Welcome back to The Deep Dive. Today we've got
a stack of sources, articles, research papers,
archive notes, and we're going to pull out the
essentials for you. Our mission today is to explore
the influence of a man whose legacy is, well,
it's kind of invisible. And it's invisible precisely
because it's so fundamental to the structure
of modern computing. Right. We are talking about
Edsger W. Dykstra. The Dutch visionary, the mathematician,
the computer scientist. He was the architect
who demanded intellectual rigor and elegance
at a time when programming was seen as little
more than a messy craft. It's such an essential
deep dive because what the sources really show
is that Dijkstra didn't just develop a few algorithms.
He was trying to establish the entire intellectual
foundation for the profession. He was setting
the standard. He was setting the standard for
what it meant to be a respectable, you know,
a rigorous computer scientist. And our sources.
paint a portrait of a very demanding very uncompromising
mind. And he certainly had the credentials to
back up that demand for rigor. He was born in
Rotterdam in the Netherlands in 1930, studied
mathematics and theoretical physics at Leiden
University. His whole career arc was about moving
programming from this sort of experimental thing
into the realm of formal science. And that trajectory
was recognized really early. He received the
highest honor in the field, the ACM Turing Award,
way back in 1972. And that was specifically for
his contributions to developing structured programming
languages. But the proof that... you know that
you the listener are using his work every single
day that comes down to something like dexter's
algorithm the shortest path algorithm yes right
if you pull up a map on your phone or if a router
is deciding the fastest way to send a packet
of data across the internet you are leveraging
his solution from 1956. it is the definition
of foundational work it really is and his brilliance
lies in the fact that he was solving these um
These theoretical problems that define the constraints
of a whole new kind of machine. He was doing
this long before most people even knew what that
machine was truly capable of. He was pushing
for intellectual integrity before the field had
even figured out its own name. Okay, let's untack
that journey because the way he even got into
computing is, it's just remarkable. It's almost
an accident. It really is. The sources show he
was actually leaning toward a career in law.
Can you believe it? In law. Yeah. He had this
ambition to represent the Netherlands in the
United Nations, which, you know, it shows an
early interest in formal sisters, in structure,
in diplomacy. It's a kind of systems thinking,
but applied socially. But the focus shifted.
He studied math and physics, apparently, at his
parents' suggestion. And this was the early 1950s.
A time when electronic computers were these massive,
unreliable curiosities. They weren't seen as
the future of everything. Not yet. So what was
the turning point? The accidental shift, really.
His supervisor introduced him to a man named
Adrian van Wyngarden at the Mathematical Center
in Amsterdam. Van Wyngarden was looking for people
to operate these brand new electronic beasts,
and that meeting was pivotal. In March 1952,
he offered Dijkstra a job as the Netherlands'
first ever computer programmer. The very first.
What a title to hold in a field that doesn't
even exist yet. But this raises the core issue
that shaped his entire philosophy, right? Was
programmer a respectable job title? Exactly.
And this intellectual dilemma is just so powerfully
captured in his 1972 Turing Award lecture, the
one called The Humble Programmer. That's EWD
340 for anyone looking it up. That's the one.
It's incredibly revealing. See, Dyster was studying
theoretical physics at the same time he had this
early programming job. And he felt this deep
pull, this crisis of identity. He felt he had
to choose. Either he stops programming and becomes
a real, respectable theoretical physicist, or
he finishes his physics degree and becomes a
programmer. And what was the worry? What was
so bad about being a programmer? The worry was
standing empty -handed when someone asked about
his professional competence. He saw his colleagues
in hardware. You know, they could point to their
vacuum tubes and their relays and say, I know
everything about this physical machine. But for
the programmer, there was no established discipline,
no body of formal knowledge. He asked himself,
was programming just some esoteric craft, a bag
of tricks, or was it a true intellectual discipline?
That distinction craft versus discipline, that
was everything to him. It was. And Van Weingarten's
response to this young, conflicted scientist,
well, it became the mandate for generations of
software developers. What did he say? He listened
to all of Dykstra's concerns very patiently.
And then he just explained that automatic computers
were undeniably here to stay. And then he posed
the question. He asked, couldn't Dijkstra be
one of the person's call to make programming
a respectable discipline in the years to come?
Wow. So it wasn't a job offer. It was a challenge.
It was a challenge to define a new field's intellectual
mission. And that challenge clearly resonated.
Dijkstra finished his physics degree as fast
as he could, and he accepted the mission. He
did. And the anecdote that just perfectly captures
the infancy of the field and his role in it comes
from 1957. This is a great detail. It's fantastic.
