Abstractions are essential in order to build complex systems and keep complexity under control. Especially in software development we rely on many abstractions to make our life easier. Although good abstractions do not “leak”, it’s always helpful to understand the background and the details behind them.

The following list (in chronological order) of classic computer science papers will give you insights of inventions of the last decades which are considered nowadays common sense. But back then, even the most basic concepts needed to be invented or discovered. I find it fascinating how much you can learn from the discovery of such breakthroughs and I hope you can learn from them as much as I did. Further it is quite satisfactory when one is able to connect the dots from the past to the present. Knowing the history prevent you from reinventing the wheel and from making same failures over and over again:

Those that fail to learn from history are doomed to repeat it.

by Winston Churchill

Recursive Functions of Symbolic Expressions and Their Computations by Machine, Part I

by John McCarthy 1960

Link to paper

This paper is special in it’s own ways and is widely considered as a seminal work of computer science.

John McCarthy defines the complete LISP programming language in roughly 30 pages. The design of Lisp with S-expressions is ingenious because it’s so simple. 1960 most of the programming language concepts, which we consider basic today, needed to be defined. McCarthy does this on the go. He introduces conditional expressions like if-then-else. Those are needed for recursive functions in order to formulate the recursion termination condition. Casually he also introduces the first garbage-collection algorithm with a free-storage-list. All in one paper, groundbreaking!

Unfortunately the paper is hard to “digest” due to its age. A contemporary and more comprehensible essay was written by Paul Graham, The Roots of Lisp. Graham picks up McCarthy’s paper and brings it in a more readable form.

On the Criteria To Be Used in Decomposing Systems into Modules

by David Parnas 1972

Link to paper

Today, we know modularization is a keystone for building large software systems. Independent and autonomous teams are critical. To achieve autonomy and smooth collaboration, modules must hide their internal implementation, i.e. they should only expose the least information which is absolutely necessary. The concept advocated by Parnas is information hiding. It is crucial to encapsulate the module’s internals, so consumers do not have to deal with the module’s internal complexity. Parnas summarizes:

The benefits expected of modular programming are: (1) managerial-development time should be shortened because separate groups would work on each module with little need for communication: (2) product flexibility - it should be possible to make drastic changes to one module without a need to change others; (3) comprehensibility - it should be possible to study the system one module at a time. The whole system can therefore be better designed because it is better understood.

The principle of information hiding enables us to replace an existing implementation but to keep the exposed interface. Hence existing consumers remain untouched. Further modules can be reused and provide their functionality safely. Basically Parnas paved the way for APIs which are one of the most influential and powerful concepts of software engineering. APIs act as contracts between consumer and producer. This is true in the small scope for software libraries but also in a large scope for REST-APIs, gRPC and the like. Modularization is a precondition for Microservices whose functionality is hidden between a well-defined and documented API. Even the Unix Philosophy is a “just” a description for a good module:

  • Do one thing well
  • Write programs that work together
  • Write programs to handle text streams, because that is a universal interface.

Historical fact: In the seventies information hiding was controversial. Even the most renowned IT people like Fred Brooks who managed the development of IBM’s System/360 with thousands of people and a budget of 5 billion dollars did not believe in it. Years later Brooks admitted (after bitter learnings):

David Parnas Was Right, and I Was Wrong About Information Hiding.

The Mythical Man-Month: Essays on Software Engineering

by Fred Brooks 1975

Link to book

Fred Brooks “Essays on Software Engineering” are from the seventies but many of his insights still hold up today. 50 years are an eternity in the IT field and it speaks for the quality of this seminal book.

In his essay The Mythical Man-Month, he directly addresses software project management fallacies and bad estimations. Developers are not line workers but creative problem solvers - increasing their numbers will not positively impact the project’s progress.

Adding manpower to a late software project makes it later.

Nine women can’t make a baby in one month

Many other terms are coined in his essays. He muses that there is No Silver Bullet, i.e. no new technology or process that will improve productivity by an order of magnitude. He also addresses the tendency towards over-engineering in the Second System effect and warns about its consequences.

The second system is most dangerous system a man ever designs … The general tendency is to over-design the second system, using all ideas and frills that were cautiously sidetracked on the first one.

Further, he advocates for small, independent teams. The surgical team, is a team with 5-10 people and cross-functional skills. Sounds familiar Agile community?

Time, Clocks, and the Ordering of Events in a Distributed System

by Leslie Lamport 1978

Link to paper

The seminal paper about logical clocks or Lamport clocks. Vector clocks, a descendent of logical clocks, are one of the main building blocks of today’s distributed systems. They provide means for event ordering and synchronization which are prerequisites for modern NoSQL databases like Amazon DynamoDB. You can find a modern treatment about the topic from Martin Fowler.

The Emperor’s Old Clothes

by C.A.R Hoare 1980

Link to paper

In Hoare’s Turing lecture, he shares his experiences of designing and implementing programming languages. He muses about his first Algol 60 compiler which was a great success. But his second project failed miserably (maybe because of the second system effect?). It was never delivered, even after years of delay. Failure was caused by well-known product management issues: “lack of software knowledge outside of the programming group, interference from higher managers who imposed decisions,… overoptimism in the face of pressure from customers and the Sales Department”. Eventually the project was reestablished and saved by implementing agile principles like early customer feedback and incremental builds - in the sixties 😂 :

We assigned to each group of customers a small team of programmers and told the team leader to visit the customers and find out what they wanted; to select the easiest request to fulfil…

At last, Hoare speaks about his frustrating experience with programming languages committees and the never ending story of feature bloat and negligence of simplicity which leads us to his most famous quote:

I conclude that there are two ways of constructing a software design: One way is to make it so simple that there are obviously no deficiencies and the other way is to make it so complicated that there are no obvious deficiencies.

