A lesson from my accountant for software Engineers

A really interesting and insightful point about the core essence of software engineering. My Accountant said, You're essentially saying that while methodologies, patterns, and best practices are important frameworks, the ultimate success of a software project boils down to a clear understanding of the desired outcome – the "answer" – much like in accounting. Let's break down your thoughts:

Your Core Argument: Software as an Accounting Problem

Your analogy to accounting is quite compelling. In accounting:

• The Goal is Balance: The fundamental principle is ensuring debits equal credits, leading to a balanced financial picture.

• Known Answer (Ideally): While estimations and forecasts exist, the underlying goal is to accurately reflect financial reality. If you know all the transactions and apply the rules correctly, you should arrive at a balanced and accurate result.

• Steps and Processes: There are established procedures and principles (GAAP, IFRS) that guide the process of recording and reporting financial data.

You're suggesting that software development should ideally mirror this:

• The Goal is a Desired Outcome: A functional, performant, and valuable piece of software that meets specific business needs.

• Known Answer (The Ideal): If the business requirements are perfectly understood and translated into technical specifications, the "answer" – the desired state of the software – is theoretically known.

• Steps and Processes: Methodologies, patterns, and best practices are the "procedures" we use to build this software.

Why Software Isn't Perfectly Balanced (Yet)

You rightly point out that software development rarely achieves this perfect "balance" in practice. There are several reasons for this:

• Ambiguity and Evolving Requirements: Unlike well-defined accounting transactions, business needs and user expectations in software often evolve, are initially vague, or are discovered during the development process. The "answer" isn't always clear from the outset and can change.

• Complexity and Interdependencies: Software systems are often incredibly complex, with numerous interconnected components. Predicting the exact behavior and interactions of these components can be challenging, leading to unexpected outcomes.

• Human Factors and Creativity: Software development involves significant human creativity and problem-solving. Different engineers might approach the same problem in different ways, leading to variations in the final product, even if the end goal is the same.

• External Factors and Uncertainty: Technology landscapes change, third-party integrations can introduce complexities, and unforeseen technical challenges can arise, impacting the "balance" of the project.

• The "Art" in Engineering: While we strive for scientific rigor, there's still an element of art and intuition in software design and problem-solving, which can make it less predictable than a purely rule-based system like accounting.

• Difficulty in Quantifying "Perfection": What constitutes "perfect" software? Is it bug-free? Highly performant? Extremely user-friendly? These qualities can be subjective and difficult to measure definitively.

How to Move Closer to the "Balanced" Ideal

While achieving perfect accounting-like balance in software might be an aspirational goal, we can certainly strive to get closer:

• Stronger Business Analysis and Requirements Elicitation: Investing heavily in understanding the "answer" through thorough business analysis, clear user stories, and well-defined acceptance criteria is crucial. The more clarity upfront, the more likely we are to build the right thing.

• Iterative Development and Feedback Loops: Agile methodologies emphasize frequent feedback and adaptation. This allows us to course-correct and refine our understanding of the "answer" as we build, rather than rigidly following an initial, potentially flawed, plan.

• Robust Testing and Quality Assurance: Rigorous testing at all stages helps identify deviations from the expected "balance" (bugs, performance issues) early in the process.

• Data-Driven Decision Making: Using metrics and data to understand user behavior, system performance, and the impact of features can help us make more informed decisions and move towards a more "balanced" and effective product.

• Clear Communication and Collaboration: Effective communication between business stakeholders, analysts, developers, and testers ensures everyone is aligned on the "answer" and potential imbalances are identified and addressed.

• Focus on Maintainability and Observability: Building software that is easy to understand, monitor, and debug allows us to quickly identify and rectify imbalances that arise after deployment.

Conclusion

Your analogy of software development as an accounting problem highlights a fundamental truth: a clear understanding of the desired outcome is paramount. While the inherent complexities, human factors, and evolving nature of software prevent it from being a purely deterministic system like accounting, striving for that clarity and applying rigorous processes to achieve it is what drives successful software engineering. We may never reach perfect "balance," but by focusing on understanding the "answer" and continuously refining our approach, we can certainly build more effective, reliable, and valuable software.