Best Application Development Software for Windows - Page 32
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Compare the Top Application Development Software for Windows as of October 2025 - Page 32
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1
Apache TomEE
Apache
Apache TomEE, pronounced “Tommy”, is an all-Apache Jakarta EE 9.1 certified application server that extends Apache Tomcat that is assembled from a vanilla Apache Tomcat zip file. We start with Apache Tomcat, add our jars, and zip up the rest. The result is Tomcat plus EE features, TomEE. Stable and ready for production, Apache TomEE 8.0 implements Java EE 8/Jakarta EE 8 and supports the javax namespace. Runs on Java 8 or higher. Mostly Jakarta EE 9.1 web profile compliant and supports the new jakarta namespace. Runs on Java 11 or higher. Apache TomEE comes in four different flavors, web profile, MicroProfile, Plus and Plume. Apache TomEE web profile delivers servlets, JSP, JSF, JTA, JPA, CDI, bean validation and EJB Lite. Apache TomEE MicroProfile adds support for MicroProfile. Apache TomEE Plus and Plume add support for JMS, JAX-WS, and more. Mostly Jakarta EE 9.1 Web Profile compliant and supports the new jakarta namespace.Starting Price: Free -
2
Apache Geronimo
Apache
Apache Geronimo is an open-source set of projects that are focused on providing JavaEE/JakartaEE libraries and Microprofile implementations. We are actively delivering reusable Java EE components though. They are widely used and still actively maintained! Apache Geronimo provides libraries for the implementations of the Java EE and Jakarta EE specifications. The implementations are also focused on providing OSGi bundle metadata. The goal of XBean project is to create a plugin-based server analogous to Eclipse is a plugin-based IDE. XBean will be able to discover, download and install server plugins from an Internet-based repository. In addition, we include support for multiple IoC systems, support for running with no IoC system, JMX without JMX code, lifecycle and class loader management, and rock-solid Spring integration. Apache Geronimo hosts several Microprofile implementations. Apache Geronimo Arthur is an effort to build a thin layer on top of Oracle GraalVM.Starting Price: Free -
3
Pulsar
Pulsar-Edit
A community-led hyper-hackable text editor. Pulsar works across operating systems. Use it on OS X, Windows, or Linux. Search and install new packages or create your own right from Pulsar. Pulsar helps you write code faster with a smart and flexible autocomplete. Easily browse and open a single file, a whole project, or multiple projects in one window. Split your Pulsar interface into multiple panes to compare and edit code across files. Find, preview, and replace text as you type in a file or across all your projects.Starting Price: Free -
4
Devel::Cover
metacpan
This module provides code coverage metrics for Perl. Code coverage metrics describe how thoroughly tests exercise code. By using Devel::Cover you can discover areas of code not exercised by your tests and determine which tests to create to increase coverage. Code coverage can be considered an indirect measure of quality. Devel::Cover is now quite stable and provides many of the features to be expected in a useful coverage tool. Statement, branch, condition, subroutine, and pod coverage information is reported. Statement and subroutine coverage data should be accurate. Branch and condition coverage data should be mostly accurate too, although not always what one might initially expect. Pod coverage comes from Pod::Coverage. If Pod::Coverage::CountParents is available it will be used instead.Starting Price: Free -
5
LuaCov
LuaCov
LuaCov is a simple coverage analyzer for Lua scripts. When a Lua script is run with the luacov module loaded, it generates a stats file with the number of executions of each line of the script and its loaded modules. The luacov command-line script then processes this file generating a report file which allows one to visualize which code paths were not traversed, which is useful for verifying the effectiveness of a test suite. LuaCov includes several configuration options, which have their defaults stored in src/luacov/defaults.lua. These are the global defaults. To use project specific configuration, create a Lua script setting options as globals or returning a table with some options and store it as .luacov in the project directory from where luacov is being run. For example, this config informs LuaCov that only foo module and its submodules should be covered and that they are located inside src directory.Starting Price: Free -
6
Tarpaulin
Tarpaulin
Tarpaulin is a code coverage reporting tool for the cargo build system, named for a waterproof cloth used to cover cargo on a ship. Currently, tarpaulin provides working line coverage and while fairly reliable may still contain minor inaccuracies in the results. A lot of work has been done to get it working on a wide range of projects, but often unique combinations of packages and build features can cause issues so please report anything you find that's wrong. Also, check out our roadmap for planned features. On Linux Tarpaulin's default tracing backend is still Ptrace and will only work on x86 and x64 processors. This can be changed to the llvm coverage instrumentation with engine llvm, for Mac and Windows this is the default collection method. It can also be run in Docker, which is useful for when you don't use Linux but want to run it locally.Starting Price: Free -
7
grcov
grcov
grcov collects and aggregates code coverage information for multiple source files. grcov processes .profraw and .gcda files which can be generated from llvm/clang or gcc. grcov also processes lcov files (for JS coverage) and JaCoCo files (for Java coverage). Linux, macOS and Windows are supported.Starting Price: Free -
8
kcov
kcov
