code coverage vs test coverage. How do they differ?

Code Coverage vs test coverage, how do they differ? Code coverage and test coverage are very important when it comes to checking the effectiveness of code. Before explaining in detail about the cruciality of Code Coverage and  Test Coverage in software testing. let’s find out how do they differEven though code coverage and test coverage are misunderstood they lot their meaning and usage differ a lot.

So, Code Coverage vs Test Coverage how do they differ? Let’s have a look

What is Code Coverage in the unit testing?
Code coverage is the degree to which any application code of any software has been executed. A huge number of test cases are applied to the application code, and the software is then checked. This is a case of white box testing.
White-box testing of this type sends the report of the application codes that are left unassessed by the test case that has been applied to the application code. In some specific situations, several test cases are further included to have better code coverage.
Usually, the term code coverage is used when an application is in its current running state. While the application is running, code coverage lets the developers know about the number of codes that have been unit tested/covered. In other words, it gives a quantitative measure of how much code has been executed and how much code has been left untouched. This report can further be used for better software testing purposes.
After learning what code coverage is, a question pops up about why someone would need the concept of code coverage. This is a confusion in the minds of many. Here is a brief description of why we need code coverage during software testing.
Wish to know the difference between smoke testing and sanity testing?

Wish to know the difference between smoke testing and sanity testing?

Why is Code Coverage Required?

  • Developing a good quality software test and applying it to the application code is not enough. While the software code is running, the developers also need to assess the fact of whether the software test is being carried out efficiently or not. For this purpose, code coverage is required. Without code coverage, no one would ever know if the software test that was carried out was efficient or not.
  • Code coverage gives an exact measure of the code that has been tested. It makes it easier for developers to look for the code that remained untested. As testing the code is very important, the accidental leaving out of any code from testing can turn out very disadvantageous. This is why an exact quantitative measure of the tested code becomes extremely important when testing any software’s source code.
  • The developers get to know what amount of codes have been tested, and hence, they can assess those codes carefully. This makes it very easier for the developers to make their software free of any potential errors and glitches. It gives out the degree of the software code that has been tested.

After the reason for the necessity of the code coverage is discussed, next comes the methods to carry out software testing. Here are the five broadly classified methods or coverages that come under code coverage.
Methods of Carrying out the Code Coverage

  • Statement Coverage: Statement coverage is the type of white box testing where the statement coverage makes sure that the executable portions in the application code are executed at least once if not more. It tells about the statements that can be executed at least once through the given requirements.

Statement coverage covers the entire source code and gives out what is not executed. This turns out to be very advantageous to the developers as they can remove all the drawbacks of the application codes.
Statement coverage helps to remove the possible drawbacks of the application code which includes all the dead codes which are the piece of code that calculates the results, but the results are never utilized. These codes are a wastage of space and hence are supposed to be removed.

Statement coverage also helps to identify the unused statements and branches. There are certain statements and branches in the application code that are never used. These statements and branches should be removed. Any missing statement is also reported, and the developers can deal with it as they please.

  • Decision Coverage: Decision coverage is based on Boolean concepts. The true or false value of Boolean expressions is reported through this coverage.
  • Branch Coverage: In branch coverage, the modules of codes are tested and reported. The main motive of branch coverage is to ensure that each branch of the application is executed at least once if not more. It also helps to measure how many independent statements exist in the application code.
  • Condition Coverage: Condition coverage reveals the way using which the variables in the conditional statements are evaluated. It is a better way to provide proper coverage to the control flow, which was not the case with decision coverage.
  • Finite State Machine Coverage: It works based on the frequency of visits of static states and other transactions like these. Finite state machine coverage turns out to be the most complicated method of coverage as the basics of this type of coverage work on the design of the structure of the software.

