Debugging in software development explained

Learn the essential techniques and tools for effective debugging in software development.

Debugging is the art of identifying bugs and issues in software code to ensure a seamless and reliable user experience.

In this post, we’ll dive deeper into debugging and understand various types of debugging approaches you can use. You’ll also learn how to use debugging tools to troubleshoot your code more effectively.

What is debugging?

“Debugging strikes me as putting the cart before the horse.”  – Edsger W. Dijkstra, Renowned Computer Scientist, Creator of the Infamous Dijkstra Algorithm 

TL;DR: Debugging is the process of identifying, analyzing, and fixing bugs in software to ensure programs run correctly and reliably.

Debugging is the process of analyzing code or software to identify and detect bugs. A bug is anything that can cause unwanted behavior in a program.

In the life cycle of developing software, debugging is crucial at every step, from planning the software to developing it and releasing it for production.

Typically, all types of software developers involved in the development and release of the software are responsible for debugging.

DevOps teams may also be responsible, depending on which phase of the software life cycle, debugging is needed. Moreover, dedicated QA (quality assurance) teams may also perform extensive debugging during the testing phase of the software before it’s released to the users.

Where did the term “debugging” originate?

TL;DR: The term “debugging” became popular after Grace Hopper’s team discovered a real bug in a computer relay in 1947, though engineers used the word earlier to describe system faults.

The term debugging has an interesting origin. Although since the 19th century, engineers have been using the term “bug” to describe faults in the system, “debugging” was used even before modern software development came into existence.

It’s said that the inventor Thomas Edison, in 1878, used debugging to describe some technical problems around his inventions.

In 1947, the term debugging became widely famous in the way it’s associated with software and systems.

Computer scientist Grace Hopper and her team working at Harvard University discovered that a real bug had been trapped in one of the computer’s relays, causing the system to crash.

Upon removal of the bug, the engineers logged the note: “First actual case of bug being found.”

From this point, the phrase debugging started to get popular and acquired the definition that it has today of the process of identifying and fixing an issue in a system.

Why is debugging important?

TL;DR: Debugging helps developers identify root causes of issues, improve software reliability, and deliver a better user experience.

Debugging is important because it enables a seamless and reliable experience to your end users. It assists engineers and developers on your team in narrowing down the cause of a bug or an issue, which further helps in its timely resolution.

Through structured debugging techniques, debugging can enable your teams to rapidly identify and, in turn, fix issues in your software, ensuring reliability and improving efficiency of your engineering teams.

In the life cycle of developing software, debugging is crucial at every step, from planning the software to developing it and releasing it for production. Following each step methodically can help teams derive the most benefits from debugging.

Testing identifies issues, whereas debugging narrows down the root cause and enables a fix.

Debugging vs testing

TL;DR: Testing detects defects in software, while debugging investigates the cause of those defects and resolves them.

Oftentimes, debugging and testing can appear similar activities. While they do have a correlation, they’re still completely different terms and have different definitions. Understanding the distinction can help teams build more effective debugging and testing workflows.

Testing identifies issues, whereas debugging narrows down the root cause and enables a fix.

Testing is the process where teams execute a program to identify issues, failures, or unexpected behaviour like performance bottlenecks, etc. It may help the team determine if under specific conditions, the application works as intended.

There are various types of testing, like unit testing, integration testing, performance testing, UI testing, etc.

When a test fails, it indicates that something in the system isn’t working as it should. Testing does not identify the cause of a problem, it’s a process that helps detect those problems.

Debugging comes into the picture after the defect has been identified, through testing or even without it. Whereas testing uncovers a problem, debugging focuses on diagnosing and potentially resolving that problem.

Teams can leverage both the debugging process and the testing process to improve overall software quality and reliability.

Through testing, they can detect issues early and utilize debugging techniques to understand those issues deeply, learn about their root cause and plot an optimal path to resolve that issue in a timely manner.

In modern software cycles, automated testing helps teams discover issues quickly so that developers and engineers can focus the majority of their time on debugging those issues and fixing them.

