| Best Sellers Rank | #89,039 in Books (See Top 100 in Books) #6 in Computer Programming Structured Design #11 in Programming Algorithms #17 in Computer Systems Analysis & Design (Books) |
| Customer Reviews | 4.7 out of 5 stars 842Reviews |
Descriptions of algorithms are based on complete implementations and on a discussion of the operations of these programs on a consistent set of examples. Instead of presenting pseudo-code, Sedgewick and Wayne work with real code, so that the programs can quickly be put to practical use. Programs are written in Java, but in a style such that most of the code can be reused to develop implementations in other modern programming languages.
Sedgewick and Wayne use a modern programming style based on data abstraction, so that algorithms and their data structures are encapsulated together.
Each chapter has a detailed description of applications where the algorithms described play a critical role. These range from applications in physics and molecular biology, to engineering computers and systems, to familiar tasks such as data compression and searching on the web.
The emphasizes developing mathematical models for describing the performance of algorithms, using the models to develop hypotheses about performance, and then testing the hypotheses by running the algorithms in realistic contexts.
Segewick and Wayne’s primary goal is to introduce the most important algorithms in use today to as wide an audience as possible. These algorithms are generally ingenious creations that, remarkably, can each be expressed in just a dozen or two lines of code. As a group, they represent problem-solving power of amazing scope. They have enabled the construction of computational artifacts, the solution of scientific problems, and the development of commercial applications that would not have been feasible without them.
They cover basic abstract data types, sorting algorithms, searching algorithms, graph processing, and string processing. They keep the material in algorithmic context, describing data structures, algorithm design paradigms, reduction, and problem-solving models. They cover classic methods that have been taught since the 1960s and new methods that have been invented in recent years.