Now, one might be confused as to which method should be chosen for the task that would prove the most efficient one. This decision is made on many criteria. Some of the criteria include the number of defects permissible or the probability of errors arising. Another one would be the cost that is involved in the software testing type.
Though the main decision of choosing the method is dependent on the number of defects or loss of sale that can occur. The higher is the number of defects probable, the lower would be the chances of using that specific coverage for the software testing.
What are the Advantages of Using Code Coverage?
After reading the information above, it is normal to have confusion regarding why anyone should choose code coverage over any other coverage. Here, the advantages provided by the code coverage is mentioned below:

  • Quantitative in Nature: Code coverage is one such unique coverage that gives out the results in a quantitative measure. This quantitative measure can be very useful to the developers.
  • Can introduce Own Test Cases: In case the already available test cases do not provide the proper testing of the software, one can introduce their own test cases to make the coverage more efficient. This probably is the best advantage of code coverage as it can help you to make your coverage more and more effective.
  • Easy Removal of dead Codes and Errors: Some areas of the program are left unattended in the execution time. Or maybe there is an existence of dead codes or useless codes. In such cases, code coverage provides the best way to figure out and remove the errors easily. This increases the efficiency of the coverage performed.

But just like every coin, even code coverage comes with its own set of limitations and disadvantages.
How to get 100% code coverage?

  • it’s possible but will be very expensive to attain 100% code coverage
  • Even with 100% code coverage, your code has no guarantee of being perfect
  • 100% test coverage does not mean that the suite is perfect.  What you need is 100% path coverage
  • it will depend on the language and framework you use. For instance, Ruby has a very mockable framework through which you can stub or mock out a large portion of the code and will save you from building complicated class composition and construction designs
  • TDD is the best way to attain 100% line coverage
  • Unit tests can be used as a regression prevention method

What is path coverage in software testing?
Test cases that can be put to use to test linearly independent paths in a software system.  in the short, the control flow of an application will be tested in the path coverage process.  Testers have to look into each individual line of code that plays its part in a particular module to make sure that there is no issues.
What are the Disadvantages of Code Coverage?

  • Unable to Report Special Features: Code coverage lacks the ability to report the absence of any special features that should have been implemented in the application code. This absence can harm the software significantly, but while using code coverage, this section of coding limitations is left untouched and hence proves to be very disadvantageous to the developers and their software.
  • Impossible to Check all Possible Values: If a new feature is added, it is almost impossible to check all the possible values of the feature using the concept of code coverage. This is a drawback as some of those values can turn out to be useless.
  • Unable to Detect improper Usage of Logic: Code coverage fails to detect the improper usage of logic in the code. The improper logic can make the whole software go in vain. This is probably the biggest drawback of using code coverage for software testing.

This was code coverage in Code Coverage vs Test Coverage. Test coverage is another software testing metric with a little bit of difference.
What is code coverage in unit testing?
Test coverage can often be confused with code coverage, but the truth is that it is quite different. Test coverage provides the amount of test that has been executed. It reports about the parts of the application that are running when the coverage is being implemented. It gives the report of the tests that have been carried out on the application. We can say it is more about the test instead of application codes.
Why do We use Test Coverage?
When there are so many coverages out there, what was the need for test coverage in such a situation? The answer to this question is given below:

  • One thing about test coverage is that it reports the area of requirement which has not been covered by the test cases.
  • It also helps to detect the areas of the test cases that are useless to software testing. These cases are reported to the developers.
  • It can also help the developers to create additional test cases whenever and wherever required. These additional test cases help ensure that the coverage is maximum.

What are the Advantages of Test Coverage?
Test coverage provides some special features that prove advantageous for the developers.

  • Test coverage enhances the quality of the coverage over the software testing and thereby improves software testing.
  • It marks the portions of the application codes that were touched or may be fixed.
  • The paths that remained untested are also reported to the developers.
  • Any defect that could generate potential threats for the software in the future is detected early in the course of execution and thereby fixed. This improves the efficiency of software testing.
  • Any gaps or scopes in the test requirements are noted and brought to the notice of the developer as soon as possible.
  • Test coverage can prevent any defect leakage.