When he married Maria de Betts, the local authorities
refused to list his profession as programmer
on the marriage certificate. Why? Because it
wasn't a recognized job title in the Netherlands
yet. The official document lists him instead
as a... theoretical physicist. That's incredible.
He literally helped invent the profession only
to have the civil bureaucracy tell him his job
doesn't exist. It's the perfect illustration
of the skepticism he was up against. And it just
reinforced his mission to establish programming
as this intellectually rigorous endeavor that
deserved respect. OK, let's move into the foundations.
This is where we see the actual engineering discipline
he created. We'll start with his early decade
at the Mathematisch Centrum in Amsterdam from
52 to 62. This was a period of really intense
intellectual growth for him, and it was all about
this disciplined interaction with the physical
limits of the hardware. His early collaboration
with the hardware builders, Bram Jan Lubstra
and Carl Scholten, it just laid the groundwork
for modern ideas of interface definition. How
so? What was so special about how they worked?
It was the order of operations. They established
a way of working that demanded abstract thinking
first. Okay, so what did that look like in practice?
Well, they agreed that before the hardware was
even physically built, they would define the
interface by writing the programming manual.
Writing the manual for a machine that doesn't
exist. Exactly. Dijkstra, the programmer, would
then write software, often just on paper. for
this non -existent machine. And while he was
doing that, the hardware engineers would focus
on building the machine to faithfully match the
specifications in the manual. That is profound.
It forces the programmer to think theoretically
about the machine's capacity instead of just
reacting to its flaws. Right. It elevates the
conceptual model, the documentation, above the
physical reality. The manual became the primary
contract. And what did that teach him? It established
two core lessons that drove the rest of his career.
First, the absolute importance of clear, unambiguous
documentation. And second, the realization that
program debugging can be largely avoided through
careful, mathematically sound design. He really
believed that, that you could avoid debugging.
He believed that the very need for extensive
debugging was a confession of intellectual failure.
And this commitment to early elegant design is
what led to the algorithm that really cemented
his early reputation, the shortest path problem.
He solved this in 1956. And initially it was
just for a small demonstration for the inauguration
of a computer called the ARMAC. The problem itself
is, you know, conceptually simple. Find the path
between two points in a network that minimizes
the cost or distance or time. It sounds simple,
but the elegance of his solution is what mattered.
It was published in 59. Tell us about its continuing
relevance. It is utterly essential. You cannot
think about modern connectivity without it. It's
the backbone of global navigation systems, obviously.
But more critically, it's used today in fundamental
network routing protocols like OSPF, that's Open
Shortest Path First, and ISIS. And these are
the protocols that determine how data travels
across the Internet. They're the rules of the
road. They determine how data travels efficiently
across massive networks. It's just a testament
to the power of getting the mathematical model
right early on. At the same time, while he was
developing these fundamental algorithms, he was
also shaping the future of programming languages
themselves. Yes, which leads us to his critical
work on LGOL60. An incredibly important step
forward for structured programming. It really
was. Working with Jobs Zonaville, they managed
a phenomenal feat of engineering. They developed
the first compiler for AlgaeL60 by August 1960.
And the quantitative angle here is key. They
beat every other major research group working
on the same problem. By more than a year. What
made AlgaeL60 such a breakthrough? It introduced
crucial features that forced greater discipline.
It formalized block structure, the ability to
group statements together with their own local
scope. And it introduced recursion, where a function
can call itself. These things drastically improve
the clarity and logical structure of the code,
making programs easier to reason about mathematically.
Which was always Dijkstra's goal. It was a language
designed by mathematicians for mathematical rigor.
Okay, so the next major phase, starting in 1962,
takes him to Eindhoven University of Technology.
He moves there as a professor in the math department.
Right, which in hindsight sounds a bit like an
ill -fitting shoe for a computer architect. It
does. And it was a challenging environment because
computer science wasn't really a recognized academic
discipline yet. The math department culture was
typically one of solitary research. But Dykstra
tried a highly unusual approach. He tried to
build a collaborative group that was focused
on large practical systems problems. And that
collaborative effort culminated in what many
consider his masterpiece in systems architecture,
the multi -programming system. Named after the
Technisch -Hoga school, Eindhoven. Now, the system
wasn't widely commercialized, but its intellectual
influence on later operating systems. Including
Unix, right? Including the design of Unix, yes.
