Software has a weight. In a totally abstract digital sense, we can create software code that is heavy with excessive lines of code that perform circuitous (sometimes inefficient, often overly-labored) functions, or we can create lean (yes, mean) lightweight code that gets the job done faster. Although this is an oversimplification and software languages differ in terms of the way they are compiled, interpreted and executed at the back-end, we can say that some software is fit and wiry, while other code is bloated.
Hence the term, code bloat.
Couch potato code
When software applications inside enterprise IT systems exhibit code bloat, this couch potato code puts undue pressure on the compute end of the deployment itself. Rather like someone with a tendency for obesity, the heart (in this case the machine or device microprocessor, or the processing units in the cloud datacenter service provider’s server racks) has to pump harder. But just as there are ways to get heart-healthy in real life, we can also clean up code bloat through refactoring processes, so how does this work?
“Very often, inefficiencies within a coded software program arise when the code accumulates redundant logic, excessive complexities and suboptimal algorithms resulting in a decreased performance,” explained Kavitha Chennupati, senior director of product management at SS&C Blue Prism, a company known for its intelligent automation solutions, powered by AI and machine learning. “Common effects of inefficient code are changes to application performance when an app comes under high user load. Why does this happen? A key reason is that developers typically take care to test functional requirements regularly – but non-functional requirements, such as performance, scalability and load balancing, are not tested.
Even when we do know why this problem is happening, replicating product loads in various situations can be challenging. As inefficiencies creep into code, thereby slower processing, increased memory usage and system resource constraints processing time extends. These challenges often transcend into functional challenges for businesses. It is of course vital for developers and coding teams to prioritize testing and address non-functional requirements in their code, upfront.
Maintainability malpractice
“Maintainability is another key culprit causing inefficiency in code,” warned Chennupati, speaking to press & analysts at a deep dive software summit in London this month. “Many code sequences are inadequately maintained, leading to challenges for developers in comprehending the links between different lines of code. This lack of structured organization, such as modular units like functions or classes, results in rigid code. Consequently, if a developer does not fully understand a business’s code, due to its rigidity and unreadability, it becomes very difficult to modify unless they were involved in its creation from the start.”
When code readability suffers, Chennupati reminds us that spreading tacit knowledge becomes difficult and new code additions worsen complexity in an already unmaintained system. When code becomes hard to handle, it causes frequent bugs and requires a significant amount of rewriting, time-to-market and increasing development cost.
Origins of code-bloating
Understanding how code becomes bloated is essential to mitigate its detrimental effects on performance and maintainability. Code-bloating is when unnecessary and redundant code gets added to a sequence, resulting in an inflated and, hence, bloated code. Bloated code is mostly a consequence of ignoring best practices. A lack of comments in a code can impact the readability and cause confusion. So, businesses need clear coding practices to fix this and ensure developers follow the processes.
“Code also becomes increasingly bloated due to the addition of codes in blocks of workarounds or shortcuts, instead of thinking holistically and reengineering or refactoring the code,” said Chennupati. Unfortunately, there is often a ‘let’s make it work now, and improve it later’ mindset which is missed due to tight timelines, often resulting in inefficient bloated code. Technical debt includes removing dead code that no longer works. Businesses and developers must have a clear practice for getting rid of dead code. Having outdated technology in your tech stack can complicate things. During mergers and acquisitions, there are instances where overlapping functionality also results in code bloat. With clear end-of-life practices, developers can ‘clean out’ their code to prevent suboptimal coding.”
The power of code refactoring
In the battle against code bloat and inefficiency, many developers turn to a seemingly simple yet profoundly effective solution: code refactoring. This is the most heavily trodden route for developers to ‘clean up’ their code. Chennupati explains this process and says that developers are adopting newer technologies and methods, yet they often retain inefficiencies. It’s essential to make a conscious effort to clean up the code and avoid carrying over all existing logic. She suggests that developers should aim to ‘clean up their code’ but they also must avoid excessive refactoring i.e. finding the balance between fine-grained changes and preserving necessary code is crucial
“One of the biggest mistakes made when refactoring is overdoing it and ignoring the strategic view of the overall code, architecture, design, structure and usability. Developers must ensure they approach code-refactoring with a futuristic mindset and ensure proper governance and guardrails are in place around the software development life cycle,” concluded Chennupati.
By recognizing the common culprits of inefficient code, understanding the origins of code bloat and embracing the power of systematic code refactoring, software application developers can now look for opportunities to navigate the complexities of software development with greater efficiency to meet the demands of today’s evolving technological landscape.
Recognizing that code bloat exists and understanding the need to get into shape (not for every application and every data service everywhere, but certainly for every organization in every business vertical at some level) is the first step towards a healthier software execution lifestyle and, hopefully, a greener cleaner use of increasingly cloud-native technology services overall.
