DZone
Thanks for visiting DZone today,
Edit Profile
  • Manage Email Subscriptions
  • How to Post to DZone
  • Article Submission Guidelines
Sign Out View Profile
  • Post an Article
  • Manage My Drafts
Over 2 million developers have joined DZone.
Log In / Join
Refcards Trend Reports
Events Video Library
Refcards
Trend Reports

Events

View Events Video Library

Related

  • Modernizing Apache Spark Applications With GenAI: Migrating From Java to Scala
  • Mastering Advanced Aggregations in Spark SQL
  • Beyond Code Coverage: A Risk-Driven Revolution in Software Testing With Machine Learning
  • Thermometer Continuation in Scala

Trending

  • Is the Data Warehouse Dead? 3 Patterns From Enterprise Architecture That Answer This Question
  • Skills, Java 17, and Theme Accents
  • Optimizing High-Volume REST APIs Using Redis Caching and Spring Boot (With Load Testing Code)
  • Building a DevOps-Ready Internal Developer Platform: A Hands-On Guide to Golden Paths, Self-Service, and Automated Delivery Pipelines
  1. DZone
  2. Coding
  3. Languages
  4. The best code coverage for Scala

The best code coverage for Scala

By 
Rado Buranský user avatar
Rado Buranský
·
Feb. 12, 14 · Tutorial
Likes (1)
Comment
Save
Tweet
Share
34.0K Views

Join the DZone community and get the full member experience.

Join For Free

The best code coverage metric for Scala is statement coverage. Simple as that. It suits the typical programming style in Scala best. Scala is a chameleon and it can look like anything you wish, but very often more statements are written on a single line and conditional “if” statements are used rarely. In other words, line coverage and branch coverage metrics are not helpful.

Java tools

Scala runs on JVM and therefore many existing tools for Java can be used for Scala as well. But for code coverage it’s a mistake to do so.

One wrong option is to use tools that measure coverage looking at bytecode like JaCoCo. Even though it gives you a coverage rate number, JaCoCo knows nothing about Scala and therefore it doesn’t tell you which piece of code you forgot to cover.

Another misfortune are tools that natively support line and branch coverage metrics only. Cobertura is a standard in Java world and XML coverage report that it generates is supported by many tools. Some Scala code coverage tools decided to use Cobertura XML report format because of its popularity. Sadly, it doesn’t support statement coverage.

Statement coverage

Why? Because a typical Scala statement looks like this (a single line of code):
def f(l: List[Int]) = l.filter(_ > 0).filter(_ < 42).takeWhile(_ != 3).foreach(println(_))

Neither line nor branch coverage works here. When would you consider this single line as being covered by a test? If at least one statement of that line has been called? Maybe. Or all of them? Also maybe.

Where is a branch? Yes, there are statements that are executed conditionally, but the decision logic is hidden in internal implementation of List. Branch coverage tools are helpless, because they don't see this kind of conditional execution.

What we need to know instead is whether individual statements like _ > 0, _ < 42 or println(_) have beed executed by an automated test. This is the statement coverage.

Scoverage to the rescue!

Luckily there is a tool named Scoverage. It is a plugin for Scala compiler. There is also a plugin for SBT. It does exactly what we need. It generates HTML report and also own XML report containing detailed information about covered statements.

Scoverage plugin for SonarQube

Recently I have implemented a plugin for Sonar 4 so that statement coverage measurement can become an integral part of your team's continuous integration process and a required quality standard. It allows you to review overall project statement coverage as well as dig deeper into sub-modules, directories and source code files to see uncovered statements.

Project dashboard with Scoverage plugin:
01_dashboard

Multi-module project overview:
Multi-module project overview:

Columns with statement coverage, total number of statements and number of covered statements:
Columns with statement coverage, total number of statements and number of covered statements:

Source code markup with covered and uncovered lines:
Source code markup with covered and uncovered lines:

Code coverage Scala (programming language)

Opinions expressed by DZone contributors are their own.

Related

  • Modernizing Apache Spark Applications With GenAI: Migrating From Java to Scala
  • Mastering Advanced Aggregations in Spark SQL
  • Beyond Code Coverage: A Risk-Driven Revolution in Software Testing With Machine Learning
  • Thermometer Continuation in Scala

Partner Resources

×

Comments

The likes didn't load as expected. Please refresh the page and try again.

  • RSS
  • X
  • Facebook

ABOUT US

  • About DZone
  • Support and feedback
  • Community research

ADVERTISE

  • Advertise with DZone

CONTRIBUTE ON DZONE

  • Article Submission Guidelines
  • Become a Contributor
  • Core Program
  • Visit the Writers' Zone

LEGAL

  • Terms of Service
  • Privacy Policy

CONTACT US

  • 3343 Perimeter Hill Drive
  • Suite 215
  • Nashville, TN 37211
  • [email protected]

Let's be friends:

  • RSS
  • X
  • Facebook