Kcov is a FreeBSD/Linux/OSX code coverage tester for compiled languages, Python and Bash. Kcov was originally a fork of Bcov, but has since evolved to support a large feature set in addition to that of Bcov. Kcov, like Bcov, uses DWARF debugging information for compiled programs to make it possible to collect coverage information without special compiler switches.Starting Price: Free -
9
test_coverage
pub.dev
A simple command-line tool to collect test coverage information from Dart VM tests. It is useful if you need to generate coverage reports locally during development.Starting Price: Free -
10
coverage
pub.dev
Coverage provides coverage data collection, manipulation, and formatting for Dart. Collect_coverage collects coverage JSON from the Dart VM Service. format_coverage formats JSON coverage data into either LCOV or pretty-printed format.Starting Price: Free -
11
scct
scct
Mainly, a better-lookin' report UI, a simpler maven configuration. Add the plugin instrumentation settings to child projects and the report merging settings to the parent project.Starting Price: Free -
12
cloverage
cloverage
Cloverage uses clojure.test by default. If you prefer use midje, pass the --runner :midje flag. (In older versions of Cloverage, you had to wrap your midje tests in clojure.test's deftest. This is no longer necessary.) For using eftest, pass the --runner :eftest flag. Optionally you could configure a runner passing :runner-opts with a map in project settings. Other test libraries may ship with their own support for Cloverage external to this library; see their documentation for details.Starting Price: Free -
13
Slather
Slather
Generate test coverage reports for Xcode projects & hook it into CI. Enable test coverage by ticking the "Gather coverage data" checkbox when editing a scheme.Starting Price: Free -
14
QML
Qt
QML is a declarative language that allows user interfaces to be described in terms of their visual components and how they interact and relate with one another. It is a highly readable language that was designed to enable components to be interconnected in a dynamic manner, and it allows components to be easily reused and customized within a user interface. Using the QtQuick module, designers and developers can easily build fluid animated user interfaces in QML, and have the option of connecting these user interfaces to any back-end C++ libraries. QML is a user interface specification and programming language. It allows developers and designers alike to create highly performant, fluidly animated and visually appealing applications. QML offers a highly readable, declarative, JSON-like syntax with support for imperative JavaScript expressions combined with dynamic property bindings.Starting Price: Free -
15
SystemC
SystemC
Your online reference for everything related to SystemC, the language for system-level design, high-level synthesis, modeling and verification. SystemC™ addresses the need for a system design and verification language that spans hardware and software. It is a language built in standard C++ by extending the language with the use of class libraries. The language is particularly suited to model system's partitioning, to evaluate and verify the assignment of blocks to either hardware or software implementations, and to architect and measure the interactions between and among functional blocks. Leading companies in the intellectual property (IP), electronic design automation (EDA), semiconductor, electronic systems, and embedded software industries currently use SystemC for architectural exploration, to deliver high-performance hardware blocks at various levels of abstraction and to develop virtual platforms for hardware/software co-design.Starting Price: Free -
16
Coco
Qt Group
Linux, Windows, RTOS and others. Using gcc, Visual Studio, embedded compilers and more. Merging multiple execution reports to provide advanced analysis and more outstanding features. Assess and optimize code performance with Coco’s built-in Function Profiler.Starting Price: $302 per month -
17
NCover
NCover
NCover Desktop is a Windows application that helps you collect code coverage statistics for .NET applications and services. After coverage is collected, Desktop displays charts and coverage metrics in a browser-based GUI that allows you to drill all the way down to your individual lines of source code. Desktop also allows you the option to install a Visual Studio extension called Bolt. Bolt offers built-in code coverage that displays unit test results, timings, branch visualization and source code highlighting right in the Visual Studio IDE. NCover Desktop is a major leap forward in the ease and flexibility of code coverage tools. Code coverage, gathered while testing your .NET code, shows the NCover user what code was exercised during the test and gives a specific measurement of unit test coverage. By tracking these statistics over time, you gain a concrete measurement of code quality during the development cycle.Starting Price: Free -
18
dotPeek
JetBrains
As soon as you've decompiled an assembly, you can save it as a Visual Studio project (.csproj). This can potentially save a lot of time if you need to restore lost source code from a legacy assembly. dotPeek can identify local source code based on PDB files, or fetch source code from source servers such as Microsoft Reference Source Center or SymbolSource. dotPeek can also perform as a symbol server and supply Visual Studio debugger with the information required to debug assembly code. dotPeek inherits a lot of features from ReSharper. These include contextual and context-insensitive navigation, usage search, as well as different code structure and hierarchy views. Use Find Usages to search for all usages of a symbol, be it a method, property, local variable or a different entity. The Find Results tool window lets you group usages, navigate between them, and open them in the code view area.Starting Price: Free -
