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Most of the time code is about reading rather than writing.

Always validate input

Most common error is from program that process input from user.

When writing a function or method, the top statement should be checking or validating input, then followed by processing the input, and finally returning the output from processing itself.

FUNCTION login(username, password) BOOLEAN
  // Check if username and password is not empty

  // Process login

  // Return the result of process
END FUNCTION

Use Constant

Rationale: using constant will minimize typo and provide easy refactoring.

Bad code example,

IF user == "administartor" THEN
END IF

will not print any error on build because typo on string. But if we use constant there will be an error or at least a hint on our IDE that the variable is undeclared.

Good code example,

const USER_ADMIN = "administrator"

IF user == USER_ADMIN THEN // OK
END IF
...
IF user == USER_ADNIN THEN // will return build error or hint (for example,
                           // red color or underscore) on our IDE.
END IF

Return first

Return first or return immediately is a concept to structuring our code to minimize if-else statements which in turn minimize code indentation.

Bad code example,

login(user, password) boolean {
	if user is exist {
		if password is equal {
			return true
		} else {
			return false
		}
	}

	return false
}

Good code example,

login(user, password) boolean {
	if user is not exist {
		return false
	}
	if password is not equal {
		return false
	}

	return true
}

Programming challenges

  • Write IF without ELSE

  • Write function body less than your screen size

Variable Naming

The name of variable should provide the context or data that their hold, it should be concise, not more than three words.

For example, instead of client, add prefix or suffix to indicate what client that variable hold for (tcpClient, httpClient).

Never have loop or indentation deeper than two

If we need loop deeper than two, then the second or third loop or indentation body should be moved to function.

At some point, we may have the following code in our function,

switch x {
case a:
	for ...
		if ...

case b:
	...
}
...

If body of "case a" may take more lines and indentations, that is an indication that the body should be moved to their own function.

The law of speed

Memory is faster than disk

There are two component where you can store data: disk or memory. Reading or writing data from disk is slower than memory. Reading or writing from disk is slower but the data will be stored permanently. Reading or writing data from memory is faster than disk but they were volatile. To get the advantages from disk and memory (permanent and faster) the technique is to load data from disk to memory at startup and store it again later when finished or when data changed.

Common technique to sync data from disk to memory and vice versa,

  1. Load data from disk at startup

  2. Setup a timer, for example, for every 1 minute, dump data to disk only data is changing (e.g. have a dirty flag on each record)

  3. Dump data to disk when exit

Use integer for index/key instead of string

Comparing integer is faster than comparing string, because processor has a native comparison for integer. The naive algorithm for comparing two strings is actually works like these (*),

FUNCTION CMP_STRING(a STRING, b STRING) BOOLEAN
BEGIN
	FOR c1 := each character in a {
		FOR c2 := each character in b {
			IF c1 != c2 {
				RETURN false;
			}
		}
	}
	RETURN true;
END;

The worst case for above algorithm is O(n*m) where string is equally matched, and the best case is O(2) where the first IF condition will return false.

(*) Some programming language may have optimization where string is compared by bulk instead of per octet.

This is bad example of code using string as key,

Record {
	key string
	value string
}

...

IF r.key == "person" THEN
	...
END;

SWITCH r.key {
CASE "person":
	...
CASE "alien":
	...
}

We can refactor the key to use constant and integer and still make the code readable,

ENUM RecordType {
	PERSON: 0
	ALIEN: 1
}

Record {
	key RecordType
	value string
}


IF r.key == RecordType.PERSON
	...
END;

SWITCH r.key {
case RecordType.PERSON:
	...
case RecordType.ALIEN:
	...
}

Use temporary variable

There are two common cases where using variable make the code more readable and faster. The first case is by storing each return function call to temporary variable instead of chaining them; the second case is by storing each computation in temporary variable.

Bad example of first case,

doX(doY(x, y))

In the above example, call to function doX based on return value of function doY. It may give clear statement because in the example the function name is short, but we recommended if we split them into two statements,

y = doY(x, y)
doX(y)

Bad example of second case,

a = y + z*10
b = doB(z*10)

It is common that I found sometimes the same computation is declared more than once on the same function. In this case is "z*10". We can rewrite the function by storing known computation into temporary variable,

tmp := z * 10
a = y + tmp
b = doB(tmp)

Note that, some compilers may or may not how to optimize the static computation depends on the type of z.

Use string concatenation instead of Printf

Rationale: printf-like statement require parsing formatted parameter, checking the "%x" input with type of arguments, and then converting back to string. Logically, it will use more operations than concatenation because its happened at compile time.

This is may vary between programming language, but in most case using "+" is faster that "Printf" or join function.

For Go, see the following benchmark.

## Run: go test -benchmem -bench .
## Output
## goos: linux
## goarch: amd64
## BenchmarkJoin-2         10000000               142 ns/op              32 B/op          2 allocs/op
## BenchmarkSprintf-2       2000000               609 ns/op              96 B/op          6 allocs/op
## BenchmarkConcat-2       20000000               106 ns/op               0 B/op          0 allocs/op
## BenchmarkBuffer-2       10000000               176 ns/op             112 B/op          1 allocs/op
## PASS
## ok      _/home/ms/Unduhan/sandbox/go/stringsconcat      7.614s

package stringsconcat

import (
	"bytes"
	"fmt"
	"strings"
	"testing"
)

var (
	testData = []string{"a", "b", "c", "d", "e"}
)

func BenchmarkJoin(b *testing.B) {
	for i := 0; i < b.N; i++ {
		s := strings.Join(testData, ":")
		_ = s
	}
}

func BenchmarkSprintf(b *testing.B) {
	for i := 0; i < b.N; i++ {
		s := fmt.Sprintf("%s:%s:%s:%s:%s", testData[0], testData[1], testData[2], testData[3], testData[4])
		_ = s
	}
}

func BenchmarkConcat(b *testing.B) {
	for i := 0; i < b.N; i++ {
		s := testData[0] + ":" + testData[1] + ":" + testData[2] + ":" + testData[3] + ":" + testData[4]
		_ = s
	}
}

func BenchmarkBuffer(b *testing.B) {
	for i := 0; i < b.N; i++ {
		var b bytes.Buffer
		b.WriteString(testData[0])
		b.WriteByte(':')
		b.WriteString(testData[1])
		b.WriteByte(':')
		b.WriteString(testData[2])
		b.WriteByte(':')
		b.WriteString(testData[3])
		b.WriteByte(':')
		b.WriteString(testData[4])
		s := b.String()
		_ = s
	}
}

Prevent using regex if possible

Technically, regular expression or regex actually is a meta language. They need to be parsed and checked; and when doing processing of input require reading each octet from beginning until end.

Using regex on testing is make sense to match the output with expected case, in case output is arbitrary and require their own parsing.

Further readings

  • Big-O or how to calculate an algorithm performance