What are the Disadvantages of Test Coverage?
The test coverage also has its own set of drawbacks, which can make any developer hesitate from using the test coverage.
The disadvantages are listed below:

  • Manual in Nature: The biggest and most disadvantageous defect of the test coverage is that it doesn’t have any tools available. Yes, that’s right that test coverage is very efficient, but the setback is that everything is manual. One needs a proper professional to sit down and do the testing work, which is hectic and causes some inefficiency on its own. There are almost no automated tools available that help the manual work become even a tad bit easier.
  • Scope of Judgmental Errors: There can always be a huge number of judgmental errors even after carrying out the whole test coverage very efficiently and properly.
  • Scope for Careless Errors: The introduction of manual work always introduces a scope of careless errors. Any slight carelessness on the part of the professional carrying out the software testing can prove to be very disadvantageous for the software. This could be a huge setback.

Cost of testing your app
Code Coverage vs Test Coverage



Code Coverage

Test Coverage



It refers to the execution of the application code while the application is running. It is not a specific plan or result but the overall test plan issued for the codes.
2. Aim of the coverage The automated tests that are running can be monitored by the developers using code coverage. It gives a measure of the amount of code that has been processed and run by the tests.
3. Subtypes of the coverage Code coverage has a number of subtypes which include statement coverage, condition coverage, Branch coverage, Toggle coverage, FSM coverage. Test coverage has no subtypes. It is all just complete in itself.

Tools used of Code Coverage
There are several tools available in the market to check code coverage. These include both open-source and paid tools. Most of these tools can also be integrated with the build and project management tools for better results. While selecting a code coverage is important to check the features it offers along with its integration with other tools used by your team.
Some of the popular code coverage tools are:

  1. py

It is an open-source code coverage tool for python. It records the codes that are executed as part of the testing and gives the result in percentage. It can be used to measure how much of the code is tested per test cycle. It also reports out the part of the code that could have been executed but was not. This helps to plan the testing activities better for the next cycle.

  1. Serenity BDD

It is mainly a UAT (User Acceptance Testing) tool that also provides code coverage options. It allows you to write epics, sub-epics, and stories for each code path and user behavior. The results generate from Serenity BDD contain much more details than just code coverage. Another advantage is that it can easily integrate with several other popular tools like Appium, Sauce Labs, Jenkins, Jira, and more.

  1. JaCoCo

JaCoCo, Java Code Coverage, is an actively maintained code coverage tool that became popular after EMMA and Cobertura were retired. It can be easily integrated with Maven, Gradle, Jenkins, Visual Studio among others to get an understanding of the java code coverage during the testing.

  1. PITest

It boasts itself as the gold standard in test and code coverage. While most code coverage tools only tell you what lines of codes were executed and the ones that were missed, PITest also uses mutation testing and helps your code to find more bugs also. PITestt modifies the actual code to run unit tests on it and thus helps in finding issues as well.

  1. NoUnit

It was developed by and is used the check the code coverage for Junit tests. It gives you a clear understanding of the part of the code that was executed and the part that was missed. It generates a color code report which is very easy to interpret even by non-technical people.
Tools used for Test Coverage
Unlike code coverage, test coverage can not be quantified. Test coverage mostly refers to the coverage with respect to the functionality or module and not the code. Many times you may need to write some code to analyze your code coverage. There are some code frameworks that can help you with your test coverage.

  1. Junit: It is the unit testing framework for Java. It is open an open-source tool have can very well be used for Test Driven Development (TDD) as well as for finding the test coverage. This framework is very popular among both developers and testers.
  2. PyUnit: PyUnit is another very popular framework that is used in TDD and helps with the test coverage calculations as well. It can be used for writing test cases, unit test cases, test cases, and even test fixtures. As the name suggests, it is used for Python developers and testers as well.

Both code coverage and test coverage are the measurements of assessing the quality of the software testing that is being carried out. Both are extremely essential when it comes to software testing and checking the internal coding and structure of the system. So there is no point in carrying out code coverage vs test coverage
In layman terms, the code coverage metric tells about the application code that is being executed. While the test coverage is mainly focused on the overall test plan. Everything is done only to focus on the well-functioning of the software that is supposed to be launched.

13 Best Java Tools 2020

Choosing the right software development tool is like choosing your favorite candy from a candy store. They all have their unique taste and touch, but you still love them all equally.

