This practical book offers programmers the knowledge and code they need to create cutting-edge mobile applications, using Apple’s iPhone SDK. The iPhone is one of the hottest new pieces of technology: a fully functional portable Unix operating system with the most advanced handheld user interface in existence. iPhone SDK Application Development covers development environment for both the iPhone and iPod Touch, from windows and navigation bars to more advanced layers of the iPhone SDK, such as screen transitions, low-level graphics rendering using CoreSurface, the MultiTouch API, and digital sound and music rendering with Celestial and CoreAudio. With this book, you will:
Understand how the iPhone works internally, with a complete introduction to the technology Learn how different iPhone components interact with each other Use your existing Mac OS X development skills by understanding the similarities between iPhone and Mac OS X Leopard Learn about the iPhone-specific APIs, such as the user interface, to develop custom iPhone applications Get code examples to help you write various features of your application
With iPhone SDK Application Development, you’ll learn how to create effective iPhone applications and games with the same tools Apple uses.
About the Author
Jonathan Zdziarski is better known as the hacker “NerveGas” in the iPhone development community. He is well known for his work in cracking the iPhone and lead the effort to port the first open source applications. Hailed on many geek news sites for his accomplishments, Jonathan is best known for the first application to illustrate and take full advantage of the major iPhone APIs: NES.app, a portable Nintendo Entertainment System emulator.
Jonathan is also a full-time research scientist and longtime spam-fighter. He is founder of the DSPAM project, a high profile, next-generation spam filter that was acquired in 2006 by a company designing software accelerators. He lectures widely on the topic of spam and is a foremost researcher in the fields of machine-learning and algorithmic theory.