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At the same time, Simon Stewart at ThoughtWorks developed a superior browser automation tool called WebDriver. In 2009, after a meeting between the developers at the Google Test Automation Conference, it was decided to merge the two projects, and call the new project Selenium WebDriver, or Selenium 2.0. [7]
Pseudolocalization (or pseudo-localization) is a software testing method used for testing internationalization aspects of software. Instead of translating the text of the software into a foreign language, as in the process of localization, the textual elements of an application are replaced with an altered version of the original language. For ...
The terms are frequently abbreviated to the numeronyms i18n (where 18 stands for the number of letters between the first i and the last n in the word internationalization, a usage coined at Digital Equipment Corporation in the 1970s or 1980s) [2] [3] and l10n for localization, due to the length of the words.
WOUnit (JUnit), TestNG, Selenium in Project WONDER Yes Yes Yes Google Web Toolkit: Java, JavaScript Yes Yes JPA with RequestFactory JUnit (too early), jsUnit (too difficult), Selenium (best) via Java Yes Bean Validation ZK: Java, ZUML jQuery: Yes Push-pull Yes any J2EE ORM framework JUnit, ZATS HibernateUtil, SpringUtil Spring Security
Website localization is the process of adapting an existing website to local language and culture in the target market. [1] It is the process of adapting a website into a different linguistic and cultural context [ 2 ] — involving much more than the simple translation of text.
Location-based service (LBS) is a general term denoting software services which use geographic data and information to provide services or information to users. [1] LBS can be used in a variety of contexts, such as health, indoor object search, [2] entertainment, [3] work, personal life, etc. [4] Commonly used examples of location-based services include navigation software, social networking ...
2005 DARPA Grand Challenge winner Stanley performed SLAM as part of its autonomous driving system. A map generated by a SLAM Robot. Simultaneous localization and mapping (SLAM) is the computational problem of constructing or updating a map of an unknown environment while simultaneously keeping track of an agent's location within it.
The above examples of localization of R-modules is abstracted in the following definition. In this shape, it applies in many more examples, some of which are sketched below. Given a category C and some class W of morphisms in C, the localization C[W −1] is another category which is obtained by inverting all the morphisms in W.