The influence was enormous. Its core innovation
was structural clarity. Dijkstra designed the
system as a rigorous hierarchy of layers. Let's
elaborate on those layers. The concept is still
used today in things like network architecture.
How did that layering promote correctness? The
layered approach meant that each layer only relied
on the services provided by the layers beneath
it. And it was completely unaware of the layers
above it. So it simplified the reasoning. Dramatically.
Yeah. The lowest layer, Layer 0, handled the
hardware interrupt processing and processor allocation,
the most immediate volatile tasks. Layer 1 managed
memory and software -based paged virtual memory,
a concept he pioneered. So if you were a programmer
working on, say, Layer 3, which might handle
I .O. buffering, you didn't have to worry about
the complexities of physical memory addresses.
Precisely. That was all handled by Layer 1. You
only had to trust the interface that Layer 2
provided you. This isolation meant that if a
flaw was found, you knew exactly which layer
to debug. And you could prove the correctness
of each layer independently, starting from the
bottom. This commitment to intellectual manageability
was radical. If the system was built correctly
from the bottom up, it had to be correct overall.
Beyond structure, Dijkstra was also crucial for
tackling the immense complexity of concurrency
when multiple processes try to run at the same
time. Yes. His work here is required reading
for anyone studying system reliability. Let's
look at the banker's algorithm, for instance.
This is a mechanism used for resource allocation
to prevent system deadlock. Okay, what exactly
is deadlock and how does the banker's algorithm
stop it? Deadlock is that state where two or
more processes are just perpetually waiting for
resources that the others hold. Imagine process
A needs resource X and process B needs resource
Y. But A is holding Y and B is holding X. Neither
can proceed. They're stuck. And the banker's
algorithm prevents this by modeling the operating
system as a bank. Right. And resources as cash.
Before granting any resource request alone, the
algorithm simulates the future. It sees if granting
the request would leave the system in an unsafe
state. An unsafe state being one where deadlock
is possible later on. Exactly. If the simulation
shows the system can run to completion, even
if all remaining demands are requested, the request
is granted. If not, the process has to wait.
It uses foresight to mathematically guarantee
the system won't hang. It's intellectual control
over chaos. And the most fundamental concept
he introduced for coordination is the semaphore.
The semaphore is Dijkstra's most direct contribution
to solving what's called the critical section
problem. In multi -threaded apps, you have shared
resources, or critical sections, which only one
process should be accessing at a time, like updating
a shared variable. And if two try to write at
the same time, you get a race condition and corrupt
data. Correct. The semaphore is the traffic cop.
It uses two atomic operations, P and V. A process
executes P to request entry. If the semaphore
count is greater than zero, it goes in and the
count decreases. If it's zero, the process waits.
When it exits, it executes v, which increments
the count, potentially letting a waiting process
go. It's a beautifully simple, elegant, and mathematically
provable solution. And finally, a concept that
feels like it's straight out of advanced systems
theory, self -stabilization. This is truly fascinating,
especially for massive distributed systems where
errors are just inevitable. Self -stabilization
is a method for ensuring fault tolerance that's
fundamentally different from traditional recovery.
Traditional methods assume you start in a correct
state and you try to maintain it. But self -stabilization
doesn't assume a correct start. No. Dijkstra
envisioned a system where, regardless of the
initial state, even a completely corrupt, chaotic,
arbitrary state, the system will eventually and
automatically converge back to a legal correct
state. All on its own. Without any external intervention.
Without any external intervention or global reset.
The elegance is that it uses only local information.
Each individual component follows simple rules,
and the emergent global behavior is system -wide
stability. It's like iron filings aligning themselves
in a magnetic field. That's a wonderful analogy.
And this profound rigor was acknowledged with
the ACM -PODC Influential Paper Award shortly
before his death. A well -deserved honor that
continues to live on, that award was later renamed
the Dykstra Prize. Yes, in 2003. ensuring his
name is forever linked to creating order out
of chaos in computing. We're moving now into
how he formalized all this rigor. This is section
three. The pen and the platform. This period
begins around 1973 with his highly unique job
at Burroughs Corporation. This was a pivotal
time for him, personally and philosophically.
In 73, he joined Burroughs, a major player in
computing, but he wasn't a conventional employee.
He was the company's sole research fellow. And
that position came with highly unusual working
conditions, didn't it? It let him keep that rigorous,
contemplative lifestyle he preferred. Exactly.
His duties required him to travel occasionally.
