Interview question: What is the difference between final, finally, and finalize in Java?
We have decided here at Algorithmic Complexity we will be launching an online store to purchase our Big-O cheat sheet, Big-O cheat sheet posters, various computer science themed t-shirts, and eventually study software for your use.
We hope to have the store launched within the next 3 months!
Thank you for sticking with us!
Graphs are such an integral part of the study of computer science, yet many people get confused about the vernacular associated with them. This is the first post in a series of posts about various data structures and algorithms.
Here are some common terms associated with graphs you should know:
Thank you everybody for being so patient with us as we continue to flush out the site. We hope to have most of the algorithms and data structures complete by the end of April 2016! If you can’t wait, please purchase our Big-O Complexity Cheat Sheet today! The cost of the sheet helps support this site and the volunteers who work on it. Again, if you cannot afford to purchase the cheat sheet, contact us and we will get it to you for absolutely free!
After many discussions with the stakeholders of this site, it has been decided that the blog will be expanded to include more articles about software development and computer science. We plan on covering multiple topics such as in-depth look at algorithms, algorithm research, new algorithms, data structures, high performance code, software engineer practices, software job interview tips, and design patterns.
2016 is looking to be a great year at Algorithmic Complexity!
What is Timsort?
Originally invented by Tim Peters, for which it is named, in 2002 for use in the Python programming language, Timsort is considered to be a hybrid stable sorting algorithm. The reason it is considered to be a hybrid algorithm is because it combines certain facets of both merge sort and insertion sort. At a high level, the algorithm finds subsets of data that are already ordered and uses that to its advantage to sort the remaining portion of the data more efficiently.
Why know Timsort?
Besides being the defacto sorting algorithm of Python and the sorting mechanism of object arrays in Java 1.7 and newer, Timsort is one of the fastest sorting algorithms when used with real-world data. It combines the limited worst case run time performance of merge sort of O(n*log(n)) with the blazing best case performance of insertion sort of O(n).
We have just finished a major site overhaul to update the design to make it more aesthetically pleasing. We also updated several of our plug-ins to display the computational complexities of the algorithms and data structures in an easier to read fashion. Additionally, you can now sort the algorithms on the main page. Please check back often and stay tuned for future updates. Big things are coming! Thank you for your continued support and readership.
I’d like to thank everyone for their continued support of the site. We are going to be working on flushing out the remaining of the algorithms and data structures pages in the near future. We are also going to feature regular blog posts about algorithmics, data structures, job interviews, and other tips to further your understanding of computer science.
In the mean time be sure to check out our Big-O Cheat Sheet featuring the time complexities of various algorithms and data structures. Currently, we are offering the cheat sheet for $1.00 as a promotion for the next few months. Purchasing the cheat sheet helps support the site and cover hosting costs.
Over 100 people have purchased the Big-O Cheat Sheet to date. Here are some of their testimonials:
“Thank you for providing a concise summary of all the important algorithms and data structures to master for job interviews.” – Dave A. from New Jersey
“I wouldn’t have gotten my current job without your site. Thank you!” – Scott C. from Nebraska
“I love your cheat sheet!” – Dean Z. from Colorado
“I aced my test thanks to the algorithmic complexity cheat sheet.” – Howard J. from California
Again thank you to everyone who has supported the site. – Justin