A while back, I had the opportunity to collaborate with my colleague, Philippe Gabriel, on a research project focused on automating defect finding and enhancing overall test coverage. Our primary concern at the time was null pointer dereferences, which had the potential to cause system-wide crashes. In our quest, we explored various strategies and tools, both free and commercial. However, what truly captured our interest was a fascinating area of research called “Symbolic execution.” Imagine having a tool that could automatically identify critical bugs in your source code with minimal or no false positives, while also generating input stimuli to trigger those bugs.

Having gained experience through numerous software projects and collaborations with diverse individuals, I’ve observed a recurring issue: a lack of understanding regarding the nature and process of software development. Surprisingly, even among developers, there persists a belief that seniority alone enables one to design and plan a problem, leaving less experienced developers to implement it. Some individuals still equate software development to assembly line production in the automotive industry.

In chapter 1 of “Structure and Interpretation of Computer Programs” SICP, Abelsson and Sussman describe a concept they call the “sorcerer’s spirit”

Let’s begin with an inspiring quote from my favorite book on computer programming, “Structure and Interpretations of Computer Programs” (SICP) by Abelson and Sussman.

Underlying our approach to this subject (computer programming) is our conviction that “computer science” is not a science and that its significance has little to do with computers. The computer revolution is a revolution in the way we think and in the way we express what we think. The essence of this change is the emergence of what might best be called procedural epistemology – the study of the structure of knowledge from an imperative point of view, as opposed to the more declarative point of view taken by classical mathematical subjects. Mathematics provides a framework for dealing precisely with notions of “what is”. Computation provides a framework for dealing precisely with notions of “how to”.

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