What are the coding errors that require debugging?

TL;DR: Common coding errors that require debugging include syntax errors, logical errors, runtime errors, and integration issues.

Software and system bugs that require debugging can originate from various kinds of coding errors. Identifying the category of error can narrow down how to correctly diagnose and resolve an issue.

1. Syntax errors

When code violates the general rules of construction of a programming language, a syntax error is said to occur. It prevents the code from compiling or executing.

A missing semicolon in C, incorrect indentation in Python, or mismatched parentheses are common examples of such errors. While compilers and interpreters highlight syntax errors, developers still need to be able to locate the issue in the code and rectify it themselves.

2. Logical errors

When code runs successfully but produces incorrect results due to a faulty logic implementation, a logical error is said to occur. For instance, a discount code calculation on the checkout page that computes a 20% discount instead of 10% discount is an example of a logical error.

Logical errors are difficult to detect because the program itself does not crash; it behaves incorrectly. However, the incorrect behaviour can be traced back to the source using debugging.

3. Runtime errors

When the program crashes during execution, a runtime error is said to occur. Some of the common reasons are accessing an undefined object or attempting to access a file that does not exist.

4. Integration errors

When modules interact with each other in an erratic fashion, an integration error is said to occur. A common integration error is an API request failing because the response format changes after a new backend release.

These errors require inspecting request payloads, logs, and service configuration mismatches between various components.

Context on where bugs come from can help developers and testing teams prevent them early on and utilise debugging techniques more efficiently.

Where do bugs come from?

TL;DR: Bugs typically arise from human mistakes, misunderstood requirements, integration issues, configuration differences, or concurrency problems.

Bugs in the software or code don’t surface arbitrarily. Bugs come from faults in the software due to the way code is written. Context on where bugs come from can help developers and testing teams prevent them early on and utilise debugging techniques more efficiently.

Here are some common sources or reasons for why bugs occur in a system:

1. Human errors

Human error is one of the most common reasons for bugs to occur.

This can happen at development time due to a number of reasons such as lack of understanding of the complete requirements on the engineer’s side, missed edge cases, lack of competency leading to incorrect logic or syntax implementation, etc.

For instance, a code condition “if (age > 18 )” is a human error if the business logic had to evaluate age 18 and above. An oversight of an equality sign missed in the condition due to human error can lead to unexpected behaviour causing a logical bug.

2. Misunderstood requirements

A lot of times there could be communication gaps between product/business teams and engineering teams. This could lead to requirements being understood differently by the engineering teams.

For instance, if a payment gateway is to be integrated in the software but the requirements don’t indicate how the currency conversion should be handled, the implementation may lead to payment amounts being produced incorrectly.

3. Integration issues

Modern applications consistently interact with their own internal APIs and also third-party APIs, external dependencies, SDKs, etc. When these components interact incorrectly, it could lead to bugs in the application.

For instance, if an update to an external API was released but the developers utilising that API did not account for the update, a change in the payload format due to the release could lead to an integration issue, causing a bug in the application.

4. Environment and configuration differences

When environments such as staging, production, and development have differences in their configuration and settings, bugs can occur due to this environment mismatch. A common example is when a bug doesn’t surface locally but shows up in production to users.

5. Concurrency and race conditions

Modern applications also handle multiple requests and interactions simultaneously. When there are timing conflicts or race conditions, such as two records in the database being updated at the same time, it could lead to inconsistent data, causing bugs.

Types of debugging

TL;DR: Developers use various debugging techniques such as backtracking, cause elimination, divide and conquer, logging, rubber duck debugging, and automated debugging.

There are several approaches one can take to effectively debug their code. Each approach has its benefits and works well with certain use cases.

Backtracking is useful in pinpointing what changes to a codebase caused a bug, and hence can be a great technique to debug any issues caused by recent code changes.