But his primary job was carrying on his own research,
which he did almost entirely from his home study
in Wienan. For a major corporation to hire a
top researcher to work remotely from a small
office in the Netherlands, that says a lot about
his stature. It does. And that arrangement allowed
him to reach his most prolific output. He reduced
his academic appointment at Eindhoven to just
one day a week. Tuesday. Tuesday. And that Tuesday
became legendary. It was the day of the Tuesday
afternoon club, where he'd meet with a select
group. They didn't just discuss scientific content.
They focused intensely on notation, on organization,
on the intellectual purity of the presentation.
It was a formal exercise in precision. And this
remote, focused environment generated the famous
EWD series. He wrote nearly 500 documents in
this period alone, out of over 1 ,300 in his
whole career. And these weren't traditional published
papers. They were handwritten technical reports,
EWDs, numbered consecutively. Rod. deep computer
science theory, math, trip reports, philosophical
letters, speeches. And the means of production
for these foundational documents is as famous
as the content itself. He had a strong bias against
technology for the act of composition. That's
right. Almost all EWDs after 1972 were produced
without a computer. He famously preferred his
typewriter and later a Montblanc Meisterstück
fountain pen. So a man who designed the architecture
of modern software refused to use the tools of
his trade to write about it. That's the classic
Dykstra paradox. It wasn't just stubbornness,
though. It was rooted in his core intellectual
philosophy, which we can call the anti -draft
mentality. An anti -draft mentality? What does
that even mean? It means he believed that if
your thought process was rigorous enough, if
you would truly solve the problem and articulated
the solution mentally, you should be able to
produce the final correct document in a single
pass. No rough draft. No rough drafts. No significant
editing. He recalled that as a physics student,
he'd solve complex homework problems entirely
in his head while walking through Leighton. The
writing was just the transcription of a perfectly
formed idea. So the lack of editing tools was
a deliberate constraint. Yes, to force intellectual
rigor before putting pen to paper. And this fierce
self -reliance extended even to his published
books. In a discipline of programming, he deliberately
omitted bibliographies. Right. And he offered
neither explanation nor apology. It was a conscious
choice to preserve his intellectual independence.
He wanted his work to stand on its own, based
purely on the elegance of his arguments. Now
we come to the writings that didn't just propose
a philosophy but actively reformed the industry.
Let's talk about the one that caused the structured
programming revolution. The famous 1968 letter
to the journal Communications of the ACM, titled
Go -To Statement Considered Harmful. Just a short
piece, but it triggered a massive industry debate.
A debate that lasted for years. Yeah, because
the GOTO statement, the instruction that lets
program flow jump arbitrarily to any label in
the code, was the norm at the time. So why was
he so vehemently opposed to it? It went back
to his core belief that programming should be
rooted in mathematics. When you use GOTO, you
create programs whose flow is incredibly difficult
to trace and reason about. You lose what's called
referential transparency. So it's not about style.
It's about making the code mathematically tractable.
Precisely. He argued that using GOTO actively
destroyed the programmer's ability to reason
about the dynamic evolution of the system. It
fostered intellectual chaos. And the debate ultimately
cemented the necessity of structured programming,
which is still the paradigm today. That's the
architecture he built. But his fiercest criticism
was reserved for something that has grown exponentially
since he wrote about it, software engineering.
This is where the academic and commercial worlds
collide dramatically. Dykstra was a vocal opponent
of including software engineering, or SE, as
a core discipline in academic computer science
departments. He infamously wrote that it should
be known as the doomed discipline. That's not
a critique. It's a condemnation. He believed
it was doomed because its goal was fundamentally
self -contradictory. He argued that the charter
of SCE had implicitly accepted a diminished standard.
Instead of focusing on how to write perfect programs,
it focused on how to manage the production of
inevitably flawed programs. He called it teaching
how to program if you cannot. Correct. For Dykstra,
the immense scale of software complexity was
not an excuse for error. It was precisely why
the demand for mathematical rigor must be higher.
If you accept imperfection, you've surrendered
the possibility of true elegance. So his ultimate
focus was never the program itself, but the intellectual
process. What was the true goal of computing
science then? He defined it beautifully in The
Humble Programmer. We must not forget that it
is not our business to make programs. It is our
business to design classes of computations that
will display a desired behavior. The focus had
to be on conceptual design. on proof, on guaranteed
behavior. That uncompromising commitment to elegance
brings us to section four, the unconventional
teacher and the witty essayist. Dijkstra was,
by all accounts, a singular character. He was
known for being witty and eloquent, often painfully
so. And the sources confirm he was also capable
of being brutally direct, even abrupt, with colleagues
whose work he found lacking in rigor. And he
left us a treasure trove of... pithy quotes that
cut straight to the heart of academic debates.
