A convenience wrapper around the escomplex complexity analysis tool for Node.js
Find the longest common subsequence.
Validation rule for GraphQL query complexity analysis
Tiny queue data structure
Extends LRU base on hashlru
Get an iterator for any JS language value. Works robustly across all environments, all versions.
Measure the churn/complexity score. Higher values mean hotspots where refactorings should happen.
ESLintCC is a ECMAScript/JavaScript tool that computes complexity of code by using ESLint
A library to find JS RegExp with super-linear worst-case time complexity for attack strings that repeat a single character.
Find wordy or unnecessary passages in your writing
realistic password strength estimation
Software complexity analysis of JavaScript-family abstract syntax trees.
eslint plugin for complexity-related rules
Query complexity validation for GraphQL.js
Converts an array of items with ids and parent ids to a nested tree in a performant `O(n)` way. Runs in browsers and node.
Iterate any iterable JS value. Works robustly in all environments, all versions.
TypeScript definitions for graphql-validation-complexity
Software complexity analysis for JavaScript projects
A Pothos plugin for defining and limiting complexity of queries
Provides module / individual file oriented AST processing for typhonjs-escomplex complexity reports.
LEB128 utilities for Node
Computes complexity in TypeScript / JavaScript files.
Provides project oriented AST processing for typhonjs-escomplex complexity reports.
Memorable password generator
CallableTree provides a framework for organizing complex logic into a tree of callable nodes. It allows you to chain execution from a root node to leaf nodes based on matching conditions. Key features include multiple traversal strategies: `seekable` (like nested `if`/`case`), `broadcastable` (one-to-many execution), and `composable` (pipelined processing). Supports class-based, builder-style and factory-style definitions.
This Ruby-based DSL allows you to create complex Graphviz DOT diagrams programmatically. With this DSL, you can define nodes, edges, and nested clusters that represent relationships and hierarchies visually.
YPetri is a DSL (domain-specific language) for modelling of dynamical systems. It is biologically inspired, but concerns of biology and chemistry have been purposely separated away from it. YPetri caters solely to the two main concerns of modelling, model specification and simulation, and it excels in the first one. Dynamical systems are described under a Petri net paradigm. YPetri implements a universal Petri net abstraction that integrates discrete/continous, timed/timeless and stoichiometric/nonstoichiometric dichotomies of the extended Petri nets, and allows efficient specification of any kind of dynamical system. Like Petri nets themselves, YPetri was inspired by problems from the domain of chemistry (biochemical pathway modelling), but is not specific to it. Other gems, YChem and YCell are planned to cater to the concerns specific to chemistry and cell biochemistry. A lower-level extension of YPetri is currently under development under the name YNelson. Its usage is practically identical to YPetri, so any YPetri user can now consider using YNelson instead. YNelson covers additional concerns: it allows relations among nodes and parameters to be specified under a zz structure paradigm (developed by Ted Nelson) and it is also aimed towards providing a higher level of abstraction in Petri net specification by providing commands that create more than one Petri net node per command. YPetri documentation is avalable online, but due to formatting issues, you may prefer to generate the documentation on your own by running rdoc in the gem directory. As for the user manuals, there are currently 3 documents applicable for both YPetri and YNelson, whose master copies are stored in the YNelson source directory: 1. Introduction to YNelson and YPetri (hands-on tutorial), 2. Object model of YNelson and YPetri, 3. Introduction to Ruby for YNelson users. These manuals are written to allow beginners, including those unfamiliar with Ruby, to start working with YPetri and/or YNelson. For an example of how YPetri can be used to model complex dynamical systems, see the eukaryotic cell cycle model which I released as "cell_cycle" gem.
Zz structures are an interesting way of representing relations invented by Ted Nelson, whose domain model I provide in a gem Yzz. In this gem, YNelson, I combine Yzz with the universal Petri net provided by YPetri (another gem I wrote) to obtain a hybrid data structure that formalizes and generelizes a spreadsheet. Because let us note spreadsheets (as I have seen them) can be considered Petri nets of a kind, with cell functions acting as Petri net transitions. At the same time, spreadsheets are globally orthogonal structures with 3 typical dimensions (rows, columns and sheets). By using zz structures, the globally orthogonal spreadsheet is generalized as a locally orthogonal zz structure, with relations represented as zz dimensions, thus generalizing and formalizing a spreadsheet. The catch is that I have not yet finished the thinking process regarding what everything should be a zz object: Places (cells) and transitions definitely yes, but how about nets and dimensions? Should YNelson go as far as making namespaces into zz objects? The reason why these questions are hard to answer is because Ted Nelson himself, while providing interfaces guidelines (zz structure views, cursors...) did not comment on these questions. While being a (textual) DSL, YNelson aims to provide convenience on par with actual spreadsheet apps. Unlike YPetri, YNelson also aims to be able to specify more than one Petri net node per command, but this is still under development. See the user guide and the documentation for the details. YNelson documentation is available online, but due to formatting issues, you may prefer to generate the documentation on your own by running rdoc in the gem directory. For an example of how YPetri can be used to model complex dynamical systems, see the eukaryotic cell cycle model which I released as "cell_cycle" gem.