Search Results for "python data analysis" - Page 2

A collection of software benchmarks developed to compare the performance of Java with C on identical code. No language libraries were used to avoid implementation differences. Some of the benchmarks are also implemented in Python and Scala. There are benchmarks for bit twiddling, numerical computing, data structure manipulation, concurrent computing, callouts to native libraries, and, graphics processing units (GPU) utilization.

Highly efficient Data Generator for Benchmarks and Algorithm Performance Analysis. Supports fully configurable schemata as well as meta structures like Foreign Keys and Functional Dependencies.

A Python programming environment providing memory sizing, profiling and analysis, and a specification language that can formally specify aspects of Python programs and generate tests and documentation from a common source.

jMINT is a integration fault injection tool which identifies data exchanges across classes and inject faults along those path. It is primarily based on the idea of program analysis and code mutation. The cross boundary data exchanges are identified by performing data flow analysis using java byte code analysis and transformation framework-soot. Mutant injection is also done via the soot framework. jMINT tool can be used to measure the effectiveness of integration test suites.

aim is to provide support for monitoring system behaviour through dynamic analysis, and for analysing and modeling this data for a better understanding of system behaviour and for test automation

The csvdatamix project aims to randomize CSV input data files in order to conceal the original state of the data. Similar to data masking or data transformation. Also has mapping abilities to translate back to the original state of the data.

Justus is a tool set for Progress 4GL (ABL) Developers. It includes a simplified parser for 4GL, an API to load Profiler data and a Test Coverage Tool.

Siafu simulates individual agents and their context, from home to city-wide scenarios. As a developer, you use the API to write your simulation for the purposes of data-set generation, test or visualization, optionally hooking it to your own application.

This project contains a set of tools for formal verification and static analysis of VHDL design.

An eclipse plugin for code coverage visualization of JUnit Tests. Especially useful for test-first development. Supported coverages include block coverage and all-uses coverage (Data Flow Analysis).

Datamixer generates mock data values for various datatypes, including integer, floating precision, datetime, and string. It can generate complex sequences, based on functions and permutations of the basic data series.

PyMetrics produces metrics for Python programs. Metrics include McCabe's Cyclomatic Complexity metric, LoC, %Comments, etc. Users can also define their own metrics using data from PyMetrics. PyMetrics optionally outputs stdout, SQL command files and CSV

Libraries and tools to support software design using executable code as specifications, to support Test Driven Development and other Agile methods.

BugEye is an XML-based unit test creation framework. Being XML-based, it can be easily translated to almost any language. The current translations are C#, Java, JavaScript, and Visual Basic. Future translations include C++, Python, Perl, and PHP.

FormatCheck screens flat files looking for violations in the format of the data. It uses a set of XML files that define the rules for each file format. The Swing front-end allows the user to run the verification, view and print the errors.

The Open Log Engine is a powerful tool for advanced logging in games or programs. It easily allows you to make logging outputs in your program and analyse them afterwards with the Open Log Viewer, which provides you a powerful filtering system.