My favorite is his take on artificial intelligence.
Ah, yes. The question of whether machines can
think is about as relevant as the question of
whether submarines can swim. It's perfect. It
captures his demand for clear operational definition.
Submarines navigate underwater. They don't need
to emulate fish. Computers compute. They don't
need to emulate the human brain. His advice to
young researchers was just as direct. When asked
how to pick a topic, he said, do only what only
you can do. It's a call to intellectual audacity.
It is. And on the other end, he directed harsh
criticism at pedagogical choices. He felt compromised
rigor, most notably the programming language.
He hated basic. He was strongly opposed to teaching
it. He viewed it as fundamentally damaging to
the development of rigorous thought in students.
He thought it encouraged sloppy habits, relied
on unstructured jumps. It instilled a poor, undisciplined
approach right from the start. So whether it
was a research topic or a first programming language,
he applied the same uncompromising demand for
excellence, and he treated teaching itself as
a serious research endeavor. He did. His lecturing
style was idiosyncratic. Students noted his long,
extended pauses. And these pauses weren't just
because English was his second language. They
were tools for deep, on -the -spot thinking.
He would formulate complex, logical arguments
in real time. That sounds both intimidating and
incredibly engaging. You knew you were watching
a mind at work. But he also had a very personal
touch. He did. We have the wonderful detail that
he would take a photo of each student at the
beginning of the semester just to memorize their
names. In the classroom, he never followed a
textbook. He'd write proofs in chalk, live. He'd
challenge students, encouraging them to suggest
ideas, and then explore or refuse those ideas
instantly based on their formal rigor. It was
a true intellectual crucible. And his final assessment
method was legendary for its intensity. Oh, it
was extraordinarily demanding. His final exams
were oral. They spanned an entire week. Each
student was examined individually in his office
or home for several hours. Not a multiple choice
test. Not at all. It was a deep, sustained assessment
of their ability to think formally under pressure.
He even used similar methods when hiring. The
story about the job candidate in Austin. Yes,
Vladimir Lifshitz. When he came for an interview
in 1990, Dykstra famously ignored the conventional
process. Instead, he gave the candidate a complex
puzzle to solve on the spot. Lifshitz solved
it and was hired. He was testing core intellectual
capacity, not a resume. Exactly. And beyond his
technical papers, we see this creative side emerge
in his essays. These witty parables that expose
the absurdity of commercializing intellectual
rigor. The parables of mathematics, ink. These
are delightful. He created a fictional company
that commercialized the production of mathematical
theorems, just like modern corporations commercialize
software. It was a perfect satire. Highlighting
the conflict between the integrity of knowledge
and the demands of profit. Absolutely. Take the
example of the Ryman hypothesis proof. Mathematics
Inc. successfully produces the proof a massive
achievement. Huge. But then they run into a commercial
problem. How do they collect royalties? The solution
of the commercial entity. They keep the proof
a trade secret. Which completely undermines the
scientific purpose of the achievement. Exactly.
Knowledge becomes proprietary. Another target
was the pressure of deadlines. Many of mathematics,
Inc.'s proofs, were rushed out the door. The
consequence? Much of the company's effort had
to be spent on maintenance, fixing the logical
gaps in theorems published too quickly. Sound
familiar? It's the modern software maintenance
crisis perfectly described, and their ultimate
success was standardization. Yes. Their most
successful effort was replacing the more than
100 incompatible existing proofs for Pythagoras'
theorem with one single standard proof. This
was his way of celebrating elegance. He described
the company as the most exciting and most miserable
business ever conceived. Let's turn to his final
years, Section V legacy, honors, and final retreat.
After Burroughs, Dykstra spent his final working
years in American academia. From 1984 to 1999,
he was at the University of Texas at Austin,
where he held the Schlumberger Centennial Chair
in the Computer Science Department. And what's
fascinating is the extreme contrast between his
chosen field. the cutting edge of global tech,
and his personal lifestyle. He maintained an
incredibly modest, even Spartan lifestyle. He
was famously adverse to consumer electronics.
No television, no VCR, no mobile phone. His life
revolved around reading, thinking, and his deep
appreciation for classical music. Mozart was
his favorite, and he played the piano. He worked
in Austin until his retirement in 99, and he
had a very specific wish that dictated his last
move. He was a deeply Dutch man. He stated he
wanted to retire in Austin, but he wanted to
die in the Netherlands. Shortly after retiring,
he returned to his original house in Noonan.
