Data Structures & Algorithm Analysis in C++

methods of organizing large amounts of data, and algorithm analysis, the estimation of the<br>running time of algorithms. As computers become faster and faster, the need for programs<br>that can handle large amounts of input becomes more acute. Paradoxically, this requires<br>more careful attention to efficiency, since inefficiencies in programs become most obvious<br>when input sizes are large. By analyzing an algorithm before it is actually coded, students<br>can decide if a particular solution will be feasible. For example, in this text students look at<br>specific problems and see how careful implementations can reduce the time constraint for<br>large amounts of data from centuries to less than a second. Therefore, no algorithm or data<br>structure is presented without an explanation of its running time. In some cases, minute<br>details that affect the running time of the implementation are explored.<br>Once a solution method is determined, a program must still be written. As computers<br>have become more powerful, the problems they must solve have become larger and more<br>complex, requiring development of more intricate programs. The goal of this text is to teach<br>students good programming and algorithm analysis skills simultaneously so that they can<br>develop such programs with the maximum amount of efficiency.<br>This book is suitable for either an advanced data structures course or a first-year<br>graduate course in algorithm analysis. Students should have some knowledge of intermediate<br>programming, including such topics as pointers, recursion, and object-based<br>programming, as well as some background in discrete math.