Search Results for "data collection algorithm"

google-maps-ios-utils is a collection of open-source utilities that extend the functionality of the Google Maps SDK for iOS. It provides additional features such as clustering, heatmaps, and geometry utilities to enhance map-based applications.

IGListKit uses an algorithm adapted from a paper titled A technique for isolating differences between files by Paul Heckel. This algorithm uses a technique known as the longest common subsequence to find a minimal diff between collections in linear time O(n). It finds all inserts, deletes, updates, and moves between arrays of data. A working range is a range of section controllers who aren’t yet visible, but are near the screen. Section controllers are notified of their entrance and exit...

Google Toolbox for Mac (GTMSession) is a comprehensive collection of open source Objective-C utilities and frameworks developed by Google to support macOS and iOS application development. It consolidates reusable code components drawn from various internal Google projects, offering developers a wide range of tools for building efficient, maintainable Apple platform software. The library includes modules for networking, logging, testing, data handling, and user interface extensions, helping...

... for developers working in the Apple ecosystem (Objective-C, Xcode) who want to build foundational knowledge in data structures and algorithms. By making the code accessible, it lowers the barrier to exploring algorithm performance, variant comparisons, and understanding underlying complexity. For learners, it offers a bridge between abstract algorithm descriptions in textbooks and real code you can compile, run, tweak, and visualize.

GNUexp is a GNUstep/Cocoa framework and a collection of tools helping you to plan, develop, and administer applications associated with visual psychophysics, experimental psychology and statistical data analysis.

The PowerCiph Data Encryption Algorithm is a versatile, yet simplistic, encryption algorithm/protocol. The ultimate goal of the algorithm is simplicity, compactness, and a lack of prerequisites.