Unraveling the Costs of Bad Code in Software Development
Bad code has always been a costly issue. Since the 1980s, researchers have found that fixing an issue after delivery can be 100 times more expensive than identifying and addressing a bug early on. Twenty years later, the National Institute of Standards and Technology estimated that bad code post-deployment costs 30 times more.
In 2024, bad code continues to plague companies, a critical problem as businesses rely on the power of their software to meet their goals and remain competitive. Code is more important and ubiquitous than ever, making bad code much more of a liability.
While generative AI stands to change the way developers write and examine code and may offload some code writing, the reality is that humans will always be part of the process. And because humans aren’t perfect, and GenAI tools are continually evolving, it should be expected that there will always be mistakes. Companies must view software as a business-critical asset, meaning the consequences of this bad code can’t be underestimated but must be mitigated to ensure business success.
The Impact of Bad Code
Bad code affects the development process and the entire life cycle of software. It tends to be difficult to understand, making it challenging for developers to extend or modify later. As developers like to reuse code whenever possible, this can lead to issues down the road if a bad line of code is copied and pasted into a different project. It also lacks scalability; it can’t adapt to changing business needs or incorporate new features.
Bad code can also be a breeding ground for bugs, as hidden issues resurface unexpectedly, becoming costly and more challenging to recover from. The more these issues accumulate, the more tech debt mounts, which can get expensive. Over five years, research shows associated costs can reach up to $1.5 million or more than 27,000 developer hours.
Fixing these bugs takes time. Developers have to spend hours deciphering bad lines of code and fixing them, which takes time away from writing new code and delays the entire development process as teams miss deadlines. Bad code also stunts productivity, taking attention away from other new, innovative projects.
All these problems only accumulate over time as bad code continues to fester. Increased costs of maintenance, bug fixing, reworking and technical debt continue to mount, affecting not only development teams but also companies as software quality lessens. Beyond that, bad code is a significant security risk that can threaten reputational damage and compliance issues, in addition to the financial danger of deploying software that incorporates it.
Bad Code Is a Growing Problem
Developers are in a difficult position. As business leaders depend on the strength and power of their software to succeed, developer teams are more strapped than ever before, with workloads quickly becoming unsustainable and unrealistic. Already, these workers feel the impact of increasing demands on their time, with 83% stating in one survey that they are experiencing burnout.
The burnout and expectations of breakneck efficiency and speedy code writing have potential consequences, especially as many turn to AI-coding tools to help. Studies show that, as a result, code churn, which measures the percentage of lines thrown out within two weeks of being written, is increasing and expected to double by the end of the year. Bad code isn’t just a static problem; it’s getting worse. How can companies look to eliminate the bad-code problem before it becomes catastrophic?
Cleaning as You Code
Perfection isn’t realistic, but developers have tools and processes to ensure they’re writing and delivering the best possible code. Clean code should always be the goal — consistent, intentional, adaptable and responsible — and ultimately easier to maintain. Clean code delivers the kind of software that allows businesses to meet their goals and surpass them.
How can developers ensure they’re writing and using this kind of code? A Clean as You Code method is the answer. Earlier, more comprehensive testing and analysis can catch problems before they become serious. Doing so can ensure that if the code is reused later, it will be free of the bugs and issues plaguing projects and companies later in the development cycle.
Employing static analysis and unit-testing measures allows coders to do the work effectively and catch any threats to quality. This mindset of cleaning as you code — working smarter, not necessarily harder — also allows developers to work faster to deliver better-quality software.
Bad Code Means Bad Business
Developers can’t afford to wait until later in the development process to identify problems and find solutions, nor should they. Early prevention and quality assurance are the best paths forward to writing high-quality code and mitigating technical debt rather than adding to it. As teams become increasingly comfortable using AI to help alleviate their workloads, this early testing only increases in importance. GitHub even recently updated its Copilot information hub to warn that it can generate “undesirable patterns,” adding that developers are responsible for ensuring the security and quality of their code.
The truth is that businesses must take bad code seriously as a threat to the workload and productivity of their development teams and their overarching business goals. Prioritizing clean code and doing so early on in the development process is the only way for companies to put themselves in a position to deliver top-quality software at a time when doing so is not only helpful but necessary for future success.
