Abstraction Level Leaps: How Software Engineering Evolves Through Structural Design

Software engineering's core thinking revolves around conceiving, insight into, and understanding software structure. Structure, trade-off decisions, and constraints embody the essence of software design wisdom.

Understanding software structure mirrors understanding all man-made things. From a single nut to an engine, wing, and finally an airplane, different hierarchical structures connect cleverly to form a useful artifact. Biological systems are even more exquisite: DNA's double helix, built from four base pairs, forms genes and proteins whose three-dimensional structures determine function. Software systems similarly exhibit hierarchical structures — fine-grained data structures and algorithms, medium-grained concurrency and communication patterns, and coarse-grained architectural patterns.

Decision-making involves evaluating countless methods and trade-offs under multiple constraints: technical (physical laws, algorithmic limits), human (team organization, skill acquisition), economic (ROI), legal (digital rights), and ethical (should we do it). Software engineers balance these forces; code is merely one tool, not the sole driver.

Through abstraction — designing structure, making trade-offs, respecting constraints — engineers create layered abstraction structures. Higher-level structures boost engineer efficiency; higher-level design primitives (both human-executable and machine-executable) enable construction of more complex systems.

The history of software engineering is a process of abstraction-level leaps: from functions and classes, rising to libraries, packages, and middleware platforms such as AOSP, the Linux kernel, Redis, and Kubernetes. When abstraction moved from assembly to high-level languages, engineers could finally focus on the "system" itself.

Researching software engineering and next-generation AI-driven software engineering demands a better grasp of the brain's overall architecture. In this process, the author realized that software design must preserve structures the way biological evolution preserves them via genes. For AI to deliver value, it must continuously construct and inherit structures; AI code needs a "gene" to encode structure — these code genes are precisely the design primitives at each hierarchical level.

Code is the final expression of every process. Each abstraction-level upgrade introduces higher-level design primitives and tools that eliminate repetitive wheel-reinventing, unleash massive productivity, and let us build grander, more complex systems.