Maintainability

Software Engineering / 09 Sep 2026 / 8 min read

Reducing Positional Coupling in Function Calls

A function can be perfectly implemented and still be easy to call incorrectly. One common cause is a parameter list in which several values have the same representation and their meaning depends mainly on position. Consider a reporting function that accepts three dates. At the call site, the values may all look valid even when two of them are accidentally reversed. A compiler or type checker often cannot help because each argument still has the expected type.

Software Engineering API Design

Software Engineering / 09 Sep 2026 / 8 min read

Reducing Coupling with the Law of Demeter

A small change to one class should not routinely force edits in code that is several objects away. Yet this happens when callers navigate through collaborators to reach deeper objects: order.customer().address().country().code() The line is compact, but the caller now knows that an order exposes a customer, a customer exposes an address, an address exposes a country, and a country exposes a code. If that structure changes, the caller may need to change even when the business question it asks stays the same.

Software Engineering Code Quality

Software Engineering / 09 Sep 2026 / 8 min read

Null Object Pattern for Optional Behavior

Optional behavior often begins with one harmless-looking condition. A component may send notifications only when a notifier is configured, record metrics only when metrics are enabled, or write audit events only in some deployments. As the code grows, the same absence check can spread across many call sites: if notifier != null: notifier.send(message) The condition is simple, but repetition creates a maintenance problem. Every caller must remember that the collaborator may be absent and must know what absence means.

Software Engineering Design Patterns

Software Engineering / 09 Sep 2026 / 9 min read

Moving Behavior Toward the Data It Uses

A method can live in one class while doing most of its work with another class’s data. At first this may seem harmless: the code runs, the names are clear, and the calculation is short. Over time, however, the method often becomes a second place that knows how the other object works. That design smell is commonly called feature envy. A piece of behavior appears to “envy” another object’s features because it reads that object’s state or calls its methods much more than it uses its own.

Software Engineering Refactoring

Software Engineering / 09 Sep 2026 / 8 min read

Making Complex Rules Visible with Decision Tables

Conditional code often starts clearly. One condition becomes two, then a special case appears, and eventually nobody can answer a simple question with confidence: have we covered every meaningful combination? The problem is not necessarily that if statements are bad. The problem is that branching code makes a set of rules visible one execution path at a time. When several independent conditions affect one decision, developers must mentally reconstruct the whole rule set from those paths.

Software Engineering Software Design

Software Engineering / 09 Sep 2026 / 8 min read

Isolating Hard-to-Test Code with a Humble Object

Some code is difficult to test for reasons that have little to do with the behavior you care about. A screen handler may require a UI framework. A file watcher may need operating-system events. A message consumer may only run inside a broker callback. Tests become slow or fragile because ordinary business decisions are trapped inside code that is expensive to execute in isolation. The Humble Object pattern addresses this by separating the difficult boundary from the logic behind it. The boundary object stays deliberately small: it translates an external event into plain data, calls ordinary code, then translates the result back. The decisions move into code that can be exercised without the framework or environment.

Software Engineering Software Design

Software Engineering / 09 Sep 2026 / 8 min read

Information Hiding: Design Modules Around Decisions

A module can have a tidy directory, a small public API, and still be difficult to change. The problem often appears when callers know details that should have remained private: how an identifier is formatted, which algorithm selects a price, or which fields must be updated together. When those details change, callers change with them. Information hiding is a design principle for reducing that coupling. The idea is simple: identify a design decision that may change, place it behind a module boundary, and expose the capability callers need rather than the decision’s internal details.

Software Engineering Modularity

Software Engineering / 09 Sep 2026 / 8 min read

Finding Seams for Safer Code Changes

Sometimes a small code change feels much larger than the requirement. You want to test one decision, replace one dependency, or alter one behavior, but the code gives you no place to do that without executing or editing a large surrounding block. A useful way to reason about this problem is to look for a seam: a place where you can change the behavior of a program without editing the code that uses that behavior. A seam might be a function parameter, an object boundary, a configurable callback, or another point where one implementation can be substituted for another.

