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This book is designed to help you make the most effective use of the Java programming language and its fundamental libraries, javalang, javautil, and, to a lesser extent, javaio The book discusses other libraries from time to time, but it does not cover graphical user interface programming or enterprise APIs This book consists of fifty-seven items, each of which conveys one rule The rules capture practices generally held to be beneficial by the best and most experienced programmers The items are loosely grouped into nine chapters, each concerning one broad aspect of software design The book is not intended to be read from cover to cover: Each item stands on its own, more or less The items are heavily cross-referenced so you can easily plot your own course through the book Most items are illustrated with program examples A key feature of this book is that it contains code examples illustrating many design patterns and idioms Some are old, like Singleton (Item 2), and others are new, like Finalizer Guardian (Item 6) and Defensive readResolve (Item 57) A separate index is provided for easy access to these patterns and idioms (page 239) Where appropriate, they are cross-referenced to the standard reference work in this area [Gamma95] Many items contain one or more program examples illustrating some practice to be avoided Such examples, sometimes known s antipatterns, are clearly labeled with a comment such as // Never do this! In each case, the item explains why the example is bad and suggests an alternative approach This book is not for beginners: it assumes that you are already comfortable with the Java programming language If you are not, consider one of the many fine introductory texts [Arnold00, Campione00] While the book is designed to be accessible to anyone with a working knowledge of the language, it should provide food for thought even for advanced programmers Most of the rules in this book derive from a few fundamental principles Clarity and simplicity are of paramount importance The user of a module should never be surprised by its behavior Modules should be as small as possible but no smaller (As used in this book, the term module refers to any reusable software component, from an individual method to a complex system consisting of multiple packages) Code should be reused rather than copied The dependencies between modules should be kept to a minimum Errors should be detected as soon as possible after they are made, ideally at compile time While the rules in this book do not apply 100 percent of the time, they do characterize best programming practices in the great majority of cases You should not slavishly follow these rules, but you should violate them only occasionally and with good reason Learning the art of programming, like most other disciplines, consists of first learning the rules and then learning when to violate them For the most part, this book is not about performance It is about writing programs that are clear, correct, usable, robust, flexible, and maintainable If you can do that, it's usually a relatively simple matter to get the performance you need (Item 37) Some items do discuss performance concerns, and a few of these items provide performance numbers These.

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MOBILE SENSOR NETWORKS DEPLOYMENT in NET Draw Denso QR barcode in net generate, create barcode none in However, in this deployment algorithm the map is built ntirely from live, rather than stored, sensory data It also satis es an additional constraint: that each node must be visible to at least one other node Multi-robot exploration and map-building has been explored by a number of authors [100,106,109,111] who use a variety of techniques ranging from topological matching [100] to fuzzy inference [106] and particle lters [111] Once again, there are two key differences between these earlier works and the work described in Howard et al [98], where maps are built entirely from live, not stored, sensory data, and the deployment algorithm must satisfy an additional constraint (ie line-of-sight visibility).

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In 1996 I pulled up stakes and headed west to work for JavaSoft, as it was then known, because it was clear that that was where the action was In the intervening five years I've served as Java platform libraries architect I've designed, implemented, and maintained many of the libraries and served as a consultant for many others Presiding over these libraries as the Java platform matured was a once-in-a-lifetime opportunity It is no exaggeration to say that I had the privilege to work with some of the great software engineers of our generation In the process, I learned a lot about the Java programming language what works, what doesn't, and how to use the language and its libraries to best effect This book is my attempt to share my experience with you so that you can imitate my successes while avoiding my failures I borrowed the format from Scott Meyers's Effective C++ [Meyers98], which consists of fifty items, each conveying one specific rule for improving your programs and designs I found the format to be singularly effective, and I hope you do too In many cases, I took the liberty of illustrating the items with real-world examples from the ava platform libraries When describing something that could have been done better, I tried to pick on code that I wrote myself, but occasionally I pick on something written by a colleague I sincerely apologize if, despite my best efforts, I've offended anyone Negative examples are cited not to cast blame but in the spirit of cooperation, so that all of us can benefit from the experience of those who've gone before While this book is not targeted solely at developers of reusable components, it is inevitably colored by my experience writing such components over the past two decades I naturally think in terms of exported APIs (Application Programming Interfaces), and I encourage you to do likewise Even if you aren't developing reusable components, thinking in these terms tends to improve the quality of the software you write Furthermore, it's not uncommon to write a reusable component without knowing it: You write something useful, share it with your buddy across the hall, and before long you have half a dozen users At this point, you no longer have the flexibility to change the API at will and are thankful for all the effort that you put into designing the API when you first wrote the software My focus on API design may seem a bit unnatural to devotees of the new lightweight software development methodologies, such as Extreme Programming [Beck99] These methodologies emphasize writing the simplest program that could possibly work If you're using one of these methodologies, you'll find that a focus on API design serves you well in the refactoring process The fundamental goals of refactoring are the improvement of system structure and the avoidance of code duplication These goals are impossible to achieve in the absence of well-designed APIs for the components of the system No language is perfect, but some are excellent I have found the Java programming language and its libraries to be immensely conducive to quality and productivity, and a joy to work with I hope this book captures my enthusiasm and helps make your use of the language more effective and enjoyable Joshua Bloch Cupertino, April 2001 California.

A distributed algorithm for the deployment of mobile robot teams has been described in [108], where the concept of virtual pheromones is introduced These are localized messages that are emitted by one robot and detected by nearby robots Virtual pheromones can be used to generate either gas expansion or guided growth deployment models The key advantage of this approach is that the deployment algorithm is entirely distributed, and has the potential to respond dynamically to changes in the environment This algorithm does, however, lead to relatively slow deployment; it is also unclear, from the published results, how effective this algorithm is at producing good area coverage A somewhat similar algorithm based on arti cial potential elds is described in Howard et al [104].

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The algorithm elaborated in this section is an incremental deployment algorithm [98], where nodes are deployed one at a time, with each node making use of information gathered by the previously deployed nodes to determine its ideal deployment location The algorithm aims to maximize the total network coverage, ie the total area that can be seen by the network At the same time, the algorithm must ensure that the visibility constraint is satis ed, ie each node must be visible to at least one other node The algorithm relies on a number of key assumptions: (1) Homogeneous nodes all nodes are assumed to be identical We also assume that each node is equipped with a range sensor, a broadcast communications device, and is mounted on some form of mobile platform.

Effective Java: Programming Language Guide. QR Code 2d Barcode .So what, if anything, are finalizers good for There are two legitimate uses One is to act as a safety net in case the owner of an object forgets to call the explicit termination method that you provided per the advice in the previous paragraph While there's no guarantee that the finalizer will get invoked promptly, it's better to free the critical resource late than never, in those (hopefully rare) cases when the client fails to hold up its end of the bargain by calling the explicit termination method The three classes mentioned as examples of the xplicit. Code-128 In Java Using Barcode printer for Java .Related: Interleaved 2 of 5 Generating .NET , Generate UPC-E Excel , C# EAN 128 Generator

(2) Static environment the environment is assumed to be static, at least to the extent that gross topology remains unchanged while the network is deploying (3) Model-free this algorithm is intended for applications in which environment models are unavailable; indeed, a key task for the network may be to generate such models (4) Full communication all nodes in the network can communicate with some remote base station on which the deployment algorithm is executed Note that this does not automatically imply that all nodes must be within radio range of the base station; the nodes may, for example, form an ad hoc multihop network (5) Localization the position of each node is known in some arbitrary global coordinate system This technique does not require external landmarks or prior models of the environment, but does require that each node is visible to at least one other node.

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