Java is an object-oriented programming language, which is specially designed for mobile and set-top box devices. In this blog, we have focused on the 13 best Java tools that are readily expected to be used in the upcoming year and how well it would satisfy user needs.

2018 has seen many ups and downs in the development scenario since many of the developers constantly tried to learn and upgrade themselves to a new version of the tool.

Recent advancements show that modularity and light-weighted Java tools will increase popularity among development processes and expertise to demonstrate new concepts.

The below given lists showcases the top 13 Java tools for 2019:

Java Development Tools

1. Eclipse

Inspite of the many numbers of tools landing in the market today, Eclipse remains one of the preferred tools for almost 60% of the Java developers. Eclipse is a one-stop-shop of all IDE’s that features plug-ins and interfaces which can be customized at any time.  It also serves a huge community and followers and is popular among large enterprise developers.

The current version of Eclipse IDE is 4.5 which supports Java Version 8. A few benefits of using the tools include:

  • Easy Navigation properties
  • Ease of error debugging
  • Easy package and plug-in downloads
  • Auto-completion feature
  • Supports multiple programming languages other than Java
  • Quick updates to the tool available
  • Syntax check while writing the code

2. NetBeans IDE

The NetBeans is an open-source IDE that supports almost all of the Java development types like Java SE, Java ME, and Java EE.  The NetBeans IDE is provided by modules where each module defines a function that supports Java language. You just have to download & install the tool and you are ready to go.

It is known for its reusable framework property which simplifies the development of Java desktop applications. The latest version being the 8.2, it doesn’t run on the JDK9 Platform.

Benefits of using NetBeans are:

  • Dynamic Language Support
  • Supports Java Standards and Platforms
  • Power-packed GUI Builder
  • Support for Non-Java code
  • Platform Extensible
  • Ideal for first-timers

3. Java Development Kit (JDK)

The Java Development Kit offers a whole lot of features to developers to bring out the best in their programs. Since the inception of the Java platform, JDK remains one of the most used tools that includes a private Java virtual machine (JVM) and some other meaningful resources.

JDK is well known for its high performance, functionality, and memory allocation techniques. Both low-level and high-level functionality can be incorporated into the tool with the Java security API.


  • Low cost of use
  • Easy for novice users
  • Easy transition from C to other languages.
  • User-friendly
  • Appeals internationally

4. Oracle JDeveloper

As the name suggests, this tool was announced by Oracle and provides a complete and comprehensive development framework. The Oracle application development aims to provide a declarative and visual approach to build an enhanced development experience.

Prior to the recent version of 11g, JDeveloper was available for 3 java editions viz. Java edition, studio edition, and the J2EE edition. It also consists of high-level features like Ant support, Open API, Audit & metrics, etc. Which may not be available on the other development tools for Java.


  • Incorporate security services
  • Re-usability of code features
  • Visual development environment
  • More than 150+ Ajax-enabled components available
  • Support to Java Persistence API

Java Testing Tools

5. JRat

The fourth tool Java Runtime Analysis Tool, widely known as Jett, is used as a testing tool for Java applications. It is an open-source platform that helps in determining the application’s execution and performance measurements. It identifies potential risks and analyses data using its pre-built desktop application.


  • Is an open-source profiling tool
  • Supports a wide developer community
  • Improves framework support
  • Allows high-level profiling functionality
  • State of art heap analysis tool
  • Can perform runtime analysis for a remote machine

6. IntelliJ IDEA 13.1

IntelliJ IDEA will always act as a good friend for your application development. When you are busy writing the code, IntelliJ Idea will be busy creating the class references, flow execution, decision tree, fields, methods and much more.  Using this functionality you can quickly navigate through your code and have an error analysis done in no time.

Any of the recent IDE’s will provide you more or less similar functionality, but IntelliJ is the only one that will present you with a deep static code analysis allowing you to focus more on your creativity.


  • Smart completion of your code
  • Data flow analysis
  • Re-factoring
  • Duplicate detection

7. Apache ANT

Apache ant is a popular and traditional built tool since its launch. Apache ANT is an open-source tool for Java developers provided by Apache Software Foundation. The tool is known to automate your process of software building which is achieved in easy steps.

