Software design has two main aspects:

• Product/external design: designing the external behavior of the product to meet the users' requirements. This is usually done by product designers with the input from business analysts, user experience experts, user representatives, etc.
• Implementation/internal design: designing how the product will be implemented to meet the required external behavior. This is usually done by software architects and software engineers.

The guiding principle of abstraction is that only details that are relevant to the current perspective or the task at hand needs to be considered. As most programs are written to solve complex problems involving large amounts of intricate details, it is impossible to deal with all these details at the same time. That is where abstraction can help.

Ignoring lower level data items and thinking in terms of bigger entities is called data abstraction.

Control abstraction abstracts away details of the actual control flow to focus on tasks at a simplified level.

Abstraction can be applied repeatedly to obtain progressively higher levels of abstractions.

Abstraction is a general concept that is not limited to just data or control abstractions.

Coupling is a measure of the degree of dependence between components, classes, methods, etc. Low coupling indicates that a component is less dependent on other components. High coupling (aka tight coupling or strong coupling) is discouraged due to the following disadvantages:

• Maintenance is harder because a change in one module could cause changes in other modules coupled to it (i.e. a ripple effect).
• Integration is harder because multiple components coupled with each other have to be integrated at the same time.
• Testing and reuse of the module is harder due to its dependence on other modules.

In the example below, design A appears to have a more coupling between the components than design B.

X is coupled to Y if a change to Y can potentially require a change in X.

class Foo{
    ...
    new Bar().read();
    ...
}

class Bar{
    void read(){
        ...
    }
    
    void write(){
        ...
    }
}

Some examples of different coupling types:

• Content coupling: one module modifies or relies on the internal workings of another module  e.g., accessing local data of another module
• Common/Global coupling: two modules share the same global data
• Control coupling: one module controlling the flow of another, by passing it information on what to do  e.g., passing a flag
• Data coupling: one module sharing data with another module  e.g. via passing parameters
• External coupling: two modules share an externally imposed convention  e.g., data formats, communication protocols, device interfaces.
• Subclass coupling: a class inherits from another class. Note that a child class is coupled to the parent class but not the other way around.
• Temporal coupling: two actions are bundled together just because they happen to occur at the same time  e.g. extracting a contiguous block of code as a method although the code block contains statements unrelated to each other

Cohesion is a measure of how strongly-related and focused the various responsibilities of a component are. A highly-cohesive component keeps related functionalities together while keeping out all other unrelated things.

Higher cohesion is better. Disadvantages of low cohesion (aka weak cohesion):

• Lowers the understandability of modules as it is difficult to express module functionalities at a higher level.
• Lowers maintainability because a module can be modified due to unrelated causes  (reason: the module contains code unrelated to each other) or many many modules may need to be modified to achieve a small change in behavior  (reason: because the code realated to that change is not localized to a single module).
• Lowers reusability of modules because they do not represent logical units of functionality.

Cohesion can be present in many forms. Some examples:

• Code related to a single concept is kept together, e.g. the Student component handles everything related to students.
• Code that is invoked close together in time is kept together, e.g. all code related to initializing the system is kept together.
• Code that manipulates the same data structure is kept together, e.g. the GameArchive component handles everything related to the storage and retrieval of game sessions.

Resources:

• Java Varargs feature (from Oracle.com)
• Java Varargs tutorial (for javaTpoint.com)

Always code as if the person who ends up maintaining your code will be a violent psychopath who knows where you live. _{-- Martin Golding}

Production code needs to be of high quality . Given how the world is becoming increasingly dependent of software, poor quality code is something we cannot afford to tolerate.

One essential way to improve code quality is to follow a consistent style. That is why software engineers follow a strict coding standard (aka style guide).

The aim of a coding standard is to make the entire code base look like it was written by one person. A coding standard is usually specific to a programming language and specifies guidelines such as the location of opening and closing braces, indentation styles and naming styles (e.g. whether to use Hungarian style, Pascal casing, Camel casing, etc.). It is important that the whole team/company use the same coding standard and that standard is not generally inconsistent with typical industry practices. If a company's coding standards is very different from what is used typically in the industry, new recruits will take longer to get used to the company's coding style.

💡 IDEs can help to enforce some parts of a coding standard e.g. indentation rules.

Go through the provided Java coding standard and learn the intermediate style rules.

