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A related problem is to calculate the age of a person on a given date . The following query shows one way to achieve this, demonstrating the technique using the Employees table:

<script runat="server"> void Page_Load (object sender, EventArgs e) { InitSiteMap(); }

DECLARE @targetdate AS DATE = CAST(SYSDATETIME() AS DATE); SELECT empid, firstname, lastname, birthdate, DATEDIFF(year, birthdate, @targetdate) - CASE WHEN 100 * MONTH(@targetdate) + DAY(@targetdate) < 100 * MONTH(birthdate) + DAY(birthdate) THEN 1 ELSE 0 END AS age FROM HR.Employees;

The expression first calculates the difference in years between the employee s birth date and the target date . Call that difference diff . If the month plus day part of the target date is smaller than the month plus date part of the employee s birth date, the calculation subtracts one year from diff . Interestingly, this calculation handles leap years correctly . This code generates the following output:

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reduced by some percentage, and the more we successfully traverse a path through code, especially with different data, the more we reduce our overall exposure to risk. Behavioral testing approaches, systematic functional testing methods, and structural testing methods are each intended to provide different types of information and evaluate the software from different perspectives. Complex problems require a plethora of perspectives to provide the qualified information the decision makers require to better assess risk and make informed business decisions. Structural testing simply provides a different perspective to a complex problem. But structural testing is an organizational investment. This level of testing costs more in terms of time and skills needed by testers to design white box structural tests. However, structural testing can prove invaluable in reducing longterm costs and minimizing risk for highly critical or complex systems that require a high degree of reliability.

void InitSiteMap () { Caption.Text = SiteMap.RootNode.Title; foreach(SiteMapNode node in SiteMap.RootNode.ChildNodes) { ListItem li = new ListItem(); li.Text = node.Title; li.Value = node.Url; MyLinks.Items.Add (li); } } </script>

empid -----1 2 3 4 5 6 7 8 9 10 11 firstname ---------Sara Don Judy Yael Sven Paul Russell Maria Zoya George Mary lastname ------------Davis Funk Lew Peled Buck Suurs King Cameron Dolgopyatova Schaller North birthdate ----------------------1958-12-08 00:00:00.000 1962-02-19 00:00:00.000 1973-08-30 00:00:00.000 1947-09-19 00:00:00.000 1965-03-04 00:00:00.000 1973-07-02 00:00:00.000 1970-05-29 00:00:00.000 1968-01-09 00:00:00.000 1976-01-27 00:00:00.000 1972-02-29 00:00:00.000 2009-05-06 00:00:00.000 age ---50 47 35 61 44 35 38 41 33 37 0

Another very interesting technique to calculate age is based on integer manipulating, and is surprisingly minimalistic . The idea is to express the target date and the person s birth date as integers in the form YYYYMMDD, calling them a and b, respectively . Then the age can be simply calculated as (a b) / 10000, using integer division . Here s an example of applying this logic to our Employees table:

Based on the web.sitemap file shown earlier, the root node has two child nodes About Us and Products. For each of these nodes, an entry into a bulleted list control is created. Figure 8-8 shows the final results.

DECLARE @targetdate AS DATE = CAST(SYSDATETIME() AS DATE); SELECT empid, firstname, lastname, birthdate, (CAST(CONVERT(CHAR(8), @targetdate, 112) AS INT) - CAST(CONVERT(CHAR(8), birthdate, 112) AS INT)) / 10000 AS age FROM HR.Employees;

My uncle Frank has fished the rivers of Montana his entire life. To this day, he is a great fisherman. He always knows which combinations of pole, line, and bait have the best chance of catching a fish, and his friends consider him an expert in the field. As good as he is at fishing, he can't catch fish if there aren't any in the area of the river where he is fishing. He knows that great equipment and bait aren't enough, so he also knows how to read depth and flow of the rivers and uses this information to predict accurately where fish will be. The combination of knowing what to do and developing a strategy based on analysis of the fishing area is what makes him so successful. Techniques such as boundary-value analysis and pairwise testing are effective for reducing the number of needed test cases while minimally affecting risk. The problem is that there is not an even distribution of bugs throughout the source code. In fact, in a typical software project, some components tend to have many bugs while others have few or none. My uncle uses a variety of techniques to predict where the fish will be. Similarly, one of the necessities of software testing is to anticipate where pockets of bugs will be, and then target test cases toward those areas of the project.

To clean up, delete the two added employees by running the following code:

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