Apache Ant vs Coveralls

Overview

Coveralls

Stacks1.7K

Followers278

Votes68

Apache Ant

Stacks250

Followers151

Votes7

GitHub Stars449

Forks449

Apache Ant vs Coveralls: What are the differences?

Developers describe Apache Ant as "Java based build tool". Ant is a Java-based build tool. In theory, it is kind of like Make, without Make's wrinkles and with the full portability of pure Java code. On the other hand, Coveralls is detailed as "Track your project's code coverage over time, changes to files, and badge your GitHub repo". Coveralls works with your CI server and sifts through your coverage data to find issues you didn't even know you had before they become a problem. Free for open source, pro accounts for private repos, instant sign up with GitHub OAuth.

Apache Ant and Coveralls are primarily classified as "Java Build" and "Code Coverage" tools respectively.

Some of the features offered by Apache Ant are:

The most complete Java build and deployment tool available.
Platform neutral and can handle platform specific properties such as file separators
Can be used to perform platform specific tasks such as modifying the modified time of a file using 'touch' command

On the other hand, Coveralls provides the following key features:

Repository Coverage Statistics
Individual File Coverage Reports
Line By Line Coverage

"Flexible" is the top reason why over 3 developers like Apache Ant, while over 44 developers mention "Free for public repositories" as the leading cause for choosing Coveralls.

Apache Ant is an open source tool with 247 GitHub stars and 254 GitHub forks. Here's a link to Apache Ant's open source repository on GitHub.

Mapbox, Practo, and Kong are some of the popular companies that use Coveralls, whereas Apache Ant is used by LinkedIn, Webedia, and Atmel. Coveralls has a broader approval, being mentioned in 58 company stacks & 45 developers stacks; compared to Apache Ant, which is listed in 24 company stacks and 12 developer stacks.

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Advice on Coveralls, Apache Ant

Felipe

May 24, 2020

Needs advice

My website is brand new and one of the few requirements of testings I had to implement was code coverage. Never though it was so hard to implement using a #docker container.
Given my lack of experience, every attempt I tried on making a simple code coverage test using the 4 combinations of #TravisCI, #CircleCi with #Coveralls, #Codecov I failed. The main problem was I was generating the .coverage file within the docker container and couldn't access it with #TravisCi or #CircleCi, every attempt to solve this problem seems to be very hacky and this was not the kind of complexity I want to introduce to my newborn website.
This problem was solved using a specific action for #GitHubActions, it was a 3 line solution I had to put in my github workflow file and I was able to access the .coverage file from my docker container and get the coverage report with #Codecov.

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Comments

Detailed Comparison

Coveralls	Apache Ant
Coveralls works with your CI server and sifts through your coverage data to find issues you didn't even know you had before they become a problem. Free for open source, pro accounts for private repos, instant sign up with GitHub OAuth.	Ant is a Java-based build tool. In theory, it is kind of like Make, without Make's wrinkles and with the full portability of pure Java code.
Repository Coverage Statistics;Individual File Coverage Reports;Line By Line Coverage;Repository Overview	The most complete Java build and deployment tool available.;Platform neutral and can handle platform specific properties such as file separators;Can be used to perform platform specific tasks such as modifying the modified time of a file using 'touch' command;Scripts are written using plain XML. If you are already familiar with XML, you can learn pretty quickly;Automate complicated repetitive tasks;Interface to develop custom tasks;Can be easily invoked from the command line and it can integrate with free and commercial IDEs
Statistics
GitHub Stars -	GitHub Stars 449
GitHub Forks -	GitHub Forks 449
Stacks 1.7K	Stacks 250
Followers 278	Followers 151
Votes 68	Votes 7
Pros & Cons
Pros 45 Free for public repositories 13 Code coverage 7 Ease of integration 2 More stable than Codecov 1 Combines coverage from multiple/parallel test runs	Pros 4 Flexible 1 Easy to learn 1 Simple 1 Easy to write own java-build-hooks Cons 1 Old and not widely used anymore 1 Slow
Integrations
Travis CI CircleCI Semaphore Jenkins Codeship	No integrations available

What are some alternatives to Coveralls, Apache Ant?

Apache Maven

Maven allows a project to build using its project object model (POM) and a set of plugins that are shared by all projects using Maven, providing a uniform build system. Once you familiarize yourself with how one Maven project builds you automatically know how all Maven projects build saving you immense amounts of time when trying to navigate many projects.

Gradle

Gradle is a build tool with a focus on build automation and support for multi-language development. If you are building, testing, publishing, and deploying software on any platform, Gradle offers a flexible model that can support the entire development lifecycle from compiling and packaging code to publishing web sites.

Bazel

Bazel is a build tool that builds code quickly and reliably. It is used to build the majority of Google's software, and thus it has been designed to handle build problems present in Google's development environment.

Codecov

Our patrons rave about our elegant coverage reports, integrated pull request comments, interactive commit graphs, our Chrome plugin and security.

Pants

Pants is a build system for Java, Scala and Python. It works particularly well for a source code repository that contains many distinct projects.

JitPack

JitPack is an easy to use package repository for Gradle/Sbt and Maven projects. We build GitHub projects on demand and provides ready-to-use packages.

SBT

It is similar to Java's Maven and Ant. Its main features are: Native support for compiling Scala code and integrating with many Scala test frameworks.

Buck

Buck encourages the creation of small, reusable modules consisting of code and resources, and supports a variety of languages on many platforms.

Please

Please is a cross-language build system with an emphasis on high performance, extensibility and reproduceability. It supports a number of popular languages and can automate nearly any aspect of your build process.

CMake

It is used to control the software compilation process using simple platform and compiler independent configuration files, and generate native makefiles and workspaces that can be used in the compiler environment of the user's choice.

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