winforms ean 13 reader

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public ActionResult Index() { IEnumerable<User> users = UserRepository.GetAll(); UserDisplay[] viewModel = users.Select( user => new UserDisplay { Username = user.Username, Name = user.FirstName + " " + user.LastName }).ToArray(); return View(viewModel); }

TABLE 2-5

This seems to be an optimization you shouldn t make. Can you really say that whenever an item is needed, all its bids are needed as well Fetching strategies in mapping metadata work on a global level. We don t consider fetch="join" a common optimization for collection mappings; you rarely need a fully initialized collection all the time. In addition to resulting in higher memory consumption, every OUTER JOINed collection is a step toward a more serious Cartesian product problem, which we ll explore in more detail soon. In practice, you ll most likely enable a batch or subselect strategy in your mapping metadata for the bids collection. If a particular procedure, such as this, requires all the bids for each Item in-memory, you modify the initial HQL or Criteria query and apply a dynamic fetching strategy:

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The category axis shows time intervals: it is subdivided by Excel into equal sections; the major tick lines don t indicate the calendar data existing in the data source, but dates at regular intervals . By contrast, the data points of the line are displayed at inharmonic intervals; that is, on those days on which the measurements were actually implemented . Each marker of the data series thus is displayed in the calendar-based correct positions of the time-scale axis .

Embedded objects in Java Persistence (they re called components in Hibernate) are objects whose lifecycle entirely depends on the owning entity. When the owning entity is deleted, the embedded object is deleted as well. Let go back to our DVD store example. A DVD is rated. Rating has several dimensions: scenario, soundtrack, picture, and of course an overall rating. A rating doesn t make sense without a DVD, so we ll model it as an embedded object. To index the associated Rating object, simply place @IndexedEmbedded on the association and mark the Rating properties for indexing. The name @IndexedEmbedded is derived from the operation performed; we embed the indexing information in the main document. Listing 4.9 describes how to declare an object as embedded in the index.

public interface ISerializationSurrogate { void GetObjectData(Object obj, SerializationInfo info, StreamingContext context); Object SetObjectData(Object obj, SerializationInfo info, StreamingContext context, ISurrogateSelector selector); }

<div class="toolbar"> <h1 id="pageTitle"></h1> <a id="backButton" class="button" href="#"></a> <a class="button" href="#searchForm">Search</a> </div>

command.CommandText = "Select * from DotNetReferences"; command.Connection = connection; IDataReader reader = command.ExecuteReader(); dt.Load(reader); reader.Close(); connection.Close();

session.createCriteria(Item.class) .setProjection( Projections.rowCount() );

The ability of an application to perform under expected and heavy load conditions, as well as the ability to handle increased capacity, is an area that often falls under the umbrella of performance testing. Stress testing is a generic term that often includes load testing, mean time between failure (MTBF) testing, low-resource testing, capacity testing, or repetition testing. The main differences between the approaches and goals of these different types of testing are described here: Stress testing Generally, the goal of stress testing is to simulate larger-than-expected workloads to expose bugs that occur only under peak load conditions. Stress testing attempts to find the weak points in an application. Memory leaks, race conditions, lock collision between threads or rows in a database, and other synchronization issues are some of the common bugs unearthed by stress testing. Load testing Load testing intends to find out what happens to the system or application under test when peak or even higher than normal levels of activity occur. For example, a load test for a Web service might attempt to simulate thousands of users connecting and using the service at one time. Performance testing typically includes measuring response time under peak expected loads. Mean time between failure (MTBF) testing MTBF testing measures the average amount of time a system or application runs before an error or crash occurs. There are several flavors of this type of test, including mean time to failure (MTTF) and mean time to crash (MTTC). There are technical differences between the terms, but in practice, these are often used

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