My Learning Blog

http://www.sqlservercurry.com/2011/08/sql-server-2008-move-data-to-different.html

function genRandomString() {
$length = 10;
$characters = ’0123456789abcdefghijklmnopqrstuvwxyz’;
$string = ”;
for ($p = 0; $p < $length; $p++) {
$string .= $characters[mt_rand(0, strlen($characters))];
}
return $string;
}

http://www.aviransplace.com/2004/10/12/using-rsa-encryption-with-java/

http://www.coderanch.com/t/517065/java/java/anyone-help-me-solve-RSA

http://www.strongauth.com/forum/index.php?topic=58.0

http://www.javaeye.com/problems/55475

「匯率」：簡單來說，就是不同貨幣之間的兌換，顯示不同貨幣間的交換比
例。例如：歐元兌美金EUR/USD = 1.3048，即表示以一單位
的歐元(EUR)可以兌換1.3048單位的美金(USD)。

「升值與貶值」： 當一單位A國貨幣可兌換B國貨幣金額增加，即表示A國
貨幣升值、B國貨幣貶值。例如：歐元兌美金匯率由
1.3048上漲為1.3055，即表示歐元升值、美金貶值，亦
可說歐元走強、美元走弱。

「匯差」：外匯可作為兩國貿易時的交易媒介，而持有外匯的主要獲利來
源有二，一是該貨幣的利息，另一則是匯差(即投資外匯所賺得
的匯率價差)。因此在投資外匯時，要注意匯率變動對投資報酬
的影響。若我們推估某種貨幣將走強而購買它，如果該外幣果
然如預期般大幅升值，那麼除了利息收入之外， 還可以賺到匯
差；相反的，當該外幣走眨時，就要承擔匯率損失。

In software development, a test suite, less commonly known as a validation suite, is a collection of test cases that are intended to be used to test a software program to show that it has some specified set of behaviours. A test suite often contains detailed instructions or goals for each collection of test cases and information on the system configuration to be used during testing. A group of test cases may also contain prerequisite states or steps, and descriptions of the following tests.

Test fixture in xUnit

In generic xUnit, a test fixture is all the things that must be in place in order to run a test and expect a particular outcome.

Frequently fixtures are created by handling setUp() and tearDown() events of the unit testing framework. In setUp() one would create the expected state for the test, and in tearDown() it would clean up what had been set up.

Four phases of a test:

1. Set up — Setting up the test fixture.
2. Exercise — Interact with the system under test.
3. Verify — Determine whether the expected outcome has been obtained.
4. Tear down — Tear down the test fixture to return to the original state.

[edit] Use of fixtures

Some advantages of fixtures include separation of the test initialization (and destruction) from the testing, reusing a known state for more than one test, and special assumption by the testing framework that the fixture set up works.

All-pairs testing or pairwise testing is a combinatorial software testing method that, for each pair of input parameters to a system (typically, a software algorithm), tests all possible discrete combinations of those parameters. Using carefully chosen test vectors, this can be done much faster than an exhaustive search of all combinations of all parameters, by “parallelizing” the tests of parameter pairs.

The reasoning behind all-pairs testing is this: the simplest bugs in a program are generally triggered by a single input parameter. The next simplest category of bugs consists of those dependent on interactions between pairs of parameters, which can be caught with all-pairs testing.[1] Bugs involving interactions between three or more parameters are progressively less common[2], whilst at the same time being progressively more expensive to find by exhaustive testing, which has as its limit the exhaustive testing of all possible inputs.

The 1×1 strategy is sufficient for detecting boundary errors and the Nx1 strategy is effective foretermining exactly what type of boundary error is present, where N is the dimension of the input space.  The 1×1 strategy tests two points for each boundary inequality, one on the boundary and one off the boundary.  The two points are chosen as close as possible to one another to ensure that domain shift errors are properly detected. If two domainsshare a boundary, then the off point is always in the domain that is open with respect to that boundary.

The Nx1 strategy tests N+1 points for each boundary inequality, N points on the boundary and 1 point off the boundary. The off point is chosen at or near the centroid of the on points. One must always be careful to choose the off point so that it is in a valid domain, i.e. one that leads to valid computations or to a specific error condition, otherwise the point may be
rejected for coincidental reasons, e.g. by an initial analysis that rejects all points not in a domain that leads to subsequent processing.

In cryptography, a zero-knowledge proof or zero-knowledge protocol is an interactive method for one party to prove to another that a (usually mathematical) statement is true, without revealing anything other than the veracity of the statement.