Software Engineering Refactoring

Software Engineering / 09 Sep 2026 / 9 min read

Feature Flags Need a Removal Plan

A feature flag can make a risky change easier to release. You deploy both the old and new behavior, choose which one runs at runtime, and change that choice without rebuilding the application. The same mechanism creates a maintenance problem. Every flag adds another condition the code may execute under. If the flag remains after the decision is settled, developers must keep reasoning about behavior that no longer needs to be optional.

Software Engineering Software Design

Software Engineering / 09 Sep 2026 / 9 min read

Command-Query Separation for Predictable Operations

A method that returns a value can look harmless even when calling it changes the system. That mismatch creates bugs that are difficult to see at the call site: remaining = cart.removeItem(itemId) Does removeItem only remove the item? Does it return the removed item, the number of remaining items, or a success flag? More importantly, can code safely call it while merely trying to inspect the cart?

Software Engineering Code Quality

Software Engineering / 09 Sep 2026 / 8 min read

Characterization Tests Before Changing Legacy Code

Changing unfamiliar code creates a difficult question: how do you know a refactor preserved behavior when nobody can state exactly what the current behavior is? Existing unit tests may be sparse. Documentation may describe the intended rules but not the edge cases the system actually implements. Some odd behavior may even have become a dependency for callers. A characterization test helps in this situation. Instead of starting from what the code ought to do, it records what the code does now for a carefully chosen input. That gives you a behavioral reference point before you change the implementation.

Software Engineering Testing

Software Engineering / 09 Sep 2026 / 7 min read

Adding Behavior with the Decorator Pattern

A component often starts with one clear responsibility and then attracts optional behavior. A client sends a request; later the system also needs logging. Some deployments need metrics. Others need caching or access checks. Putting every option inside the original component can make its core job harder to see, while creating subclasses for every combination quickly becomes awkward. The Decorator pattern offers another shape. A decorator implements the same contract as the component it wraps, performs additional work, and delegates the main operation to that wrapped component. Because callers still see the same contract, decorators can be added, removed, and combined without teaching callers about each feature.

Software Engineering Design Patterns

Software Engineering / 08 Sep 2026 / 9 min read

Turning Validation into Trusted Data

A request enters an application with an email address, a quantity, and a delivery method. The request handler validates all three fields. Later, the pricing code checks the quantity again. The notification code checks the email again. A background job checks the delivery method again. The system has validation, but developers still cannot tell which values are safe to use without checking them first. A more useful design goal is to make validation change what the program knows about the data. Unchecked input crosses a boundary, validation establishes specific facts, and successful validation produces a representation that preserves those facts. Code after that boundary can then rely on the representation instead of repeatedly rediscovering the same conditions.

Software Engineering Software Design

Software Engineering / 08 Sep 2026 / 9 min read

Testing Hard-to-Test Code with Humble Objects

Some code is difficult to test for reasons that have little to do with the behavior you care about. A user-interface callback depends on a framework event loop. A scheduled job reads the clock, queries a service, writes a file, and decides whether to alert someone. A device handler receives data through an operating-system API before applying a simple rule. When the decision and the awkward environment live in the same unit, every test inherits the environment’s complexity. The test may need framework setup, timing control, filesystem state, or several mocks just to reach a small branch.

Software Engineering Testing

Software Engineering / 08 Sep 2026 / 7 min read

Testing Complex Rules with Decision Tables

A rule can be easy to understand one condition at a time and still be difficult to test correctly when several conditions interact. Consider a refund policy. A refund depends on whether the order is within 30 days, whether the item is damaged, and whether it was marked final sale. Writing a few examples from memory can miss an important combination. Adding every possible combination can create noisy tests that repeat the same reasoning.

Software Engineering Testing

Software Engineering / 08 Sep 2026 / 8 min read

Replacing Repeated Absence Checks with the Null Object Pattern

Optional collaborators often begin innocently. A service may have a notifier when notifications are enabled, a metrics recorder when monitoring is configured, or an audit sink in environments that need auditing. The first absence check is easy to understand. The twentieth can make the real behavior harder to see. The Null Object pattern is one way to remove that repetition. Instead of representing “no collaborator” with a null-like value and asking every caller to handle it, provide an object that implements the same contract with behavior appropriate for absence.

