Updated the index.html to include a full HTML structure with Bootstrap
and Google tag. Modified pages.yaml to deploy from 'build/pages' branch
instead of the default branch.
Like this project? Please considering [sponsoring me](https://github.com/sponsors/dwmkerr) and the [translators](#translations). Also check out this podcast on [The Changelog - Laws for Hackers to Live By](https://changelog.com/podcast/403) to learn more about the project! You can also [download the latest PDF eBook](https://github.com/dwmkerr/hacker-laws/releases/latest/download/hacker-laws.pdf). Check the [Contributor Guide](./.github/contributing.md) if you are keen to contribute!
@@ -10,73 +10,80 @@ Like this project? Please considering [sponsoring me](https://github.com/sponsor
[90-90 Rule on Wikipedia](https://en.wikipedia.org/wiki/Ninety%E2%80%93ninety_rule)
> The first 90 percent of the code accounts for the first 90 percent of the development time. The remaining 10 percent of the code accounts for the other 90 percent of the development time.
A wry reinterpretation of the [Pareto Principe (or 80-20 rule)](#the-pareto-principle-the-8020-rule) that highlights the real-world challenges of completing engineering work. This sentiment is also echoed in [Hofstadter's Law](#hofstadters-law).
[Amdahl's Law on Wikipedia](https://en.wikipedia.org/wiki/Amdahl%27s_law)
@@ -151,7 +172,7 @@ Examples:
> Adding human resources to a late software development project makes it later.
This law suggests that in many cases, attempting to accelerate the delivery of a project which is already late, by adding more people, will make the delivery even later. Brooks is clear that this is an over-simplification, however, the general reasoning is that given the rampup time of new resources and the communication overheads, in the immediate short-term velocity decreases. Also, many tasks may not be divisible, i.e. easily distributed between more resources, meaning the potential velocity increase is also lower.
This law suggests that in many cases, attempting to accelerate the delivery of a project which is already late, by adding more people, will make the delivery even later. Brooks is clear that this is an over-simplification, however, the general reasoning is that given the ramp-up time of new resources and the communication overheads, in the immediate short-term velocity decreases. Also, many tasks may not be divisible, i.e. easily distributed between more resources, meaning the potential velocity increase is also lower.
The common phrase in delivery "Nine women can't make a baby in one month" relates to Brooks' Law, in particular, the fact that some kinds of work are not divisible or parallelisable.
@@ -186,11 +207,23 @@ See also:
- [The Fallacies of Distributed Computing](#the-fallacies-of-distributed-computing)
- [PACELC](#TODO)
### Clarke's three laws
[Clarke's three laws on Wikipedia](https://en.wikipedia.org/wiki/Clarke's_three_laws)
Arthur C. Clarke, an british science fiction writer, formulated three adages that are known as Clarke's three laws. The third law is the best known and most widely cited.
These so-called laws are:
- When a distinguished but elderly scientist states that something is possible, they are almost certainly right. When they state that something is impossible, they are very probably wrong.
- The only way of discovering the limits of the possible is to venture a little way past them into the impossible.
- Any sufficiently advanced technology is indistinguishable from magic.
### Conway's Law
[Conway's Law on Wikipedia](https://en.wikipedia.org/wiki/Conway%27s_law)
This law suggests that the technical boundaries of a system will reflect the structure of the organisation. It is commonly referred to when looking at organisation improvements, Conway's Law suggests that if an organisation is structured into many small, disconnected units, the software it produces will be. If an organisation is built more around 'verticals' which are orientated around features or services, the software systems will also reflect this.
This law suggests that the technical boundaries of a system will reflect the structure of the organisation. It is commonly referred to when looking at organisation improvements, Conway's Law suggests that if an organisation is structured into many small, disconnected units, the software it produces will be. If an organisation is built more around 'verticals' which are oriented around features or services, the software systems will also reflect this.
