We'll always have source code

Will AI change programming? Will it eliminate the need for programmers? Will we no longer need programs, or rather, the source code for programs? I think we will always have source code, and therefore always have programmers. But perhaps not as we think of programmers and source code today.

But first, let's review the notions of computers, software, and source code.

Programming has been with us almost as long as we have had electronic computers.

Longer than that, if we include the punch cards used by the Jacquard loom, But let's stick to electronic computers and the programming of them.

The first digital electronic computers were built in the 1940s. They were programming not by software but by wires -- connecting various wires to various points to perform a specific set of computations. There was no concept of a program -- at least not one for the computer. There were no programming languages and there was no notion of source code.

The 1950s saw the introduction of the stored-program computer. Instead of wiring plug-boards, program instructions were stored in cells inside the computer. We call these instructions "machine code". When programming a computer, machine code is a slightly more convenient than wiring plug-boards, but not by much. Machine code consists of a number of instructions, which each reside at distinct, sequential locations in memory. The processor executes the program by simply reading one instruction from a starting location, executing it, and then reading the next instruction at the next memory address.

Building a program in machine code took a lot of time and required patience and attention to detail. Changing a program often meant inserting instructions, which meant that the programmer had to recalculate all of the destination addresses for loops, branches, and subroutines. With stored-program computers, there was the notion of programming, but not the notion of source code.

Source code exists to be processed by a computer and converted into machine code. We first had source code with symbolic assemblers. Assemblers were (and still are) programs that read a text file and generate machine code. Not just any text file, but a text file that follows specific rules for content and formatting, and specifies a series of machine instructions but as text -- not as numbers. The assembler did the grunt work of converting "mnemonic" codes to numeric machine codes. It also converted numeric and text data to the proper representation for the processor, and calculated the destinations for loops, branches, and subroutines. Revising a program written in assembly language was much easier than revising machine code.

Later languages such as FORTRAN and COBOL converted higher-level text into machine code. They, too, had source code.

Early C compilers converted code into assembly code, which then had to be processed by an assembler. This last sequence looked like this:

    C source code --> [compiler] --> assembly source code --> [assembler] --> machine code

I've listed both the C code and the assembly code as "source code", but in reality only the C code is the source code. The assembly code is merely an intermediate form of the code, something generated by machine and later read by machine.

A better description of the sequence is:

    C source code --> [compiler] --> assembly code --> [assembler] --> machine code

I've changed the "assembly source code" to "assembly code". The adjective "source" is not really correct for it. The C program (at the left) is the one and only source.

Later C compilers omitted this intermediate step and generated machine code directly. The sequence become:

    C source code --> [compiler] --> machine code

Now let's consider AI. (You didn't forget about AI, did you?)

AI can be used to create programs in two ways. One is to enhance a traditional programming IDE with AI, and thereby assist the programmer as he (or she) is typing. That's no different from our current process; all we have done is made the editor a bit smarter.

The other way is to use AI directly and ask it to create the program. In this method, a programmer (or perhaps a non-programmer) provides a prompt text to an AI engine and the AI engine creates the entire program, which is then compiled into machine code. The sequence looks like this:

    AI prompt text --> [AI engine] --> source code --> [compiler] --> machine code

Notice that the word "source" has sneaked back into the middle of the stream. The term doesn't belong there; that code is intermediate and not the source. A better description is:

    Source AI prompt text --> [AI engine] --> intermediate code --> [compiler] --> machine code

This description puts the "source" back on the first step of the process. That prompt text is the true source code. One may argue that a prompt text is not really source code, that it is not specific enough, or not Turing-complete, or not formatted like a traditional program. I think that it is the source code. It is created by a human and it is the text used by the computer to generate the machine code that we desire. That makes it the source.

Notice that in this new process with AI, we still have source code. We still have a way for humans to instruct computers. I've been writing about source code as if it were written. Source code has always been written (or typed, or keypunched) in the past. It is possible that future systems recognize human speech and build programs from that (much like on several science fiction TV programs). If so, those spoken words will be the source code.

AI may change the programming world. It may upend the industry. It may force many programmers to learn new skills, or to retire. But humans will always want to express their desires to computers. The way they express them may be through text, or through speech, or (in some far-off day) through direct neural links. Those thoughts will be source code, and we will always have it. The people who create that source code are programmers, so we will always have them.

We will always have source code and programmers, but source code and programming will change over time.

Executables, source code, and automated tests

People who use computers tend to think of the programs as the "real" software.

Programmers tend to have a different view. They think of the source code as the "real" software. After all, they can always create a new executable from the source code. The generative property of source code gives it priority of the mere performant property of executable code.

But that logic leads to an interesting conclusion. If source code is superior to executable code because the former can generate the latter, then how do we consider tests, especially automated tests?

Automated tests can be used to "generate" source code. One does not use tests to generate source code in the same, automated manner that a compiler converts source code to an executable, but the process is similar. Given a set of tests, a framework in which to run the tests, and the ability to write source code (and compile it for testing), one can create the source code that produces a program that conforms to the tests.

That was a bit of a circuitous route. Here's the concept in a diagram:


     automated tests --> source code --> executable code


This idea has been used in a number of development techniques. There is test-driven development (TDD), extreme programming (XP), and agile methods. All use the concept of "test first, then code" in which tests (automated tests) are defined first and only then is code changed to conform to the tests.

The advantage of "test first" is that you have tests for all of your code. You are not allowed to write code "because we may need it someday". You either have a test (in which case you write code) or you don't (in which case you don't write code).

A project that follows the "test first" method has tests for all features. If the source code is lost, one can re-create it from the tests. Granted, it might take some time -- this is not a simple re-compile operation. A complex system will have thousands of tests, perhaps hundreds of thousands. Writing code to conform to all of those tests is a manual operation.

But it is possible.

A harder task is going in the other direction, that is, writing tests from the source code. It is too easy to omit cases, to skip functionality, to misunderstand the code. Given the choice, I would prefer to start with tests and write code.

Therefore, I argue that the tests are the true "source" of the system, and the entity we consider "source code" is a derived entity. If I were facing a catastrophe and had to pick one (and only one) of the tests, the source code, and the executable code, I would pick the tests -- provided that they were automated and complete.