Bad Programmer

Bad Programmers

Solving your skillset problems

Signs that you are a bad programmer

1. Inability to reason about code

Reasoning about code means being able to follow the execution path ("running the program in your head") while knowing what the goal of the code is.

Symptoms

1. The presence of "voodoo code", or code that has no effect on the goal of the program but is diligently maintained anyway (such as initializing variables that are never used, calling functions that are irrelevant to the goal, producing output that is not used, etc.)
2. Executing idempotent functions multiple times (eg: calling the save() function multiple times "just to be sure")
3. Fixing bugs by writing redundant code that overwrites the result of the faulty code
4. "YoYo code" that converts a value into a different representation, then converts it back to where it started (eg: converting a decimal into a string and then back into a decimal, or padding a string and then trimming it)
5. "Bulldozer code" that gives the appearance of refactoring by breaking out chunks into subroutines, but that are impossible to reuse in another context (very high cohesion)

Remedies

To get over this deficiency a programmer can practice by using the IDE's own debugger as an aide if it has the ability to step through the code one line at a time. In Visual Studio, for example, this means setting a breakpoint at the beginning of the problem area and stepping through with the 'F11' key, inspecting the value of variables--before and after they change--until you understand what the code is doing. If the target environment doesn't have such a feature, then practice in one that does.

The goal is to reach a point where you no longer need the debugger to be able to follow the flow of code in your head, and where you are patient enough to think about what the code is doing to the state of the program. The reward is the ability to identify redundant and unnecessary code, as well as how to find bugs in existing code without having to re-implement the whole algorithm from scratch.

2. Poor understanding of the language's programming model

Object Oriented Programming is an example of a language model, as is Functional or Declarative programming. They're each significantly different from procedural or imperative programming, just as procedural programming is significantly different from assembly or GOTO-based programming. Then there are languages which follow a major programming model (such as OOP) but introduce their own improvements such as list comprehensions, generics, duck-typing, etc.

Symptoms

1. Using whatever syntax is necessary to break out of the model, then writing the remainder of the program in imperative/procedural style
2. (OOP) Attempting to call non-static functions or variables in uninstantiated classes, and having difficulty understanding why it won't compile
3. (OOP) Writing lots of "xxxxxManager" classes that contain all of the methods for manipulating objects that have little or no methods of their own
4. (Relational) Treating the database as an object store by giving each table an identity column (or GUID) for the primary key, and possibly going as far as serializing the state of the object to a binary column
5. (Functional) Creating multiple versions of the same algorithm to handle different types or operators, rather than passing high-level functions to a generic implementation
6. (Functional) Manually caching the results of a deterministic function
7. (Pure Functional) Using cut-n-paste code from someone else's program to deal with I/O and Monads
8. (Declarative) Setting individual values in imperative code rather than using data-binding

Remedies

If your skills deficiency is a product of ineffective teaching or studying, then an alternative teacher is the compiler itself. There is no more effective way of learning a new programming model than starting a new project and committing yourself to use whatever the new constructs are, intelligently or not. You also need to practice explaining the model's features in crude terms of whatever you are familiar with, then recursively building on your new vocabulary until you understand the subtleties as well. For example:

Phase 1: "OOP is just records with methods"
Phase 2: "OOP methods are just functions running in a mini-program with its own global variables"
Phase 3: "The global variables are called fields, some of which are private and invisible from outside the mini-program"
Phase 4: "The idea of having private and public elements is to hide implementation details and expose a clean interface, and this is called Encapsulation"
Phase 5: "Encapsulation means my business logic doesn't need to be polluted with implementation details"

Phase 5 looks the same for all languages, since they are all really trying to get the programmer to the point where he can express the intent of the program without burying it in the specifics of how. Take functional programming as another example:

Phase 1: "Functional programming is just doing everything by chaining deterministic functions together"
Phase 2: "When the functions are deterministic, they don't need to be executed until the output is called for, and only for as much as needed. This is called Lazy Evaluation and Partial Evaluation"
Phase 3: "In order to support Lazy and Partial Evaluation, the compiler requires that I write functions in terms of how to transform a single parameter, sometimes into another function. This is called Currying"
Phase 4: "When all functions are curried, the compiler can choose the best execution plan by using a constraint solver"
Phase 5: "By letting a constraint solver figure out the mundane details, I can write programs by describing what I want, rather than how to give it to me"

3. Deficient research skills / Chronically poor knowledge of the platform's features

Modern languages and frameworks now come with an awesome breadth and depth of built-in commands and features, with some leading frameworks (Java, .Net, Cocoa) being too large to expect any programmer, even a good one, to learn in anything less than a few years. But a good programmer will search for a built-in function that does what they need before they begin to roll their own, and excellent programmers have the skill to break-down and identify the abstract problems in their task, then search for existing frameworks, patterns, models and languages that can be adapted before they even begin to design the program.