Read also: Top 11 WordPress Plugins For Developers and Testers

The tool includes Ant libraries that have defined tasks to compile and execute the program. The benefit of these libraries is that it does not require to write another set of code for building the application. The whole process takes place and is defined by the targets which are XML files.


  • Since Ant is built using plain XML, if you already know XML, it’s very simple to learn Ant.
  • Includes a large list of predefined tasks
  • Interface for creating your own task list
  • Clean and easy to understand dependency reports
  • Supports conflict management

8. Gradle

Gradle is the next generation view for JVM based tools. It takes its lessons from the famous Apache Maven and Ant and provides the better of the two. Gradle includes a declaratively modeling of your difficulty domain making use of strong and expressive domain-specific language (DSL), which is implemented in Groovy and not XML, unlike Apache Ant. Because Gradle is a JVM native, it allows you to write custom logic in the language you’re most comfortable with, be it Java or Groovy.


  • Can create multiple APKs for your app
  • Re-usability of code and build process
  • Integration customized to the android studio.
  • Integrated SCM
  • Jenkins integration environment
  • A good number of plug-ins available

9. Mockito

Are you dealing with advanced framework integration? Then Mockito is a tool you should search for. Mockito offers you a mocking framework that is used by people looking out for unit testing their java application. Just as the name, it follows building a fake mock-up for testing purposes.

Mockito allows you to define classes as well as in interfaces that support test espionage and not just mock-ups. It also offers a good void method handling so you need not write separate code for the same.  The only drawback being its maintenance issue.


  • Efficient dependency handling
  • Can create tests in advance
  • Can create mock-ups for non-accessible resources.
  • Client involvement possible
  • Isolation of system made easy

10. YourKit

Known to be a Java profiling tool, YourKit offers the most powerful and innovative performance analysis capability.  Your Kit solves some of the major reasons giving rise to performance and scalability problems. This functionality thus saves a lot of time developers put in.

Along with the above benefits, it also offers management of CPU and memory profiling. The tool is an all-stop shop for all the advanced Java profiling capabilities and features.

  • Advance YourKit features at disposal
  • Boosts productivity and saves a lot of time
  • High-level result-oriented
  • Easy and straight process for installation
  • Developer friendly.

11. Clover

Clover is a code coverage tool that identifies bugs that were not tested and can prove fatal for the systems working. It provides test automation functionality for smooth integration. The recent version being the 4.1.

Read also: What is Code Coverage? Difference between Code Coverage and Test Coverage

Many organizations use clover for desktop and server applications. It balances the effort between a code that runs the program and code that tests it. You can test a part of the program that changed instead of testing the entire application all over again.


  • Includes code coverage tests in the reports
  • Can integrate with any existing system
  • Quality assurance and cloud sourcing
  • Compare actual and expected results

12. FindBugs

Findbugs is a static analysis tool that identifies potential software bugs of the Java bytecode.  These benefits the users to identify any bugs well before in advance. The tool is like a plug-in and has to be used in the development tools like Eclipse and IntelliJ.

You can check for bugs without actually running the application. It doesn’t focus on style or formatting of your code but searches for actual bugs that might hamper the performance.


  • Generates meaningful results
  • Eliminates false positives
  • Application-specific detector packages
  • Pluggable architecture
  • Setting can be shared among the network

13. Cobertura

Cobertura is a free Java tool that calculates the percentage of code the test has accessed. It is a plug-in that can be installed from Jenkins. It enables you to visualize and measure Java code by putting it in a detailed tree view.


  • Configure built tools
  • Execute code from Jenkins
  • Hierarchy of projects
  • Generates HTML based reports
  • Customizable threshold


The Java environment is vast and keeps on changing with new tools and techniques every year. Though every tool discussed here have their own advantages and drawbacks, it all depends on a user’s need whether to use or not.

All the upcoming improvements in Java forces developers to adopt this tool for a wider array of digital transformations, and looking towards the future, Java is certainly one of best tool to make amazing apps in the coming years.