See also:
@@ -214,7 +247,7 @@ See also:
"Dunbar's number is a suggested cognitive limit to the number of people with whom one can maintain stable social relationships— relationships in which an individual knows who each person is and how each person relates to every other person." There is some disagreement to the exact number. "... [Dunbar] proposed that humans can comfortably maintain only 150 stable relationships." He put the number into a more social context, "the number of people you would not feel embarrassed about joining uninvited for a drink if you happened to bump into them in a bar." Estimates for the number generally lay between 100 and 250.
Like stable relationships between individuals, a developer's relationship with a codebase takes effort to maintain. When faced with large complicated projects, or ownership of many projects we lean on convention, policy, and modeled procedure to scale. Dunbar's number is not only important to keep in mind as an office grows, but also when setting the scope for team efforts or deciding when a system should invest in tooling to assist in modeling and automating logistical overhead. Putting the number into an engineering context, it is the number of projects (or normalized complexity of a single project) for which you would feel confident in joining an on-call rotation to support.
Like stable relationships between individuals, a developer's relationship with a codebase takes effort to maintain. When faced with large complicated projects, or ownership of many projects, we lean on convention, policy, and modeled procedure to scale. Dunbar's number is not only important to keep in mind as an office grows, but also when setting the scope for team efforts or deciding when a system should invest in tooling to assist in modeling and automating logistical overhead. Putting the number into an engineering context, it is the number of projects (or normalized complexity of a single project) for which you would feel confident in joining an on-call rotation to support.
See also:
@@ -233,7 +266,7 @@ The Dunning–Kruger effect is a theoretical cognitive bias which was described
The Dunning-Kruger effect has sometimes been used to describe a related, but not necessarily implied effect which could be described as "The less a person understands a domain, the more they are likely to believe they can easily solve problems in that domain, as they are more likely to see the domain as _simple_". This more general effect is highly relevant in technology. It would suggest that people who are less familiar with a domain, such as non-technical team members or less experienced team members, are more likely to _underestimate_ the effort required to solve a problem in this space.
As a person's understanding and experience in a domain grows, they may well encounter another effect, which is that they tend to _overestimate_ the ability of _others_ or _underestimate_ their own ability, as they are have become so experienced in the domain. In all cases these effects are _cognitive biases_. As with any bias, an understanding that it may be present will often be sufficient to help avoid the challenges - as when there is awareness of a bias more inputs and opinions can be included to attempt to eliminate these biases. A closely related is the bias of [Illusory superiority](https://en.wikipedia.org/wiki/Illusory_superiority).
As a person's understanding and experience in a domain grows, they may well encounter another effect, which is that they tend to _overestimate_ the ability of _others_ or _underestimate_ their own ability, as they are have become so experienced in the domain. In all cases these effects are _cognitive biases_. As with any bias, an understanding that it may be present will often be sufficient to help avoid the challenges — as when there is awareness of a bias, more inputs and opinions can be included to attempt to eliminate these biases. A closely related bias is that of [Illusory superiority](https://en.wikipedia.org/wiki/Illusory_superiority).
Real-world examples:
@@ -392,6 +425,24 @@ See also:
- [The Law of Leaky Abstractions](#the-law-of-leaky-abstractions)
- [XKCD 1172](https://xkcd.com/1172/)
### Input-Process-Output (IPO)
[Input–Process–Output on Wikipedia](https://en.wikipedia.org/wiki/IPO_model)
Systems can be incredibly complex, but can typically be broken down into smaller parts that follow a simple pattern:
1. Input is provided
2. Some kind of processing or transformation is performed
3. Output is returned
A sort function in a programming language or system could be a classic example of the IPO pattern; where arbitrary input is sorted based on a predicate and returned back. A web server could be modelled as an IPO system, where HTTP requests are transformed into HTTP responses. A highly complex Generative AI system could likewise be modelled in this way, with user input being passed through a complex model and a response being generated.
The IPO pattern is present in different forms across almost all technological domains, from [functional programming](https://en.wikipedia.org/wiki/Functional_programming) languages that explicitly follow IPO patterns to [The Unix Philosophy](#the-unix-philosophy), which suggests that highly complex systems can be built by chaining together many simple IPO programs.
