the C.

What it'll mean for the design of your program is greater emphasis on the model. You'll either design a model that fits the organization of the GUI, or build adaptors that transform your model into what's easiest for the GUI to consume. The style is part of a broader concept known as Reactive Programming. Remember that your data model should fit the solution, not the problem. Don't look at the definition of the problem and start creating classes for every noun that you see, and nor should you necessarily create classes that model the input or output--those may be easily convertible without mapping them to anything more sophisticated than strings.

Some of the best candidates for modelling first are actions and imaginary things, like transactions, requests, tasks and commands. A program that counts coins probably doesn't need an abstract Coin class with Penny , Nickel , Dime and Quarter dutifully subclassing it, but it should have a Session class with properties to record the start time, end time, total coin count and total value.

It might also contain a Dictionary property to keep separate counts for each type of coin, and the data type representing the coin type may just end up being an Enum or string if that's all it really needs. With the title blocks, users are capable of drawing plans, facades and sections, building details and completing them.

SketchUp provides numerous add-ons and a forum. Each object, surface and material has a unique texture. Its straightforward interface will appeal to architects, designers, builders and engineers at any stage of construction design. AutoCAD is extensively used by specialists for effective development, creation of designs and standard documentation.

You are unlikely to encounter compatibility problems unless you have used AutoCAD crack. If you start experimenting with layers and line weights, you will receive a decent project with standard drawing conventions and measurable design details. Another version is AutoCAD Architecture, an integrated toolset adapted to the needs of the architect. The created drawings will demonstrate real behavior, will take shape and structure.

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Verdict: In this free architectural drawing software, the emphasis is put on a swift and straightforward structural design process. It supports integration with plenty of well-known tools Trello, Visio, Jira for optimizing the workflow, as well as exporting drawings and plans to different formats for printing.

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FreeCAD is a parametric online 3D modeler of real objects. The tool lets users produce 2D thumbnails for creating 3D objects, and vice versa. Parametric modeling makes it easy to modify a component by going back to the model history. Objects, walls, floors, etc.