Software Engineering Design Patterns

Software Engineering / 08 Sep 2026 / 9 min read

Refactoring Feature Envy by Moving Behavior

A method belongs to InvoiceService, but most of its code asks an Invoice for fields, combines those fields according to invoice rules, and barely uses the service’s own state. Every time the invoice model changes, the service changes with it. This is a common design smell called feature envy: behavior lives in one place but depends heavily on the data or rules owned by another place. The name is less important than the maintenance problem. Knowledge that belongs together is split across a boundary, so one conceptual change requires coordinated edits.

Software Engineering Refactoring

Software Engineering / 08 Sep 2026 / 8 min read

Parse Inputs into Trusted Data at System Boundaries

Input validation often begins as a few sensible checks and slowly spreads through a codebase. A controller checks that an amount is positive. A service checks it again. A helper receives the same primitive value and checks it a third time because it cannot tell whether the earlier checks ran. The problem is not that validation is useless. The problem is that the program keeps carrying data in a form that does not record what has already been established.

Software Engineering Software Design

Software Engineering / 08 Sep 2026 / 10 min read

Making Resource Ownership Explicit

A function opens a file and returns a parser. A factory creates a client backed by a connection pool. A component starts a worker and hands another component a handle. Everything works until shutdown, an exception, or a refactor exposes a basic question that the design never answered: who is responsible for releasing the resource? Resource leaks are often described as missing cleanup calls. That is only the visible failure. The deeper design problem is ambiguous ownership. If several parts of the program can use a resource but none clearly owns its lifetime, cleanup becomes guesswork.

Software Engineering Software Design

Software Engineering / 08 Sep 2026 / 10 min read

Making Invalid States Hard to Represent

A function receives an Order and immediately checks whether its total is negative, its currency is missing, and its status is compatible with its payment state. Another function repeats some of those checks. A third forgets one. The codebase contains validation everywhere, yet invalid combinations still appear. The deeper problem is not a shortage of if statements. The program allows states that its own rules say should never exist, then asks every consumer to defend itself against them.

Software Engineering Software Design

Software Engineering / 08 Sep 2026 / 8 min read

Keeping Behavior Close to the Data It Uses

A method can live in the wrong place even when its code is correct. One common sign is a method that repeatedly reads another object’s fields, interprets those values, and makes a decision that is really about that other object. This creates a maintenance problem. The data and the rules governing that data change for related reasons, but the code is stored in different places. A small change to the meaning of the data can then require developers to find and update distant callers.

Software Engineering Software Design

Software Engineering / 08 Sep 2026 / 9 min read

Information Hiding as a Design Tool

A module can have private fields and still expose too much. Callers may know which storage format it uses, which sequence of operations is required, or which implementation rule determines a result. When that hidden-looking detail changes, code outside the module must change with it. Information hiding is a design principle for preventing that spread. The idea is simple: identify a design decision that other code should not need to know, then place that decision behind a boundary whose public contract can remain stable when the decision changes.

Software Engineering Software Design

Software Engineering / 08 Sep 2026 / 9 min read

Functional Core, Imperative Shell for Testable Business Logic

Business logic often becomes difficult to test for a reason that has little to do with the rule itself. A function that decides whether to approve a refund may also read a database, check the clock, call another service, write an audit record, and send a message. The decision is now mixed with the machinery required to obtain inputs and apply outputs. Tests must control all of that machinery just to ask, “What should happen for this refund?”

Software Engineering Software Design

Software Engineering / 08 Sep 2026 / 9 min read

Enforcing Architecture with Fitness Functions

A team can agree on a sensible architecture and still watch it erode one small change at a time. A developer imports an internal module because it is convenient. Another adds a direct dependency across layers. Months later, the diagram still shows clean boundaries, but the code no longer follows them. Code review can catch these changes, but reviewers must remember every architectural rule and notice every violation. For properties that matter repeatedly, memory is a weak enforcement mechanism.

Software Engineering Software Architecture