We describe the vision of being able to reason about the design space of data structures. 
We break this down into two questions: 1) Can we know all data structures that is possible to design?  2) Can we compute the performance of arbitrary designs on a given hardware and workload without having to implement the design or even access the target hardware?
If those challenges are possible, then an array of exciting opportunities would become feasible such as interactive what-if design to improve the productivity of data systems researchers and engineers, and informed decision making in industrial settings with regards to critical ardware/workload/data structure design issues. Then, even fully automated discovery of new data structure designs becomes possible. Furthermore, the structure of the design space itself provides numerous insights and opportunities such as the existence of design continuums that can lead to data systems with deep adaptivity, and a new understanding of the possible performance trade-offs. Given the universal presence of data structures at the very core of any data-driven field across all sciences and industries, reasoning about their design can have significant benefits, making it more feasible (easier, faster and cheaper) to adopt tailored state-of-the-art storage solutions. And this effect is going to become increasingly more critical as data keeps growing, hardware keeps changing and more applications/fields realize the transformative power and potential of data analytics.  
This paper presents this vision and surveys first steps that demonstrate its feasibility. 

GNU recutils is a set of tools and libraries to access human-editable, text-based databases called recfiles. The data is stored as a sequence of records, each record containing an arbitrary number of named fields. Advanced capabilities usually found in other data storage systems are supported: data types, data integrity (keys, mandatory fields, etc.) as well as the ability of records to refer to other records (sort of foreign keys). Despite its simplicity, recfiles can be used to store medium-sized databases.

Any C structure can be stored in a hash table using uthash. Just add a UT_hash_handle to the structure and choose one or more fields in your structure to act as the key. Then use these macros to store, retrieve or delete items from the hash table.

Any C structure can be stored in a hash table using uthash. Just add a UT_hash_handle to the structure and choose one or more fields in your structure to act as the key. Then use these macros to store, retrieve or delete items from the hash table.

Collections: double linked list, deque, RBtree, channels.

Data structure and algorithms are core part of any Programming job interview. It doesn't matter whether you are a C++ developer, a Java developer or a Web developer working in JavaScript, Angular, React, or Query. As a computer science graduate, its expected from a programmer to have strong knowledge of both basic data structures e.g. array, linked list, binary tree, hash table, stack, queue and advanced data structures like the binary heap, trie, self-balanced tree, circular buffer etc. I have taken a lot of Java interviews for both junior and senior positions in the past, and I have been also involved in interviewing C++ developer. One difference which I have clearly noticed between a C++ and a Java developer is their understanding and command of Data structure and algorithms.

On average, a C or C++ developer showed a better understanding and application of data structure and their coding skill was also better than Java developers. This is not a coincidence though. As per my experience, there is a direct correlation between a programmer having a good command of the algorithm also happens to be a good developer and coder.

I firmly believe that interview teaches you a lot in very short time and that's why I am sharing some frequently asked Data structure and algorithm questions from various Java interviews.

If you are familiar with them than try to solve them by hand and if you do not then learn about them first, and then solve them. If you need to refresh your knowledge of data structure and algorithms then you can also take help from a good book our course like Data Structures and Algorithms: Deep Dive Using Java for quick reference.

A library of common data structures and algorithms written in C.