19
JaCoCo
EclEmma
JaCoCo is a free code coverage library for Java, which has been created by the EclEmma team based on the lessons learned from using and integrating existing libraries for many years. The master branch of JaCoCo is automatically built and published. Due to the test-driven development approach, every build is considered fully functional. See the change history for the latest features and bug fixes. SonarQube code quality metrics of the current JaCoCo implementation are available on SonarCloud.io. Integrate JaCoCo technology with your tools. Use JaCoCo tools out of the box. Improve the implementation and add new features. There are several open-source coverage technologies for Java available. While implementing the Eclipse plug-in EclEmma the observation was that none of them are really designed for integration. Most of them are specifically fit to a particular tool (Ant tasks, command line, IDE plug-in) and do not offer a documented API that allows embedding in different contexts.Starting Price: Free -
20
OpenClover
OpenClover
Balance your effort spent on writing applications and test code. Use the most sophisticated code coverage tool for Java and Groovy. OpenClover measures code coverage for Java and Groovy and collects over 20 code metrics. It not only shows you untested areas of your application but also combines coverage and metrics to find the riskiest code. The Test Optimization feature tracks which test cases are related to each class of your application code. Thanks to this OpenClover can run tests relevant to changes made in your application code, significantly reducing test execution time. Do testing getters and setters bring much value? Or machine-generated code? OpenClover outruns other tools in its flexibility to define the scope of coverage measurement. You can exclude packages, files, classes, methods, and even single statements. You can focus on testing important parts of your code. OpenClover not only records test results but also measures individual code coverage for every test.Starting Price: Free -
21
JCov
OpenJDK
The JCov open-source project is used to gather quality metrics associated with the production of test suites. JCov is being opened in order to facilitate the practice of verifying test execution of regression tests in OpenJDK development. The main motivation behind JCov is the transparency of test coverage metrics. The advantage to promoting standard coverage based on JCov is that OpenJDK developers will be able to use a code coverage tool that stays in the 'lock step' with Java language and VM developments. JCov is a pure java implementation of a code coverage tool that provides a means to measure and analyze dynamic code coverage of Java programs. JCov provides functionality to collect method, linear block, and branch coverage, as well as show uncovered execution paths. It is also able to show a program's source code annotated with coverage information. From a testing perspective, JCov is most useful to determine execution paths.Starting Price: Free -
22
Istanbul
Istanbul
JavaScript test coverage made simple. Istanbul instruments your ES5 and ES2015+ JavaScript code with line counters, so that you can track how well your unit-tests exercise your codebase. The nyc command-line-client for Istanbul works well with most JavaScript testing frameworks, tap, mocha, AVA, etc. First-class support of ES6/ES2015+ using babel-plugin-Istanbul. Support for the most popular JavaScript testing frameworks. Support for instrumenting subprocesses, using the nyc command-line interface. Adding coverage to your mocha tests could not be easier. Now, simply place the command nyc in front of your existing test command. nyc's instrument command can be used to instrument source files outside of the context of your unit tests. nyc is able to show you all Node processes that are spawned when running a test script under it. By default, nyc uses Istanbul's text reporter. However, you may specify an alternative reporter.Starting Price: Free -
23
blanket.js
Blanket.js
A seamless JavaScript code coverage library. Blanket.js is a code coverage tool for JavaScript that aims to be easy to install, easy to use, and easy to understand. Blanket.js can be run seamlessly or can be customized for your needs. JavaScript code coverage compliments your existing JavaScript tests by adding code coverage statistics (which lines of your source code are covered by your tests). Parsing the code using Esprima and node-falafel, and instrumenting the file by adding code tracking lines. Connecting to hooks in the test runner to output the coverage details after the tests have been completed. A Grunt plugin has been created to allow you to use Blanket like a "traditional" code coverage tool (creating instrumented copies of physical files, as opposed to live-instrumenting). Runs the QUnit-based Blanket report headlessly using PhantomJS. Results are displayed on the console, and the task will cause Grunt to fail if any of your configured coverage thresholds are not met.Starting Price: Free -
24
jscoverage
jscoverage
jscoverage tool, both node.js and JavaScript support. Enhance the coverage range. Use mocha to load the jscoverage module, then it works. jscoverage will append coverage info when you select list or spec or tap reporter in mocha. You can use covout to specify the reporter, like HTML, and detail. The detail reporter will print the uncovered code in the console directly. Mocha runs test case with jscoverage module. jscoverage will ignore files while listing in covignore file. jscoverage will output a report in HTML format. jscoverage will inject a group of functions into your module exports. default jscoverage will search covignore in the project root. jscoverage will copy exclude files from the source directory to the destination directory.Starting Price: Free -