Programs should be written and polished until they acquire publication quality. _{--Niklaus Wirth}

Among various dimensions of code quality, such as run-time efficiency, security, and robustness, one of the most important is understandability. This is because in any non-trivial software project, code needs to be read, understood, and modified by other developers later on. Even if we do not intend to pass the code to someone else, code quality is still important because we all become 'strangers' to our own code someday.

int subsidy() {
    int subsidy;
    if (!age) {
        if (!sub) {
            if (!notFullTime) {
                subsidy = 500;
            } else {
                subsidy = 250;
            }
        } else {
            subsidy = 250;
        }
    } else {
        subsidy = -1;
    }
    return subsidy;
}

int calculateSubsidy() {
    int subsidy;
    if (isSenior) {
        subsidy = REJECT_SENIOR;
    } else if (isAlreadySubsidised) {
        subsidy = SUBSIDISED_SUBSIDY;
    } else if (isPartTime) {
        subsidy = FULLTIME_SUBSIDY * RATIO;
    } else {
        subsidy = FULLTIME_SUBSIDY;
    }
    return subsidy;
}

def calculate_subs():
    if not age:
        if not sub:
            if not not_fulltime:
                subsidy = 500
            else:
                subsidy = 250
        else:
            subsidy = 250
    else:
        subsidy = -1
    return subsidy

def calculate_subsidy():
    if is_senior:
        return REJECT_SENIOR
    elif is_already_subsidised:
        return SUBSIDISED_SUBSIDY
    elif is_parttime:
        return FULLTIME_SUBSIDY * RATIO
    else:
        return FULLTIME_SUBSIDY

Be wary when a method is longer than the computer screen, and take corrective action when it goes beyond 30 LOC (lines of code). The bigger the haystack, the harder it is to find a needle.

If you need more than 3 levels of indentation, you're screwed anyway, and should fix your program. _{--Linux 1.3.53 CodingStyle}

In particular, avoid arrowhead style code.

Example:

Avoid complicated expressions, especially those having many negations and nested parentheses. If you must evaluate complicated expressions, have it done in steps (i.e. calculate some intermediate values first and use them to calculate the final value).

return ((length < MAX_LENGTH) || (previousSize != length)) && (typeCode == URGENT);

boolean isWithinSizeLimit = length < MAX_LENGTH;
boolean isSameSize = previousSize != length;
boolean isValidCode = isWithinSizeLimit || isSameSize;

boolean isUrgent = typeCode == URGENT;

return isValidCode && isUrgent;

return ((length < MAX_LENGTH) or (previous_size != length)) and (type_code == URGENT)

is_within_size_limit = length < MAX_LENGTH
is_same_size = previous_size != length
is_valid_code = is_within_size_limit or is_same_size

is_urgent = type_code == URGENT

return is_valid_code and is_urgent

The competent programmer is fully aware of the strictly limited size of his own skull; therefore he approaches the programming task in full humility, and among other things he avoids clever tricks like the plague. _{-- Edsger Dijkstra}

When the code has a number that does not explain the meaning of the number, we call that a magic number (as in “the number appears as if by magic”). Using a named constant makes the code easier to understand because the name tells us more about the meaning of the number.

return 3.14236;
...
return 9;

static final double PI = 3.14236;
static final int MAX_SIZE = 10;
...
return PI;
...
return MAX_SIZE-1;

return 3.14236
...
return 9

PI = 3.14236
MAX_SIZE = 10
...
return PI
...
return MAX_SIZE-1

Similarly, we can have ‘magic’ values of other data types.

"Error 1432"  // A magic string!

Make the code as explicit as possible, even if the language syntax allows them to be implicit. Here are some examples:

• [Java] Use explicit type conversion instead of implicit type conversion.
• [Java, Python] Use parentheses/braces to show grouping even when they can be skipped.
• [Java, Python] Use enumerations when a certain variable can take only a small number of finite values. For example, instead of declaring the variable 'state' as an integer and using values 0,1,2 to denote the states 'starting', 'enabled', and 'disabled' respectively, declare 'state' as type SystemState and define an enumeration SystemState that has values 'STARTING', 'ENABLED', and 'DISABLED'.

Lay out the code so that it adheres to the logical structure. The code should read like a story. Just like we use section breaks, chapters and paragraphs to organize a story, use classes, methods, indentation and line spacing in your code to group related segments of the code. For example, you can use blank lines to group related statements together. Sometimes, the correctness of your code does not depend on the order in which you perform certain intermediary steps. Nevertheless, this order may affect the clarity of the story you are trying to tell. Choose the order that makes the story most readable.

Avoid things that would make the reader go ‘huh?’, such as,

• unused parameters in the method signature
• similar things look different
• different things that look similar
• multiple statements in the same line
• data flow anomalies such as, pre-assigning values to variables and modifying it without any use of the pre-assigned value

As the old adage goes, "keep it simple, stupid” (KISS). Do not try to write ‘clever’ code. For example, do not dismiss the brute-force yet simple solution in favor of a complicated one because of some ‘supposed benefits’ such as 'better reusability' unless you have a strong justification.

Debugging is twice as hard as writing the code in the first place. Therefore, if you write the code as cleverly as possible, you are, by definition, not smart enough to debug it. _{--Brian W. Kernighan}

Programs must be written for people to read, and only incidentally for machines to execute. _{--Abelson and Sussman}

Optimizing code prematurely has several drawbacks:

• We may not know which parts are the real performance bottlenecks. This is especially the case when the code undergoes transformations (e.g. compiling, minifying, transpiling, etc.) before it becomes an executable. Ideally, you should use a profiler tool to identify the actual bottlenecks of the code first, and optimize only those parts.
• Optimizing can complicate the code, affecting correctness and understandability
• Hand-optimized code can be harder for the compiler to optimize (the simpler the code, the easier for the compiler to optimize it). In many cases a compiler can do a better job of optimizing the runtime code if you don't get in the way by trying to hand-optimize the source code.

