Decompiler Construction: Chapter 0 - Introduction

This series describes a full decompiler pipeline that lifts machine code into an intermediate representation, reconstructs control flow, and incrementally simplifies it into readable high-level code.

Before I started on this series of decompilers, I primarily started this not only to document the research I had made in it but also to get people to appreciate and understand how decompilers work under the hood. I have experience in building decompilers. Making my first one in 2020, albeit very limited, led to a system that can decompile large real-world binaries, including low-level system components. For reversers out there, you may be skeptical, although you should be aware that a lot of decompilers as of 2026 still face issues that I had to solve. I will be explaining everything in this blog in a structured way, whether you are a beginner or not, so that the material is accessible for everyone while still very useful. As of 2026, the current implementation of the decompiler is closed source, but the architecture, design, and techniques will be explained in detail throughout this series. One last thing before I jump in: I will be covering a lot of topics, so be prepared for a large amount of complex abstract content.

Approaches and Mindset

Decompilers are very hard and complex pieces of programs designed at the fundamental level to take something very hard to understand on its own and transform it into something someone with a decent amount of experience in that target can understand. There are several main approaches I will talk about:

Hueristical approach

Heuristically analyzing code means going through your target and simplifying known patterns one at a time. This approach has several main issues: one, if the pattern is never seen before, it will fail; two, if the pattern has smaller patterns in it, it will also fail. Here is an example of pseudo-code on how it works. Let’s say we have x - 0

Simple enough that it can be turned into x

Okay, let’s try a different example (x - 0) - 0

Now do you see the problem? We could keep doing this forever, and the amount of pure heuristics you will need to check is infinite. The solution to this problem is to stop thinking in terms of big and think in terms of small. Which leads us to the most popular and used approach:

Pass-based representation approach

We transform machine code into a structured intermediate representation (IR) by lifting (transforming) code into a unique IR from an Intermidiate Languege(IL). This serves two purposes. If the original code is architecture-dependent X86 or ARM, for example, our decompiler will only serve that architecture, but because we are making it independent from any architecture, albeit with some catches, we will get into that in the future, we can have a decompiler that works for any architecture that is possible to lift from the assembly form to our custom form. Another very important thing with this idea is that it makes simplifying it more manageable, because we will be simplifying it over and over again, and we can generalize each pattern to its basic form. As an example, let’s simplify that hard problem from before

(x - 0) - 0

Lets look at (x - 0) expression it can be turned into X, which we will be left with x - 0

Which we can turn into x. This approach is very powerful; we had almost infinite patterns. Now, we still have infinite patterns, but we, in theory, have a finite number of very common patterns that make it possible to simplify our code.

That is the mindset of making a decompiler: “Turn something into a readable form first, then simplify it, small things at a time.” Even if the initial pass of turning your assembly into code is sloppy, you still have all of the other passes to simplify everything out. After everything is simplified, you can transform that IR into C, C++, Rust, or really several high-level target languages, with the catch that you can represent it in that language.

Now this is a very simplified version of how decompilers work next chapter, we will talk about lifting.

Chapters

1. Utilizing Dynamic Binary Instrumentation for Lifting
2. Designing an Architecture-Agnostic Intermediate Language (IL)
3. Lifting Assembly to an Intermediate Language
4. Designing an Architecture-Agnostic IR
5. Lifting IL to IR
6. IR Semantics Edge Cases, Undefined Behavior, and Special Handling
7. Reconstructing Control Flow using Graph Theory, SSA, and Types
8. Designing Safe Optimization Passes
9. Coverage-Guided Fuzzing for Validation and Symbolic Execution
10. Dead Code Elimination and IR Canonicalization
11. Control Flow Recovery and Branch Simplification
12. Abstract Modeling: Pages, Regions, Self-Modifying Code, and Indirect Calls
13. Safe Page-Level Optimization
14. Modeling Inlined Functions as Virtual Function
15. Recovering Virtual Functions
16. Deobfuscation Mixed Boolean Arithmetic and Opaque Predicate Removal
17. Memory Inferencing Safely
18. Lowering IR to Readable and Executable Code

19. Practical Decompilation Results and Pipeline Evaluation

Next Chapter: Chapter 1 - Utilizing Dynamic Binary Instrumentation for Lifting