Coinciding with novel software development frameworks, new languages for advanced tech (e.g. languages for the Internet of Things, Data Analytics, Artificial Intelligence), new benchmarks, novel managed code systems, platforms, and new compiling methods, there came about new and improved Software Development Life Cycle (SDLC) methodologies. These methodological systems include phases, steps, and general best practices associated with developing new software and have helped professionals engineer more robust applications in a shorter amount of time.
Several SDLC types or systems are available which utilize different philosophies in how applications should be developed:
Within the realm of software development, an issue often comes up called technical debt. Technical debt – like financial debt – is an accumulation of issues that arise in an application when less-than-best practices are utilized during the development stages or phases. This can include shortcuts, using insecure code, skipping steps within a methodology, using certain functions or loops that are not best practice for an application, not checking, securing, or fixing errors, and more. Ultimately, though an application may be prone to having certain non-fatal errors (that is, the application executes and runs without crashing), the fundamental aspect of technical debt is that such accumulating issues may create more significant problems down the line for an application, which can come up during routine maintenance, security work, or code reviews, requiring either a re-working of the code, or taking the route of not fixing the code, which can leave the application open to security breaches, among other things.
It is the job of software engineers to ensure that technical debt is minimized by writing solid code from the get-go, which is a critical factor that will enable operations admins and security admins to maintain the application in the future without the code requiring a re-write. Minimizing technical debt also ensures that the application works smoothly from the beginning and that engineers can focus on what is important – writing a robust, performance and functionally-optimized application.
Agile software engineers should utilize best practices from the start to manage how they write code, which includes using secure coding methodologies, and integrating their iterations – or sprints (in the event of using Scrum) – with automated security testing, while having teams at the ready to ensure that the code is reviewed and optimized at all times.
Technical Debt is a type of digital debt that accumulates when a developer takes a short-cut for a short-term payoff (i.e. not needing to write secure code during phase one), while not taking into account the long-term, negative consequence of taking the short-cut. These short-cuts often result in technical issues that accumulate later, resulting in a software application that does not run as smoothly, securely, or optimally as it should.
Remembering that, like financial debt, the short-cuts that result in technical debt are like the process of borrowing money now to pay later, technical debt can come from a variety of sources during the developmental phases of the SDLC that is utilized for development, including:
As can be seen, technical debt is not just a matter of taking developmental short-cuts (though it usually is), it can also result from an enterprise making an application simply for quick profit, without the software being aligned to the strategy of the company. In such a situation, the application incurs debt because it does not sufficiently benefit the company with a positive ROI, in which it may have to be re-engineered later on to truly benefit the business vision of the enterprise. A broader definition of technical debt is any application that does not completely follow the software strategy of the company, and/or industry best practices.
Like financial debt, technical debt is like “borrowing” (i.e. taking short-cuts during software development) and isn’t necessarily a bad thing if the debt is paid off before it becomes a problem later on. But the Agile SDLC is unique since it utilizes an iterative, continuous approach to development and deployment. Since Agile developers often rush to produce a product or software to meet the due date without properly testing it, that is most often where they incur technical debt. Likewise, with Scrum development, sprints are often more function and performance-based, as opposed to writing optimized software that is tested, and that is fully secure.
Technical debt may not be negative if the “interest” does not accumulate before it is paid off. In a financial sense, borrowing may allow one to complete a significant task sooner than expected, while the interest becomes a problem only if the balance is not paid within the time limit. That said, technical debt may allow an engineer to develop novel systems within an application in a quick manner, which may not be a problem if the code can be utilized optimally later without it resulting in a “snowball” effect of bugs, security holes, and execution errors. Taking quick action in application development can allow a company to seize novel opportunities, reach new markets, and meet customer needs with the tradeoff existing as technical debt.
The root issue associated with technical debt in Agile SDLC models is the quick nature in which iterations are developed (often with functionality in mind) to meet deadlines. This often results in short-cuts being taken and an accumulation of bugs that often go ignored as more iterations are completed. However, with DevOps methodologies baked into Agile models, these models can be used to quickly and efficiently develop quality components in an application. These are the different types of technical debt that can exist within the ecosystem of Agile development methodologies and models.
There are three major types of technical debt (2019), the first of which is deliberate debt. This type of technical debt is the standard type of debt typically thought of when the term is used and is defined by engineers knowing the correct way to develop an application, yet choosing the “quick” (i.e. wrong) way for the sake of meeting deadlines, among other things. Remember, the quickest way is not always the wrong way, but it sometimes is. Oftentimes, engineers actually overly code for a simple solution, which is not optimal either.