He passed away there on August 6, 2002, after
a long struggle with cancer. And while the Turing
Award in 72 is the monumental capstone, his influence
is consistently recognized in posthumous honors,
showing that his ideas are still vital. The recognition
is deep and institutional. We mentioned his work
on self -stabilization led to the ACMPODC award
being renamed the Dijkstra Prize in 2003. This
is a perpetual honor that ensures his name is
associated with the highest standard of fault
tolerance and concurrent systems design. And
his name is used to promote academic excellence
in the next generation. Yes. Institutions continue
to honor him. There's the Dykstra Award for Outstanding
Academic Achievement at Loyola University Chicago.
And at UT Austin, they established the Edsger
W. Dykstra Memorial Lecture Series. That continuity
is largely possible because of his dedication
to writing. His influence wasn't just through
his students, but through his immense body of
work. His output is staggering. Over 1 ,300 papers,
essays, and reports. And these writings ensure
his ideas continue to spread. The full EWD archive
is now online. through the University of Texas.
He was also a distinguished fellow of the British
Computer Society, a member of the Royal Netherlands
Academy of Arts and Sciences, and a foreign honorary
member of the American Academy of Arts and Sciences.
His stature was global. His impact spans every
layer of computing, from the shortest path calculation
on your phone to the complex coordination mechanisms
inside a server farm, and perhaps most importantly...
the philosophy behind how every programmer should
approach their craft. If we summarize Dijkstra's
unique contribution, it's that uncompromising
shift he enacted. He moved programming from an
unpredictable, error -prone craft into a scientific
discipline rooted in mathematical rigor and elegance.
His legacy taught us that elegance and brevity
aren't just aesthetic choices. They are active
guarantees of correctness and manageability.
He insisted that if a system is simple enough
to be proven right, it is right. And he summarized
that profound demand for rigor, the concise nature
of superior intellectual expression, with one
powerful equation. He said, a picture may be
worth a thousand words, a formula is worth a
thousand pictures. That perfectly encapsulates
his worldview. It does. He believed that the
ultimate power of computer science lay in its
ability to be formalized, not simply visualized
or described. That is a staggering standard to
set for a global industry. So what does this
all mean for you, the listener, today? Consider
this final provocative thought based on Dijkstra's
foundational work. Dijkstra so vehemently criticized
software engineering, believing its goal, how
to manage the creation of imperfect programs,
was fundamentally self -contradictory. Yet decades
after he accepted the mission to make programming
a respectable discipline, we see the continued
exponential growth of global software output.
And this output is often rushed out the door
under immense commercial pressure, inevitably
requiring constant maintenance, much like his
fictional mathematics, Inc. So the question is
this. Welcome to the debate. Our focus today
is the monumental and I think, often paradoxical
legacy of Edsger W. Dijkstra, the Dutch computer
scientist, Turing Award laureate, and, well,
the source of concepts that run our world, like
the shortest path algorithm and the semaphore.
And his technical genius is just, it's undeniable.
But it was so deeply tied to this aggressive,
almost ascetic philosophy toward computing, a
philosophy that really became central to his
whole professional identity. And of course, his
critiques of the entire field. Right. And that's
the tension we're diving into. The relationship
between Dijkstra's foundational genius and his
extreme, uncompromising intellectual discipline.
So the core question is this. Was Dijkstra's
famous rigor, you know, the rigor exemplified
by his work habits and his philosophical challenges,
was it an essential, inseparable component needed
to elevate computing from a chaotic craft? Or
conversely, was his personal methodology just
an idiosyncratic and ultimately unsustainable
ideal, one that created an unnecessary barrier
and actually hindered the field's broader professionalization
and, you know, scalable growth? I hold that latter
position. I'm going to argue his personal rigor
was exceptional, for sure, but totally inaccessible,
and it set standards that were obstructive to
modern collaborative practice. And I will argue
that his uncompromising stand was the vital corrective
the field absolutely needed during the early
software crisis. His insistence on that rigor
was necessary to establish the robust, mathematically
grounded foundation that, frankly, allows modern,
reliable, large -scale computing systems to even
exist. You know, Dijkstra's most profound contribution
wasn't just a single algorithm. It was a complete
paradigm shift. He was forcing the community
to recognize programming as a rigorous branch
of applied mathematics where correctness is paramount
and has to be designed in, not just hunted down
with debugging tools. I mean, this insight really
emerged from the sheer terror of early computer
failure. And that context is absolutely critical.