Symptoms

These are only indicative of the problem if they continue to appear in the programmer's work long after he should have mastered the new platform.

1. Re-inventing or laboring without basic mechanisms that are built-into the language, such as events-and-handlers or regular expressions
2. Re-inventing classes and functions that are built-into the framework (eg: timers, collections, sorting and searching algorithms)
3. "Email me teh code, plz" messages posted to help forums
4. "Roundabout code" that accomplishes in many instructions what could be done with far fewer (eg: rounding a number by converting a decimal into a formatted string, then converting the string back into a decimal)
5. Persistently using old-fashioned techniques even when new techniques are better in those situations (eg: still writes named delegate functions instead of using lambda expressions for one-offs)
6. Having a stark "comfort zone", and going to extreme lengths to solve complex problems with primitives

Remedies

A programmer can't acquire this kind of knowledge without slowing down, and it's likely that he's been in a rush to get each function working by whatever means necessary. He needs to have the platform's technical reference handy and be able to look through it with minimal effort, which can mean either having a hard copy of it on the desk right next to the keyboard, or having a second monitor dedicated to a browser. To get into the habit initially, he should refactor his old code with the aim of reducing its instruction count by 10:1 or more.

4. Inability to comprehend pointers

If you don't understand pointers then there is a very shallow ceiling on the types of programs you can write, as the concept of pointers enables the creation of complex data structures and efficient APIs. Managed languages use references instead of pointers, which are similar but add automatic dereferencing and prohibit pointer arithmetic to eliminate entire classes of bugs. They are still similar enough, however, that a failure to grasp the concept will be reflected in poor data-structure design and bugs that trace back to the difference between pass-by-value and pass-by-reference in method calls.

Symptoms

1. Failure to implement a linked list, or write code that inserts/deletes nodes from linked list without losing data
2. Allocating arbitrarily big arrays for variable-length collections and maintaining a separate collection-size counter, rather than using a linked list or other dynamic data structure
3. Inability to find or fix bugs caused by performing arithmetic on pointers
4. Modifying the dereferenced values from pointers passed as the parameters to a function, and not expecting it to change the values in the scope outside the function
5. Making a copy of a pointer, changing the dereferenced value via the copy, then assuming the original pointer still points to the old value
6. Serializing a pointer to the disk or network when it should have been the dereferenced value
7. Sorting an array of pointers by performing the comparison on the pointers themselves

Remedies

A friend of mine named Joe was staying somewhere else in the hotel, but I didn't know which room number. I did, however, know which room his acquaintance, Frank, was staying in. So I went up there and knocked on his door and asked him, "Where's Joe staying?" Frank didn't know, but he did know which room Joe's co-worker, Theodore, was staying in, and gave me that room number instead. So I went to Theodore's room and asked him where Joe was staying, and Theodore told me that Joe was in Room 414. And that, in fact, is where Joe was.

Pointers can be described with many different metaphors, and the data structures you can build translated into many analogies. The above is a simple analogy for a linked list, and anybody can invent their own, even if they aren't programmers. The comprehension failure doesn't occur when pointers are described, so you can't describe them any more thoroughly than they already have been. It fails when the programmer then tries to visualize what's going on in the computer's memory and it gets conflated with their understanding of regular variables, which are very similar. It may help to translate the code into a simple story to help reason about what's going on, until the distinction clicks and the programmer can visualize pointers and the data structures they enable as intuitively as scalar values and arrays.

5. Difficulty seeing through recursion

The idea of recursion is easy enough to understand, but programmers often have problems imagining the result of a recursive operation in their minds, or how a complex result can be computed with a simple function. This makes it harder to design a recursive function because you have trouble picturing "where you are" when you come to writing the test for the base condition or the parameters for the recursive call.