1. Backtracking

Backtracking involves tracing the path of the occurrence of a bug to identify the source. Instead of checking directly in the code, you go backward from the bug to narrow down the part of the code that caused the bug.

Backtracking is useful in pinpointing what changes to a codebase caused a bug, and hence can be a great technique to debug any issues caused by recent code changes.

For instance, if a specific release crashes an application, using backtracking, developers can narrow down the commit that likely caused the change.

2. Cause elimination

This technique is used to eliminate multiple plausible causes and is often helpful in situations where a bug could have many seemingly similar causes associated with it.

Using cause elimination, you can methodically go through each possible cause and eliminate the ones that don’t seem relevant to the bug. This helps in isolating the root cause of the bug, which also simplifies resolution.

Consider a scenario where you’re trying to debug the cause of why your frontend application performs more slowly than expected.

Using cause elimination, you can eliminate any database performance, API latency, or response times as possible causes and narrow down to a specific feature, page, or interaction on the client side that could be causing the performance issues.

3. Divide and conquer

You can use divide and conquer to break a specific part of your codebase into smaller and more manageable components. Each component can then be divided further, and the process goes on till you can narrow down the smallest piece of code that likely caused the bug.

This strategy is effective for complex and larger systems where bugs are difficult to trace due to lots of moving parts.

For instance, if you’re trying to troubleshoot a memory leak in a backend application, you can break or divide your monolith into individual services, and then further divide or break these services into functions, and so on until you narrow down a single function that was causing the memory leak.

You can use divide and conquer to break a specific part of your codebase into smaller and more manageable components.

4. Print and log debugging

“Start small and simple, logging only the most obvious and critical of errors.” – Jeff Atwood, American Software Developer/Entrepreneur and creator of StackExchange 

Using print statements and logging code outputs is the most straightforward type of debugging.

Here, you can add print statements where you can print values of variables, their types, and also log timestamps and references to variables to narrow down the cause of a bug. This technique is most helpful in debugging runtime bugs in your application.

5. Rubber duck debugging

“The effort of walking an imaginary someone through your problem, step by step and in some detail, is what will often lead you to your answer.” – Jeff Atwood, American Software Developer/Entrepreneur and creator of StackExchange 

The rubber duck debugging technique explains code step by step, running it by explaining it to an inanimate object, like a rubber duck.

This technique is extremely helpful in situations where developers experience knowledge bias or mental fatigue during time-sensitive debugging sessions. It allows them to logically address mistakes in the code by verbalizing them.

For instance, a developer can use the rubber duck debugging technique to understand why the base case of a recursive code block can lead to an infinite loop bug that can cause the application to crash.

A popular example of this is re-rendering a frontend component indefinitely due to state updates mistakenly set in an infinite loop.

6. Automated debugging

Automated debugging tools such as debuggers in terminals, integrated into IDEs, or debugger logs presented on the console or in the browser can be extremely helpful in initiating a debugging session where you’re unsure of which approach or technique to take, or for bugs where manual debugging techniques can be cumbersome to implement.

7. Brute force debugging

Brute force debugging involves checking every case or condition in a code block to identify the condition causing the bug.

Due to its time-intensive nature, it’s often the last resort developers adopt when all other techniques fail. It can also be helpful for stubborn bugs that aren’t easily captured in a logical analysis or issues that occur without any general pattern.

Examples of debugging

TL;DR: Debugging commonly occurs when investigating failed tests, API errors, or performance issues in software systems.

Debugging is often needed the most in cases where testing and automation may fail to identify the root cause. The following examples illustrate common scenarios where developers or QA teams utilize debugging.

1. Investigating a failed automated test

A common use case for debugging is when an automated UI or unit test passes locally but fails in the CI pipeline.

For instance, a test that validates the attempt to click a button on the page fails. By reviewing CI execution logs for that test run, the QA engineer can debug the test and discover that the page loading asynchronously is causing a race condition where the click happens before the page actually renders.

By inspecting API requests on the server, the backend engineer can identify that a missing dependency or a dependency conflict is causing erratic behaviour on the server.

