Get a PDF sampler of EPI from http: //bit.ly/http: //elementsofprogramminginterviews.com/sample/ Have you ever... Wanted to work at an exciting futuristic company? Struggled with an interview problem that could have been solved in 15 minutes? Wished you could study real-world computing problems? If so, you need to read Elements of Programming Interviews (EPI). The core of EPI is a collection of 300 problems with detailed solutions, including over 100 figures and 250 tested programs. The problems are challenging, well-motivated, and accessible. They are representative of the questions asked at interviews at the most exciting companies. The book begins with a summary of patterns for data structure, algorithms, and problem solving that will help you solve the most challenging interview problems. This is followed by chapters on basic and advanced data structures, algorithm design, concurrency, system design, probability and discrete mathematics. Each chapter starts with a brief review of key concepts and results followed by a deep and wide set of questions. EPI concludes with a summary of the nontechnical aspects of interviewing, including common mistakes, strategies for a great interview, perspectives from across the table, negotiating the best offer, and much more. "This book is the best compilation of programming related problems I have seen. It is a great resource for a diverse set of topics when preparing for technical interviews, as a quick refresher in a subject area or when you are just looking for a brain teaser to challenge yourself." Shashank Gupta / Scaligent, formerly Engineering Manager, Amazon.com, Senior Engineering Manager, Yahoo!, Manager of Software Development, Cisco Systems
Adnan, Amit, and Tsung-Hsien have worked at
Google,
Facebook,
Microsoft,
IBM,
Qualcomm, and
several startups. They co-developed algorithms and systems that are used by
over one billion people everyday. They have extensive experience with interviewing candidates, making hiring decisions, and being interviewed.
Adnan Aziz is a research scientist at Facebook. Previously, he was a professor at the Department of Electrical and Computer Engineering at The University of Texas at Austin, where he conducts research and teaches classes in applied algorithms. He received his Ph.D. from The University of California at Berkeley; his undergraduate degree is from Indian Institutes of Technology Kanpur.
Amit Prakash is a founder of Thoughspot, a Silicon Valley startup. Previously, he was a Member of the Technical Staff at Google, where he worked primarily on machine learning problems that arise in the context of online advertising. Before that he worked at Microsoft in the web search team. He received his Ph.D. from The University of Texas at Austin; his undergraduate degree is from Indian Institutes of Technology Kanpur.
Tsung-Hsien Lee is a Software Engineer at Google. Previously, he worked as a Software Engineer Intern at Facebook. He received both his M.S. and undergraduate degrees from National Tsing Hua University. He has a passion for designing and implementing algorithms. He likes to apply algorithms on every aspect of his life.