The best and most direct way to manage deliberate debt is to creatively figure out the best way to develop an application that is quickest, but also the most optimal. A compromise between speed and efficiency is key. However, when this type of debt is unavoidable, creating a log detailing where shortcuts were taken can allow engineers to pay back the debt before it accumulates.
Bit Rot debt is a type of long-term debt where a system digitally “rots” due to non-optimal code-changes by engineers who may not understand the original design, and may thus maintain the system with bad, unnecessarily complex, or overly complex code that needs to be cleaned and/or scrapped. When this cleanup process does not happen, the system becomes completely unoptimized or even obsolete, and the original issues become unsolvable.
The best way to completely stop bit rot debt from accumulating is to allow engineers who understand the original design and intent of the system to continuously refactor the system and clean its code, while updating it to meet new requirements, resulting in an optimal evolution of the system.
Outdated Design is one of the more difficult types of debt to avoid and results from a constant evolution of enterprise needs and issues that need to be solved which the original design of an enterprise IT system was unable to incorporate into its development, making it outdated, and even irrelevant.
The only way to manage this type of debt is to attempt to balance future-proofing the system, while ensuring that the system can meet the company’s current needs. The system must also be designed to support enough significant refactoring to allow the system to be relevant enough to meet future needs and to solve unseen, future problems.
These major forms of technical debt may plague an Agile, iterative developmental approach during an application’s SDLC, but other forms of technical debt may become an issue as well.
Quality debt is a type of technical debt associated with customer-facing design and UI errors, bugs, and flaws in an application that affects the quality of the app’s usability, and contrasts the internally-facing, code-related technical debt that results in issues associated with how the application runs.
Process debt is a type of software-based technical debt associated with taking short-cuts in processes that can result in software systems not optimally executing or running. That is, process debt usually results from engineers using non-optimal processes and policies that fix a problem in the short-term, while creating more long-term issues in the system.
Feature debt is based on the theory that all new features in a software application create hypothetical error possibilities and thus additional ground for technical debt to accumulate. Essentially, an application should only have the most critical functions that are necessary in order to meet the strategic goals, as extra features often lead to extra debt accumulation.
User Experience debt – or UX debt – like quality debt, happens when engineers take less-than-optimal shortcuts in UI design, which results in unintentional design errors and issues with the user experience as a whole.
Skill debt is an issue associated with an engineer not currently having the right skill set for optimally solving an issue in software development, resulting in him/her instead using their current skill set to get the job done, albeit less optimally. This results from the engineer not wanting to take time to learn the new requisite skill to optimally solve the problem at hand.
Several best practices should be leveraged by industry professionals to ensure that technical debt is kept to a minimum when designing and engineering robust enterprise applications. Ways to mitigate technical debt revolve around managing development work, integrating testing workflows into the developmental process, and having optimal team collaboration to guarantee that all debt is paid off before becoming a significant issue.
One of the major ways that a company can reduce technical debt is by assigning specific teams and tasks that perform iterative testing of components of the application in development so that errors, bugs, and issues do not accumulate. Teams can also collaborate to keep debt logs to ensure that such debt is paid off quickly and efficiently before snowballing into a set of larger issues.
Automation is a critical way for testing software components for bugs in an application that is still under development, and can be leveraged by companies so that technical debt in the form of errors and bugs does not accumulate, which could potentially result in a costly and time-consuming code revamp.
Using an integrative approach like the DevOps model can keep technical debt to a minimum during the iterative development process associated with Agile development. Operations admins and testing teams can ensure that an application’s components (after each sprint) work optimally and are secure, and that they execute without major errors, bugs, or crashes. This keeps any technical debt from snowballing into larger issues later. Any errors, security holes and bugs that are found can be fixed on the spot during the iterative development process, instead of remaining to be fixed later, when it is too late.
Agile development allows for an unparalleled integrative developmental experience where technical debt is kept at an absolute minimum when testing and code review processes are hard-baked into its iterative, incremental approach. Being organized, having teams review code and testing components during the developmental process, while keeping the overall technical strategy in mind, can allow a business to avoid costly, time-consuming software reworking, repairs, and refactoring to pay off technical debt once the debt has accumulated beyond control. Using these industry best practices during Agile development workflows can help to keep things from spiraling out of control and save an enterprise a significant amount of time and resources, and can ensure that all engineered systems are relevant into the future.
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