2. Debugging an API failure

Another common scenario where debugging can be helpful is identifying the root cause for the failure of an API. Oftentimes after making changes to the backend or deploying an endpoint, it starts behaving unexpectedly, returning erroneous status codes like 500.

Engineers can utilize debugging to compare the server config with the local setup. By inspecting API requests on the server, the backend engineer can identify that a missing dependency or a dependency conflict is causing erratic behaviour on the server.

They can then deploy a fix where the same dependencies and their versions are used on the server as the ones used locally.

3. Debugging performance regression

Oftentimes, a new release causes performance issues by slowing down an application. This may become more apparent during load or stress testing of the release, so it may not be caught by the developers during development.

Through performance monitoring tools, engineers can trace the bottlenecks and identify the root cause of the issue.

Debugging process

TL;DR: Effective debugging follows a structured process: reproduce the issue, identify the bug, determine the root cause, fix it, validate the solution, and document the findings.

Following a structured approach during debugging can help you reap the benefits of debugging effectively. The following steps can be performed as part of the debugging process.

1. Reproduce the issue

Before you can start debugging the issue, you need to experience it firsthand. You can reproduce the issue by replicating the exact conditions under which it occurs.

Reproducing the issue gives you more clarity in understanding it, which can help in the subsequent steps of debugging as well. It may also induce empathy for your users, which can lead to a better resolution.

2. Identify the bug

Identifying the bug means locating precisely where the bug occurs. This step may be performed after or before you reproduce the issue.

For instance, you can identify if the bug happens on the client side or server side, or which file it occurs in, which function it belongs to, etc. This step helps you narrow down the target code that you need to analyze for debugging.

3. Determine the root cause

The heart of debugging lies in determining the root cause. However, oftentimes, developers ask themselves, “How can I effectively identify the root cause of a bug in my code?”

Once you’ve identified the bug and successfully reproduced it, you can use one or more of the debugging techniques described in the previous section to determine the exact root cause of the bug.

This step helps you understand why the bug occurs and will simplify the solution you choose for its resolution.

Choosing the right technique based on the debugging scenario and time constraints can greatly help in identifying the root cause of the bug.

4. Implement the fix

Determining the root cause gives you a clear sense of what you can do to fix the bug. In this step, you should think through possible fixes for resolving the bug and implement the fix that makes the most sense.

If you’re not directly involved in the resolution process, you can also share your possible solutions with the desired team to save time.

5. Validate the fix

“No bug is considered properly fixed without an automated regression test.” – Mike Bland, popular technical writer/software engineer

Using the same conditions or test cases that led you to reproduce the bug, you should validate the fix to ensure the bug has been successfully resolved.

You can also go beyond this and write any test cases to make the fix more foolproof or perform more thorough testing to ensure the fix doesn’t introduce a new bug of its own.

6. Document the process

Recording how and why the bug occurred, what debugging technique helped, the resolution selected, and so on can help deliver the relevant knowledge to other teammates. It can also act as a reference for future debugging processes.

Identifying the bug means locating precisely where the bug occurs.

What are the common tools used for debugging in software development?

TL;DR: Tools like IDE debuggers, browser developer tools, logging utilities, and static code analyzers help developers identify and resolve bugs efficiently.

The entire process of debugging can be simplified to a great extent using dedicated debugging tools.

You should pick a debugging tool that you’re most familiar with and comfortable with, since using a tool that involves a learning curve can prolong the debugging process and delay the resolution.

The following are some of the common tools used for debugging by developers:

1. IDEs

Visual Studio Code, Atom, and IntelliJ IDEA provide built-in debugging tools that you can use from within your codebase to inspect code and pinpoint errors.

2. Debuggers

For client-side debugging, browsers offer a built-in debugger where you can pause and run your code based on a debugger line that you can add to your code. This helps with root cause detection by allowing you to focus on the specific lines of code that you suspect may be at fault.