25
SimpleCov
SimpleCov
SimpleCov is a code coverage analysis tool for Ruby. It uses Ruby's built-in Coverage library to gather code coverage data, but makes processing its results much easier by providing a clean API to filter, group, merge, format, and display those results, giving you a complete code coverage suite that can be set up with just a couple lines of code. SimpleCov/Coverage track covered ruby code, gathering coverage for common templating solutions like erb, slim, and haml is not supported. In most cases, you'll want overall coverage results for your projects, including all types of tests, Cucumber features, etc. SimpleCov automatically takes care of this by caching and merging results when generating reports, so your report actually includes coverage across your test suites and thereby gives you a better picture of blank spots. SimpleCov must be running in the process that you want the code coverage analysis to happen on.Starting Price: Free -
26
UndercoverCI
UndercoverCI
Actionable test coverage for Ruby and GitHub. Checks and insights to help your team ship healthy code while saving time on PR reviews. Stop focusing on getting to 100% test coverage. Reduce pull request defects by telling when the changed code is untested before it's deployed to production. The CI server runs tests and uploads coverage data to UndercoverCI. That's the only required post-install setup step! We scan the PR diff and verify local test coverage for each updated class, method, and block because an absolute percentage check is not enough. Reveal untested methods and blocks, find unused code paths, and improve your test suite. Install UndercoverCI's hosted GitHub App or explore the Ruby gems family. Fully-featured GitHub App code review integration with quick setup for your organization. The UndercoverCI project and related Ruby gems are entirely open-source and free to use locally and in your CI/CD workflows.Starting Price: $49 per month -
27
DeepCover
DeepCover
Deep Cover aims to be the best coverage tool for Ruby code. More accurate line coverage, and branch coverage. It can be used as a drop-in replacement for the built-in Coverage library. It reports a more accurate picture of your code usage. In particular, a line is considered covered if and only if it is entirely executed. Optionally, branch coverage will detect if some branches are never taken. MRI considers every method defined, including methods defined on objects or via define_method, class_eval, etc. For Istanbul output, DeepCover has a different approach and covers all def and all blocks. DeepCover doesn't consider loops to be branches, but it's easy to support them if needed. Even after DeepCover is required and configured, only a very minimal amount of code is actually loaded and coverage is not started. To make it easier to transition for projects already using the builtin Coverage library deep-cover can inject itself into those tools.Starting Price: Free -
28
pytest-cov
Python
This plugin produces coverage reports. Compared to just using coverage run this plugin does some extras. Subprocess support, so you can fork or run stuff in a subprocess and will get covered without any fuss. Xdist support, so you can use all of pytest-xdist’s features and still get coverage. Consistent pytest behavior. All features offered by the coverage package should work, either through pytest-cov’s command line options or through coverage’s config file. Under certain scenarios, a stray .pth file may be left around in site packages. The data file is erased at the beginning of testing to ensure clean data for each test run. If you need to combine the coverage of several test runs you can use the --cov-append option to append this coverage data to coverage data from previous test runs. The data file is left at the end of testing so that it is possible to use normal coverage tools to examine it.Starting Price: Free -
29
V Programming Language
V Programming Language
Simple, fast, safe, and compiled. For developing maintainable software. Simple language for building maintainable programs. You can learn the entire language by going through the documentation over a weekend, and in most cases, there's only one way to do something. This results in simple, readable, and maintainable code. This results in simple, readable, and maintainable code. Despite being simple, V gives a lot of power to the developer and can be used in pretty much every field, including systems programming, webdev, gamedev, GUI, mobile, science, embedded, tooling, etc. V is very similar to Go. If you know Go, you already know 80% of V. Bounds checking, No undefined values, no variable shadowing, immutable variables by default, immutable structs by default, option/result and mandatory error checks, sum types, generics, and immutable function args by default, mutable args have to be marked on call.Starting Price: Free -
30
XCTest
Apple
Create and run unit tests, performance tests, and UI tests for your Xcode project. Use the XCTest framework to write unit tests for your Xcode projects that integrate seamlessly with Xcode's testing workflow. Tests assert that certain conditions are satisfied during code execution, and record test failures (with optional messages) if those conditions aren’t satisfied. Tests can also measure the performance of blocks of code to check for performance regressions and can interact with an application's UI to validate user interaction flows. A test method is a small, self-contained method that tests a specific part of your code. A test case is a group of related test methods. Add test cases and test methods to a test target to confirm that your code performs as expected. The primary class for defining test cases, test methods, and performance tests. An abstract base class for creating, managing, and executing tests.Starting Price: Free