In the early days, huge projects were just collapsing
under their own weight. This uncontrolled complexity
led to what we now call the software crisis.
Exactly. When Dijkstra realized he needed to,
you know, define programming as a profession,
he famously asked, where was the sound body of
knowledge that could support it as an intellectually
respectable discipline? He saw the failure rate
of the industry and just concluded the fundamental
approach was entirely wrong. We were acting like
artisans, not like scientists. His solution was
this disciplined approach he learned at the Mathematisch
Zentrum. He advocated for designing the interface
first, the formal logic, and writing the software
for a conceptual machine. He realized that if
you approach programming with mathematical certainty,
debugging could, in his words, largely avoided
through careful design. This insistence on formal
methods, which of course led to the Turing Award
for Structured Programming, was the necessary
antidote to all that chaos. It's what gave us
the elegance and predictability we need for reliability.
I absolutely agree on the foundational impact
of structured programming and concepts like the
semaphore, which managed concurrency beautifully.
That's all, you know, bedrock stuff. But the
way he arrived at those foundational concepts,
his methods, they were deeply idiosyncratic and,
I would argue, largely untransferable. I can
see why you'd think that. But let me offer a
different perspective on his method. That asceticism
was the very generator of the genius. Well, let's
examine that generator. I mean, consider his
famous professional methodology. For his core
work, he deliberately avoided what was, even
then, modern technology. He preferred a Montblanc
fountain pen, perfecting his thoughts entirely
on paper. He often refused to write an article
with quote, rough drafts, rewriting, or any significant
editing. He would work the entire solution out
in his head first, sometimes just walking the
streets of Leiden, solving these huge problems
internally before he ever committed them to paper.
And that mental rigor is precisely why his work
is so elegant and free of unnecessary complexity.
The friction of the fountain pen and the typewriter,
the sheer difficulty of editing, it forced clarity
and precision before execution. Perhaps, but
that is the mark of a master craftsman, isolating
himself to produce a singular masterpiece. It's
not a model for scalable, collaborative engineering.
And what's more, the dissemination of his ideas,
while it suffered from this isolation. His critical
essays and technical reports, the famous EWD
series which totaled over 1 ,300 documents, they
were often circulated for private circulation
within a select group. He was acting like an
intellectual high priest sharing secrets with
his chosen few, rather than building accessible,
shared public knowledge. And this really brings
us to the core philosophical tension. I acknowledge
he was pushing for the highest standards, but
I think that view overlooks the practical needs
of a maturing field. Dijkstra viewed software
engineering with absolute scorn. I mean, he famously
called it the doomed discipline, asserting its
charter was, quote, how to program if you cannot.
Wasn't this uncompromising hostility just counterproductive
to developing rigorous methodologies for the
complex real world systems we actually have to
build? That's a compelling point about his tone
for sure. But I would argue his extreme critique
was necessary to prevent the dilution of scientific
standards at a really critical moment in the
field's institutionalization. He saw software
engineering as an attempt to manage complexity
through, you know, organizational charts and
project schedules, relying on testing and management
rather than eliminating complexity through elegant,
provable design. But the reality of building
a massive banking system or air traffic control
system is that you cannot eliminate all complexity
mathematically from the outset. It's impossible.
You require structured managerial practices.
You need testing protocols and methodologies
for collaboration. Dykstra's position suggested
that any programmer who needed those tools was
inherently weak. It felt like an intellectual
barrier designed to exclude rather than to elevate
the average standard. I'm just not convinced
by that line of reasoning because... His rejection
of it was a defense of mathematical honesty.
If a system is so complex that you can't formally
prove its correctness, then how can you possibly
claim it's reliable? He recognized that complexity
is the enemy of reliability. When he spoke of
a doomed discipline, he was challenging the field
to maintain the highest standard, asserting that
programming, at its core, is a discipline of...
Of a mathematical nature. Yes, I know, but that's
my entire point. Right. That view, while noble,
sets an impossible bar for the profession as
a whole. And this deep commitment to rigor, it
translated directly into foundational technical
achievement. I mean, his method ensured an elegance
and economy in his work. Consider the TMD multi
-programming system. That reliance on precision
forced by his manual approach resulted in its
clean, layered structure. So why should we discount
this method? when it produced an architectural
design that influenced operating system development
for decades to come. Okay, yes, it was an elegant
piece of architecture, certainly a monument to
his individual genius, but I come at it from
a different way. That masterpiece was created
largely by a single mind with a fountain pen.