3. Logging utilities

Logging tools provide detailed error logs of your applications at both runtime and compile time. Moreover, logging functions, either custom built or open source, can help log code outputs that can facilitate the debugging process.

4. Static code analyzers

A static code analyzer inspects your code for any potential bugs or issues without actually running it. It can help you flag potential bugs before they’re released in production. It’s a commonly used technique in white box testing to identify errors in static code.

Benefits of debugging

TL;DR: Debugging improves software reliability, performance, and user experience, and can reduce operational costs caused by software failures.

Debugging has numerous benefits, such as:

1. Improved software reliability

It ensures software functions and performs more reliably for users.

2. Enhanced performance

Bugs and unwanted issues may hamper your application’s performance. Debugging eliminates these bugs and improves the performance of the application.

3. Improved user experience

The end-user impact of debugging is creating a more user-friendly software usage experience that leaves a good impression on your customers.

4. Improved costs

Debugging crucial bugs that can lead to downtime or complete software crashes can save costs for your company and avoid a negative impact on your business.

Standard debugging techniques may not prove to be effective, so you should always try to evolve these techniques as your software evolves in complexity.

Challenges of debugging

TL;DR: Debugging can be complex and time-consuming, especially in modern systems with many dependencies and moving parts.

Debugging by itself poses certain challenges that can be difficult to navigate, even if you use the most effective debugging technique.

With the increasing complexity of modern software, debugging may become more complex too. Standard debugging techniques may not prove to be effective, so you should always try to evolve these techniques as your software evolves in complexity.

It’s also important to note that debugging by itself can be a monotonous and time-consuming process. It can drain the mental bandwidth of your engineering teams.

Sometimes, seeking a fresh perspective from a teammate or tackling debugging sessions with a relaxed and well-rested mind can help overcome this challenge.

What strategies can I use to reduce the occurrence of bugs in my software?

“Everyone knows that debugging is twice as hard as writing a program in the first place. So if you’re as clever as you can be when you write it, how will you ever debug it?” – Brian Kernighan, renowned computer scientist and author of The Elements of Programming Style

TL;DR: Writing clear code, conducting code reviews, and implementing thorough automated and manual testing helps reduce bugs early.

By following the given strategies, you can reduce the occurrence of bugs in your software to simplify and, in some cases, even eliminate your debugging sessions.

1. Write clear and maintainable code that’s easy to understand and work on top of.
2. Follow thorough code reviews to ensure code quality amongst your team.
3. Implement rigorous testing, both manual and automated, to catch bugs before they’re released.

Speed up debugging with intelligent insights

TL;DR: Platforms like Tricentis Sealights help teams identify untested code and risky changes, making debugging faster and more focused.

Debugging can be made significantly easier when teams can clearly understand which parts of the code are tested and how changes introduced in a release are correlated to issues and risk in the software.

Modern engineering teams rely on tools that help them detect these failures early on, understand test coverage of their code, and also narrow down the changes that could be responsible for the issues.

Platforms like Tricentis Sealights can give teams the visibility they need into their test coverage across various builds and releases.

By analysing the test coverage and linking it directly to changes being released, teams can identify areas that are untested, spot potentially faulty commits, and in turn prioritise where debugging efforts make the most sense.

With this deep level of insight, developers and QA teams can save time from searching for the source of the bugs and utilise that saved time in actually resolving the issues effectively.

Learn more about Tricentis Sealights and how teams understand which code changes are tested to spot risks early on and resolve issues faster.

Conclusion

Debugging is a crucial part of software development. Using the right debugging technique coupled with the right set of tools, you can improve your customer satisfaction and your business outcomes, in addition to the numerous other benefits that debugging offers.

This post was written by Siddhant Varma. Siddhant is a full stack JavaScript developer with expertise in frontend engineering. He’s worked with scaling multiple startups in India and has experience building products in the Ed-Tech and healthcare industries. Siddhant has a passion for teaching and a knack for writing. He’s also taught programming to many graduates, helping them become better future developers.