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Data Structures, Algorithms, and Invariants
Data Structures, Algorithms, and Invariants: A Practical Guide provides students with the knowledge and understanding they need to make sensible decisions regarding the choice of an abstract data type (ADT) for particular use cases. The book is a practical guide that helps readers with the process of building a software application utilizing a variety of list-based, tree-based, and graph-based ADTs.The opening chapters discuss solving problems, the concept of computational complexity, different types of ADTs, and why they are needed in software development. Additional chapters address unordered, positional, and ordered ADTs, the process of sorting, ways of determining order, and graphs. Each chapter features an introduction, learning objectives, key terms, takeaways, QR codes that link out to additional content such as videos, and chapter review questions to support the reading and learning experience. Additionally, students gain access to a companion source code repository that provides implementations of many of the ADTs.Data Structures, Algorithms, and Invariants is an ideal textbook for data structure and algorithms courses in information science, data science, and programming.
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R 4,472.00
Approximation, Randomization and Combinatorial Optimization. Algorithms and Techniques
This volume contains the papers presented at the 8th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems (APPROX 2005) and the 9th International Workshop on Randomization and Computation(RANDOM2005),whichtookplaceconcurrentlyattheUniversity of California in Berkeley, on August 22-24, 2005. APPROX focuses on algori- mic and complexity issues surrounding the development of e?cient approximate solutions to computationally hard problems, and APPROX 2005 was the eighth in the series after Aalborg (1998), Berkeley (1999), Saarbru ..cken (2000), Ber- ley (2001),Rome (2002),Princeton(2003),and Cambridge(2004).RANDOM is concerned with applications of randomness to computational and combinatorial problems, and RANDOM 2005 was the ninth workshop in the series foll- ing Bologna (1997), Barcelona (1998), Berkeley(1999), Geneva (2000), Berkeley (2001), Harvard (2002), Princeton (2003), and Cambridge (2004).Topics of interest for APPROX and RANDOM are: design and analysis of approximation algorithms, hardness of approximation, small space and data streaming algorithms, sub-linear time algorithms, embeddings and metric space methods, mathematical programming methods, coloring and partitioning, cuts and connectivity, geometric problems, game theory and applications, network designandrouting,packingand covering,scheduling,designandanalysisofr- domized algorithms, randomized complexity theory, pseudorandomness and - randomization,random combinatorialstructures, randomwalks/Markovchains, expander graphs and randomness extractors, probabilistic proof systems, r- dom projections and embeddings, error-correcting codes, average-case analysis, property testing, computational learning theory, and other applications of - proximation and randomness. The volume contains 20 contributed papers selected by the APPROX P- gram Committee out of 50 submissions, and 21 contributed papers selected by the RANDOM Program Committee out of 51 submissions.
R 1,590.31
Approximation and Online Algorithms
This book constitutes the thoroughly refereed post-workshop proceedings of the 12th International Workshop on Approximation and Online Algorithms, WAOA 2014, held in Wrocław, Poland, in September 2014 as part of ALGO 2014. The 22 revised full papers presented were carefully reviewed and selected from 49 submissions. They cover a wide range of topics such as coloring and partitioning, competitive analysis, network design, packing and covering, paradigms for design and analysis of approximation and online algorithms, randomization techniques, real-world applications, and scheduling problems.
R 2,171.09
