Last week, Tricentis released its inaugural Quality Transformation Report, packed with eye-opening insights. According to the report, nearly two-thirds of global businesses are at serious risk of a software disruption within the next 12 months due to the growing practice of deploying untested code.

In attempts to ship software faster and more efficiently, there has been a noticeable decrease in quality, to the point where it threatens a catastrophic outcome. 

“In today’s hyper-competitive environment, software delivery is no longer just a technical discipline – it’s a defining factor of business success. Every industry is under pressure to move faster, innovate boldly, and embrace artificial intelligence (AI) as a catalyst for change. Yet, as revealed in [our] inaugural Quality Transformation Report, the race for software development and delivery speed often comes at the expense of overall quality, compounding risks and costs that quietly erode business performance. —-Tricentis

Through their research, the team identified a technology landscape marked by opportunity, but also by imbalance, with advances such as AI offering both the promise of testing automation and acceleration, even as misalignment around what truly defines high-quality software threatens to stall progress.

Therefore, in this report, we want to do a quick refresher on what constitutes high-quality software and why you might want to build one. 

The Kingpin: Software Code Quality

“Quality is whatever design and implementation choices minimize the total cost of keeping the software within spec over its lifetime, in the face of requirements that change gradually over time in a way that can only be partially predicted.”
— Glenford Myers, adapted

High-quality software is software that works as expected, is easy to maintain, and contains fewer bugs. There are a number of interlocking features that contribute to quality at scale—code readability, maintainability, testability, debuggability, and above all, predictability.

To be considered high quality, a software product must meet these technical and operational goals in a way that minimizes costs over its entire lifetime—development, deployment, and beyond.

But quality doesn’t just happen by accident.

“When I was a junior, my boss told me to change the appearance of the main window. The project was massive and tightly coupled—impossible to alter without breaking something. I counted ~50 functions with the same general name doing completely different things.

Later, I found a thread in the company forum where the team lead said this exact task had become impossible at the current state of the project. That was written a year before I even joined. Since then, the codebase has doubled.

I tried for a month and failed. I think the boss just wanted me fired.
— Anonymous software engineer, r/programming

This is not an isolated story. It’s the natural result of software where short-term hacks beat long-term strategy, as revealed by the Tricentis’ survey data, where organizations indicated clear prioritization of speed over quality. 

Nearly half (45%) of organizations surveyed in this research say they are focused on accelerating delivery, with only 13% emphasizing software quality. 

This productivity push, fueled in part by generative AI tools, is causing teams to cut corners with a surprising 63% of organizations admitting to releasing untested code into production while citing compressed release cycles (46%) and accidental oversights (40%) as the top reasons.

How might we prevent this?

Well, the findings are clear: according to Tricentis, software development and delivery teams that can balance the demands of velocity with discipline around quality and risk will lead the next wave of digital transformation. 

Those that fall short will continue to face mounting operational costs, increasing customer turnover, more frequent security breaches or compliance failures, as well as the ever-present risk of business disruption.

Also read: What Every Software Developer Must Know About Cybersecurity In 2025

Use Case Definition

Before code comes the requirement gathering process—arguably one of the most critical stages in a software project’s lifecycle. Without clearly defined and well-structured requirements, even the most talented development team can produce the wrong solution.

In Agile environments—especially those using Scrum—requirements are typically maintained in a product backlog, a dynamic and prioritized list of functionality to be developed over time. According to Mike Cohn, “Although product backlog items can be whatever the team desires, user stories have emerged as the best and most popular form of product backlog items.”

Waterfall vs Agile: Two Paths to Requirements

Requirement gathering is generally approached in one of two ways:

  • Waterfall Approach: Emphasizes comprehensive, upfront documentation. The software specification is detailed and fixed early, which makes changes later in the project expensive and impractical.
  • Agile Methodology: Requirements are expressed as user stories, which describe functionality from the user’s perspective. Agile accommodates evolving needs by iterating on features over successive sprints—allowing teams to respond flexibly to change.

For modern development teams, Agile has become the dominant paradigm—especially in complex or fast-moving domains, because it prioritizes collaboration over contracts, working software over documentation, and adaptability over rigid plans.

As a software development tool, user stories provide a good framework for teams to develop high-quality solutions without over-specification.

A common trait shared by high-quality software applications is their foundation in a disciplined, structured, and responsive requirements-gathering process. The journey from idea to high-quality deployment doesn’t begin with code, but with collaborative recruitment, discovery, and continuous refinement.

Documentation

Lastly, even clean code can be incomprehensible if the context isn’t shared. Inline comments, design documents, and onboarding guides foster a maintainable culture and are all part of the foundational formula for deriving high-quality software products.

In high-performing engineering teams, documentation serves several critical functions, including:

1. Preserving Technical Context

Code tells you what is being done; documentation tells you why. Design decisions made today may seem obvious in the moment, but quickly fade from memory. Without records of architectural reasoning, trade-offs, or assumptions, new developers are forced to rediscover the logic from scratch—slowing down onboarding and increasing the risk of errors.

Thus, well-maintained development documents help preserve institutional knowledge and reduce cognitive load for future contributors.

2. Smoother Onboarding and Team Scaling

As teams grow, institutional knowledge becomes harder to distribute informally. Effective documentation turns tribal knowledge into accessible learning paths. Onboarding guides, internal wikis, and README files are vital in reducing the ramp-up time for new engineers and ensuring consistency in implementation standards.

Without these, productivity dips and the risk of unintentional divergence from established patterns increases.

3. Consistency in Maintenance and Collaboration

When code is touched by dozens of hands over a product’s lifetime, the ability to understand its behavior quickly becomes paramount. Inline comments and function-level documentation make it easier for teammates (and future you) to debug, refactor, or extend functionality without accidentally breaking something.

Moreover, good documentation standards—like consistent API references, developer guides, and change logs—support seamless handoffs between teams and reduce bottlenecks in cross-functional collaboration.

4. Regulatory and Security Compliance

In industries where compliance is non-negotiable (finance, healthcare, defense), documentation isn’t just helpful—it’s legally required. Auditors and security analysts rely on clearly documented processes, data handling flows, access controls, and dependency logs to verify that the system meets necessary standards.

Why It Matters

As code quality is ignored, velocity slows, bugs multiply, and trust erodes—both among developers and from users. The long-term cost of this is not just measured in crashes or outages, but in burnout, missed deadlines, and the eventual rewriting of entire systems.

On the other hand, investing in code quality:

  • Lowers total cost of ownership.
  • Enables faster iteration and innovation.
  • Makes onboarding easier.
  • Improves cross-functional collaboration.
  • Delivers a better, more reliable user experience.

Just as entropy naturally increases in physical systems, bad code compounds unless actively countered; therefore, building quality in—from the first line of code to the last commit—isn’t a luxury. 

It’s the only sustainable path forward towards a future where demand for faster product iteration and the accidental oversight issues we presently face do not lead to the predicted increase in operational costs, customer turnover, more frequent security breaches, and ever-present risk of business disruption.

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