Symptoms

1. Hideously complex iterative algorithms for problems that can be solved recursively (eg: traversing a filesystem tree), especially where memory and performance is not a premium
2. Recursive functions that check the same base condition both before and after the recursive call
3. Recursive functions that don't test for a base condition
4. Recursive subroutines that concatenate/sum to a global variable or a carry-along output variable, and aren't implementing tail recursion
5. Apparent confusion about what to pass as the parameter in the recursive call, or recursive calls that pass the parameter unmodified

Remedies

Get your feet wet and be prepared for some stack overflows. Begin by writing code with only one base-condition check and one recursive call that uses the same, unmodified parameter that was passed. Stop coding even if you have the feeling that it's not enough, and run it anyway. It throws a stack-overflow exception, so now go back and pass a modified copy of the parameter in the recursive call. More stack overflows? Excessive output? Then do more code-and-run iterations, switching from tweaking your base-condition test to tweaking your recursive call until you start to intuit how the function is transforming its input. Resist the urge to use more than one base-condition test or recursive call unless you really know what you're doing.

Your goal is to have the confidence to jump in, even if you don't have a complete sense of "where you are" in the imaginary recursive path. Then when you now need to write a function for a real project you'd begin by writing a unit test first, and proceeding with the same technique above.

Signs that you are a mediocre programmer

1. Inability to think in sets

Transitioning from imperative programming to functional and declarative programming will immediately require you to think about operating on sets of data as your primitive, not scalar values. The transition is required whenever you use SQL with a relational database (and not as an object store), whenever you design programs that will scale linearly with multiple processors, and whenever you write code that has to execute on a SIMD-capable chip (such as modern graphics cards and video game consoles).

Symptoms

The following count only when they're seen on a platform with Declarative or Functional programming features that the programmer should be aware of.

1. Performing atomic operations on the elements of a collection within a for or foreach loop
2. Writing Map or Reduce functions that contain their own loop for iterating through the dataset
3. Fetching large datasets from the server and computing sums on the client, instead of using aggregate functions in the query
4. Functions acting on elements in a collection that begin by performing a new database query to fetch a related record
5. Writing business-logic functions with tragically compromising side-effects, such as updating a user interface or performing file I/O
6. Classes that open their own database connections or file handles and keep them open for their lifespan

Remedies

Funny enough, visualizing a card dealer cutting a deck of cards and interleaving the two stacks together by flipping through them with his thumbs can jolt the mind into thinking about sets and how you can operate on them in bulk. Other stimulating visualizations are:

• freeway traffic passing through an array of toll booths (parallel processing)
• springs joining to form streams joining to form creeks joining to form rivers (parallel reduce/aggregate functions)
• a newspaper printing press (coroutines, pipelines)
• the zipper tag on a jacket pulling the zipper teeth together (simple joins)
• transfer RNA picking up amino acids and joining messenger RNA within a ribosome to become a protein (multi-stage function-driven joins, see animation)
• the above happening simultaneously in billions of cells in an orange tree to convert soil, water and sunlight into orange juice (Map/Reduce on large distributed clusters)

If you are writing a program that works with collections, think about all the supplemental data and records that your functions need to work on each element and use Map functions to join them together in pairs before you have your Reduce function applied to each pair.

2. Lack of critical thinking

Unless you criticize your own ideas and look for flaws in your own thinking, you will miss problems that can be fixed before you even start coding. If you also fail to criticize your own code once written, you will only learn at the vastly slower pace of trial and error. This is the root of lazy thinking and egocentric thinking, so its symptoms seem to come from two different directions.

Symptoms

1. "Business Rule Engines"
2. Fat static utility classes, or multi-disciplinary libraries with only one namespace
3. Conglomerate applications, or attaching unrelated features to an existing application to avoid the overhead of starting a new project
4. Architectures that have begun to require epicycles
5. Adding columns to tables for tangential data
6. Inconsistent naming conventions
7. "Man with a hammer" mentality, or changing the definitions of problems so they can all be solved with one particular technology
8. Programs that dwarf the complexity of the problem they solve
9. Pathologically and redundantly defensive programming ("Enterprisey code")

Remedies

Start with a book like Critical Thinking by Paul and Elder, work on controlling your ego, and practice resisting the urge to defend yourself as you submit your ideas to friends and colleagues for criticism.