I find it fascinating that his insights about building compilers are not only apparent today but also apply to software product development in general.

Reflections on Trusting Trust

by Ken Thomson 1984

Link to paper

In his Turing Lecture Ken Thomson talks about trust:

You can’t trust code that you did not totally create yourself. (Especially code from companies that employ people like me (Ken Thomson).

You can’t trust code, this applies especially to software libraries and tools like compilers. In three stages he describes how to inject a Trojan Horse into a compiler without leaving any traces in the source code. This is possible due to re-compiling the compiler and removing the offensive code but the binary is still infected and will inject the offensive code for new compilations. It is hard to grasp but once you have it, it is mind-bending.

Casually, Ken shows a beautiful Quine, a program that prints its own source code. Have you ever written one? Try it out without looking to solutions - it’s a enlightening experience.

A Note on Distributed Computing

by Jim Waldo, Geoff Wyant, Ann Wollrath, Sam Kendall 1994

Link to paper

Abstractions are not for free, often they are leaky, inappropriate or just do more harm than good. This paper gives great insights why you should not treat distributed computing as local computing. Hiding distributed computing under local interfaces is a bad idea. Many technologies failed, trying exactly that - remember SOAP Web Services, Corba, Java EJBs and Java RMI.

Conclusion: one cannot hide the inherent issues of distributed systems, namely latency, concurrency, partial failure etc. behind an abstraction. Developers must always have those in mind and use appropriate techniques in order to build robust and resilient systems. It’s good to see that old fashioned technologies like Corba or Java RMI are fading away and that REST and gRPC via HTTP gained ascendancy.

A Plea for Lean Software

by Niklaus Wirth 1995

Link to paper

Wirth elaborates about embracing simplicity and fighting complexity, both traits often forgotten by today’s developers and customers. He makes a clear differentiation between inherent complexity and self-inflicted complexity. The later is the main reason for bulky software.

His insights about iterative software development, modularization and the decomposition of complex systems are delightful. Especially because those insights transition so well into the modern world with microservices.

He proves his points with the Oberon OS, a complete system written by him and his colleague in less then three years. Compare this to IBM OS/360, a project with five thousand man-years budget but infected with self-inflicted complexity and feature bloat. Both projects had a “similar” scope, namely an OS with additional tools like compiler, editor etc.

It is one of the best paper’s ever written and makes you a better programmer, simply because it changes your way of approaching big software projects and makes you honor simplicity more than ever.

Wirth’s paper is so full of gems, a selection of quotes (all before the agile revolution):

Truly good solutions emerge, after iterative improvements or after redesigns that explicit new insights, and the most rewarding iterations are those that result in programming simplifications.

The belief that complex systems require armies of designers and programmers is wrong. A system that is not understood in its entirety, or at least to a significant degree of detail by a single individual, should probably not be built.

Communication problems grow as the size of the design team grows. Whether they are obvious or not, when communication problems predominate, the team and the project are both in deep trouble.

To gain experience, there is no substitute for one’s own programming effort.

Introduction to Functional Programming

by Richard Bird, Philip Wadler 1998

Link to book

Alongside Fred Brooks Mythical Man-Month, this is the second book on the list and it is the best introduction to functional programming, period. In a way, it complements SICP, another classic and the best introduction to programming in general.

The book touches functional core concepts like immutable and lazy data structures, pure functions, function composition and high-order functions like map, filter, fold. After reading the book, you are well prepared for solving real world problems in a functional way. With these new tools in your toolbox, you will be better programmer and see the world differently. For example, avoiding state and side-effects, will make your code much more readable, more composable, better testable and easier maintainable.

Out Of The Tar Pit

by Ben Moseley, Peter Marks 2006

Link to paper

This paper is a great elaboration about complexity, its causes and how to manage it.

Like Wirth, the authors distinguish between two types of complexity: essential complexity and accidental complexity. The latter is the main reason why systems are much more complex than necessary. Further they expose state as another major cause for complexity, but also code volume and the negligence of simplicity are main drivers.

Rings a bell? Today avoiding state is tantamount in Computer Science to good, simple and scalable system design. Thinking of functional programming, stateless microservices and HTTP as a stateless protocol.

On Designing and Deploying Internet-Scale Services

by James Hamilton 2007

Link to paper

Today, distributed systems are everywhere. With the raise of ever-growing systems and new tools like Kubernetes, Containers and Microservices, new best practices were needed. This paper is whirlwind tour about best practices to build robust distributed systems in an operating-friendly way.

The paper describes keystones like redundancy, fault tolerance, build for failure, avoid single point of failures, geo-distribution, firedrills, fail fast and many more. Without knowing it, he basically describes the contemporary DevOps mindset (and his observations gives us the reason why it makes sense):

The trend we’ve seen when looking across many services is that low-cost administration correlates highly with how closely the development, test and operations teams work together.

If development is frequently called in the middle of the night, automation is the likely outcome. If operations is frequently called, the usual reaction is to grow the operations team.

I like his tendency to “testing in production” with permanent firedrills and his meticulous attitude leaving nothing to chance:

The general rule is that nothing works if it isn’t tested frequently.

It is a great read, especially, if you consider to build “internet-scale” systems. You find most of the advice in other distributed system books but the paper provides them in a condensed and terse way.


Interested in more? You can find a great and free collection of literature at github/papers- we-love.