How does that isolated process, relying on one
person's immense capacity for internal abstraction,
how does that inform a team of 50 working on
a modern... distributed code base that has to
be maintained and iterated on by hundreds of
different engineers over two decades. You see,
the methods that created this system are not
the methods that can sustain the profession.
His EWDs, those 1 ,300 technical reports and
essays, while precise, they represented a non
-collaborative, non -digital approach to documentation.
In a high -tech field that demands shared, accessible,
and iterative resources, that form of knowledge
dissemination is just fundamentally restrictive.
It's a genius demonstrating intellectual self
-reliance, not building a scalable knowledge
infrastructure. But there's a real value in the
EWDs precisely because they existed outside the
formal, slow publication process. They were raw
shark philosophical arguments and explorations
often circulated purely to provoke thought among
his peers. He used them to explore ideas that
would have been completely sanitized by standard
academic publishing. That freedom, born from
his personal dedication, allowed him to push
boundaries without compromise. but that freedom
came at the cost of accessibility. The entire
framework of modern computer science, the ability
to train millions of students and collaborate
globally, it relies on standardization and shared
reference points. Dijkstra's whole approach resists
standardization. And this intellectual isolation,
it's something I think he even recognized maybe
a bit wryly in his own fictional writings. I'm
talking about his amusing essay about the fictional
company Mathematics Incorporated. He writes that
this company, which is dedicated to abstract
rigor, spent a ton of effort on maintenance and
had serious difficulty collecting royalties for
its proofs, even a proof of the Riemann hypothesis.
It subtly acknowledges the tremendous friction
between pure abstract rigor and the demands of
real -world commercial execution. The world doesn't
pay for elegant proofs. It pays for functional,
maintainable systems, as messy as they may be.
That's a great example of his dry academic wit,
I'll grant you that. But let's consider how he
implemented his rigor. In the one domain where
he had total control, education. And that's where
the idiosyncratic nature becomes the clearest.
Let's just examine his teaching style. While
he was incredibly dedicated, he studied every
single student's solution. He even took photos
to memorize their names. It was highly, highly
unscalable. He conducted his final exams orally
over an entire week, lasting several hours for
each student. Hmm. I'm just not convinced by
that because his goal was never the mass production
of average practitioners. His goal was the rigorous
training of computer scientists who understood
the mathematical underpinnings. He sought teaching
as a, quote, serious research endeavor. In his
Austin courses, he was interested in the presentation
of mathematical proofs, not just teaching coding
as a tradecraft. His essay on the cruelty of
really teaching computer science lays out the
severity of his standards perfectly. The cruelty
he's referring to is the intellectual rigor he
demanded, the refusal to accept any hand -waving
or intuition where formal logic was required.
He just wouldn't explore ideas that violated
his fundamental formal tenets. The practical
consequence of that cruelty He was safeguarding
the scientific identity of the profession. He
believed that if you treated programming merely
as a vocational trade, or if you allowed students
to approach it without intellectual honesty about
complexity, So to summarize my position, Dijkstra's
deep, often uncompromising commitment to formalism,
his belief that a formula is worth a thousand
pictures, was the absolutely vital force required
to establish computer science as a true scientific
discipline. His ascetic refusal to compromise
on intellectual precision, even when it meant
eschewing popular tools or scalable practices,
provided the robust, elegant, and mathematically
grounded foundation upon which all reliable,
complex, modern systems are built. I think without
his rigor, we would still be trapped in the chaos
of constant debugging. And to summarize mine,
while Dijkstra's technical output, like the shortest
path algorithm and semaphores, is indelible and,
yes, essential, his insistence on a singular,
highly restrictive personal methodology is ultimately
a non -replicable path to excellence. His personal
rigor yielded brilliance, absolutely, but the
necessary growth and future stability of computing
relies on scalable, collaborative engineering
methods, the very methodologies he dismissed
as the miserable and doomed discipline. We have
to appreciate the essential lasting results of
his genius without requiring the entire field
to adopt his idiosyncratic high barrier personal
methodology, which prioritized individual brilliance
over scalable collaboration. Well, this discussion
really illuminates that the foundational age
of computing was shaped not just by clever inventions,
but by a passionate, almost brutal philosophical
disagreement over what programming should be.
The tensions between mathematical certainty and
practical engineering, between the singular genius
and the collaborative team, they continue to
define how the field operates today. There is
certainly more to explore in how these original
high standards influence modern challenges like
verification and systems architecture.