Once you get used to other people examining your ideas, start examining your own ideas yourself and practice imagining the consequences of them. In addition, you also need to develop a sense of proportion (to have a feel for how much design is appropriate for the size of the problem), a habit of double-checking assumptions (so you don't overestimate the size of the problem), and a healthy attitude towards failure (even Isaac Newton was wrong, but we needed him to try anyway).

Finally, you must have discipline. Being aware of flaws in your plan will not make you more productive unless you can muster the willpower to correct and rebuild what you're working on.

3. Pinball Programming

When you tilt the board just right, pull back the pin to just the right distance, and hit the flipper buttons in the right sequence, then the program runs flawlessly with the flow of execution bouncing off conditionals and careening unchecked toward the next state transition.

Symptoms

1. One Try-Catch block wrapping the entire body of Main() and resetting the program in the Catch clause (the pinball gutter)
2. Using strings/integers for values that have (or could be given) more appropriate wrapper types in a strongly-typed language
3. Packing complex data into delimited strings and parsing it out in every function that uses it
4. Failing to use assertions or method contracts on functions that make assumptions about their arguments
5. The use of Sleep() to wait for another thread to finish its task
6. Switch statements, on non-enumerated values, that don't have an "Otherwise" clause
7. Using Automethods or Reflection to invoke methods that are named in unqualified user input
8. Setting global variables in functions as a way to return multiple values
9. Classes with one method and a couple of fields, where you have to set the fields as the way of passing parameters to the method
10. Multi-row database updates without a transaction
11. Hail-Mary passes (eg: trying to restore the state of a database without a transaction and ROLLBACK)

Remedies

Imagine your program's input is water. It's going to fall through every crack and fill every pocket, so you need to think about what the consequences are when it flows somewhere other than where you've explicitly built something to catch it.

You will need to make yourself familiar with the mechanisms on your platform that help make programs robust and ductile. There are three basic kinds:

1. those which stop the program before any damage is done when something unexpected happens, then helps you identify what went wrong (type systems, assertions, exceptions, etc.),
2. those which direct program flow to whatever code best handles the contingency (try-catch blocks, multiple dispatch, event driven programming, etc.),
3. those which pause the thread until all your ducks are in a row (WaitUntil commands, mutexes and semaphores, SyncLocks, etc.)

There is also a fourth, Unit Testing, which you use at design time.

Using these ought to become second nature to you, like putting commas and periods in sentences. To get there, go through the above mechanisms (the ones in parenthesis) one at a time and refactor an old program to use them wherever you can cram them, even if it doesn't turn out to be appropriate (especially when they don't seem appropriate, so you also begin to understand why).

Signs that you shouldn't be a programmer

The following may not have any remedies if you still suffer from them after taking a programming course in school, so you will stand a better chance of advancing your career by choosing another profession.

1. Inability to determine the order of program execution

Symptoms

a = 5
b = 10
a = b

print a

1. You look at the code above and aren't sure what number gets printed out at the end

Alternative careers

1. Electrician
2. Plumber
3. Architect
4. Civil engineer

2. Insufficient ability to think abstractly

Symptoms

1. Difficulty comprehending the difference between objects and classes
2. Difficulty implementing design patterns for your program
3. Difficulty writing functions with low cohesion
4. Incompetence with Regular Expressions
5. Lisp is opaque to you
6. Cannot fathom the Church-Turing Thesis

Alternative careers

1. Contract negotiator
2. Method actor

3. Collyer Brothers syndrome

Symptoms

1. Unwilling to throw away anything, including garbage
2. Unwilling to delete anything, be it code or comments
3. The urge to build booby-traps for defense against trespassers
4. Unwilling to communicate with other people
5. Poor organization skills

Alternative careers

1. Antique dealer
2. Bag lady

4. Dysfunctional sense of causality

Symptoms

1. You seriously consider malice to be a reason why the compiler rejects your program
2. When called on to fix a bug in a deployed program, you try prayer
3. You take hidden variables for granted and don't think twice about blaming them for a program's misbehavior
4. You think the presence of code in a program will affect its runtime behavior, even if it is never invoked
5. Your debugging repertoire includes rituals like shining your lucky golf ball, twisting your wedding ring, and tapping the nodding-dog toy on your monitor. And when the debugging doesn't work, you think it might be because you missed one or didn't do them in the right order

Alternative careers

1. Playing the slot machines in Vegas