A popular saying in the industry is make it work, make it right, make it fast which means in most cases getting the code to perform correctly should take priority over optimizing it. If the code doesn't work correctly, it has no value on matter how fast/efficient it it.

Premature optimization is the root of all evil in programming. _{--Donald Knuth}

Note that there are cases where optimizing takes priority over other things e.g. when writing code for resource-constrained environments. This guideline simply a caution that you should optimize only when it is really needed.

Avoid varying the level of abstraction within a code fragment. Note: The Productive Programmer (by Neal Ford) calls this the SLAP principle i.e. Single Level of Abstraction Per method.

readData();
salary = basic*rise+1000;
tax = (taxable?salary*0.07:0);
displayResult();

readData();
processData();
displayResult();

The happy path (i.e. the execution path taken when everything goes well) should be clear and prominent in your code. Restructure the code to make the happy path unindented as much as possible. It is the ‘unusual’ cases that should be indented. Someone reading the code should not get distracted by alternative paths taken when error conditions happen. One technique that could help in this regard is the use of guard clauses.

if (!isUnusualCase) {  //detecting an unusual condition
    if (!isErrorCase) {
        start();    //main path
        process();
        cleanup();
        exit();
    } else {
        handleError();
    }
} else {
    handleUnusualCase(); //handling that unusual condition
}

if (isUnusualCase) { //Guard Clause
    handleUnusualCase();
    return;
}

if (isErrorCase) { //Guard Clause
    handleError();
    return;
}

start();
process();
cleanup();
exit();

Proper naming improves the readability. It also reduces bugs caused by ambiguities regarding the intent of a variable or a method.

There are only two hard things in Computer Science: cache invalidation and naming things. _{-- Phil Karlton}

Every system is built from a domain-specific language designed by the programmers to describe that system. Functions are the verbs of that language, and classes are the nouns. _{― Robert C. Martin, Clean Code: A Handbook of Agile Software Craftsmanship}

Use nouns for classes/variables and verbs for methods/functions.

Distinguish clearly between single-valued and multivalued variables.

Person student;
ArrayList<Person> students;

student = Person('Jim')
students = [Person('Jim'), Person('Alice')]

Use correct spelling in names. Avoid 'texting-style' spelling. Avoid foreign language words, slang, and names that are only meaningful within specific contexts/times e.g. terms from private jokes, a TV show currently popular in your country

A name is not just for differentiation; it should explain the named entity to the reader accurately and at a sufficient level of detail.

If the name has multiple words, they should be in a sensible order.

Imagine going to the doctor's and saying "My eye1 is swollen"! Don’t use numbers or case to distinguish names.

While it is preferable not to have lengthy names, names that are 'too short' are even worse. If you must abbreviate or use acronyms, do it consistently. Explain their full meaning at an obvious location.

Related things should be named similarly, while unrelated things should NOT.

Avoid misleading or ambiguous names (e.g. those with multiple meanings), similar sounding names, hard-to-pronounce ones (e.g. avoid ambiguities like "is that a lowercase L, capital I or number 1?", or "is that number 0 or letter O?"), almost similar names.

Good code is its own best documentation. As you’re about to add a comment, ask yourself, ‘How can I improve the code so that this comment isn’t needed?’ Improve the code and then document it to make it even clearer. _{--Steve McConnell, Author of Clean Code}

Some think commenting heavily increases the 'code quality'. This is not so. Avoid writing comments to explain bad code. Improve the code to make it self-explanatory.

If the code is self-explanatory, refrain from repeating the description in a comment just for the sake of 'good documentation'.

Bad

// increment x
x++;

//trim the input
trimInput();

Do not write comments as if they are private notes to self. Instead, write them well enough to be understood by another programmer. One type of comments that is almost always useful is the header comment that you write for a class or an operation to explain its purpose.

// a quick trim function used to fix bug I detected overnight
void trimInput(){
    ....
}

/** Trims the input of leading and trailing spaces */
void trimInput(){
    ....
}

# a quick trim function used to fix bug I detected overnight
def trim_input():
    ...

def trim_input():
"""Trim the input of leading and trailing spaces"""
    ...

Comments should explain what and why aspect of the code, rather than the how aspect.

What : The specification of what the code supposed to do. The reader can compare such comments to the implementation to verify if the implementation is correct

/** Removes all spaces from the {@code input} */
void compact(String input){
    input.trim();
}

Why : The rationale for the current implementation.

// Remove spaces to comply with IE23.5 formatting rules
compact(input);

How : The explanation for how the code works. This should already be apparent from the code, if the code is self-explanatory. Adding comments to explain the same thing is redundant.

// return true if both left end and right end are correct or the size has not incremented
return (left && right) || (input.size() == size);

boolean isSameSize = (input.size() == size) ;
return (isLeftEndCorrect && isRightEndCorrect) || isSameSize;