See also:
- [The Unix Philosophy](#the-unix-philosophy)
### Kernighan's Law
> Debugging is twice as hard as writing the code in the first place. Therefore, if you write the code as cleverly as possible, you are, by definition, not smart enough to debug it.
@@ -502,7 +553,7 @@ See also:
### Premature Optimization Effect
[Premature Optimization on WikiWikiWeb](http://wiki.c2.com/?PrematureOptimization)
[Premature Optimization on WikiWeb](http://wiki.c2.com/?PrematureOptimization)
> Premature optimization is the root of all evil.
>
@@ -543,6 +594,15 @@ See also:
- [Metcalfe's Law](#metcalfes-law)
- [Dunbar's Number](#dunbars-number)
### The Ringelmann Effect
[The Ringelmann effect on Wikipedia](https://en.wikipedia.org/wiki/Ringelmann_effect)
The Ringelmann Effect is the tendency of an individual to become increasingly inefficient as more and more people are involved in a task. In other words, as more individuals are added to a team, the more the average individual performance decreases. Multiple causes are believed to be at work, including loss of motivation ("[social loafing](https://en.wikipedia.org/wiki/Social_loafing)") and challenges related to coordination.
See also:
- [Brooks' Law](#brooks-law)
### The Law of Conservation of Complexity (Tesler's Law)
[The Law of Conservation of Complexity on Wikipedia](https://en.wikipedia.org/wiki/Law_of_conservation_of_complexity)
@@ -589,6 +649,25 @@ Real-world examples:
- [Photoshop Slow Startup](https://forums.adobe.com/thread/376152) - an issue I encountered in the past. Photoshop would be slow to startup, sometimes taking minutes. It seems the issue was that on startup it reads some information about the current default printer. However, if that printer is actually a network printer, this could take an extremely long time. The _abstraction_ of a network printer being presented to the system similar to a local printer caused an issue for users in poor connectivity situations.
### The Law of the Instrument
[The Law of the Instrument](https://en.wikipedia.org/wiki/Law_of_the_instrument)
> I call it the law of the instrument, and it may be formulated as follows: Give a small boy a hammer, and he will find that everything he encounters needs pounding.
>
> _Abraham Kaplan_
> If all you have is a hammer, everything looks like a nail.
>
> _Abraham Maslow_
In the context of computer programming, this law suggests that people tend to use tools that are familiar with, rather than the best possible tool. This over-reliance on a familiar tool is an anti-pattern referred to as 'the golden hammer'.
See also:
- [Avoiding the law of the instrument](https://josemdev.com/avoiding-the-law-of-the-instrument/)
- [Anti-Pattern - The Golden Hammer](https://archive.org/details/antipatternsrefa0000unse/page/111/mode/2up)
### The Law of Triviality
[The Law of Triviality on Wikipedia](https://en.wikipedia.org/wiki/Law_of_triviality)
@@ -649,6 +728,18 @@ The number of links between people can be expressed as `n(n-1)/2` where n = numb
<imgwidth="200px"alt="Complete graph; Links between people"src="./images/complete_graph.png"/>
### Twyman's law
[Twyman's Law on Wikipedia](https://en.wikipedia.org/wiki/Twyman%27s_law)
> The more unusual or interesting the data, the more likely they are to have been the result of an error of one kind or another.
This law suggests that when there are particularly unusual data points, it is more likely that they are the result of errors or manipulation. For example, if a dataset of long-jump results from a sporting event showed a maximum value of 20 meters (more than twice the world record), it is more likely to be due to an error (such as recording a value in feet rather than meters) than due to an unusually long jump. It is also more likely in this case that the results could have been manipulated.
See also:
- [Sagan Standard](#TODO)
### Wadler's Law
[Wadler's Law on wiki.haskell.org](https://wiki.haskell.org/Wadler's_Law)
@@ -788,7 +879,7 @@ See also:
A management concept developed by Laurence J. Peter, the Peter Principle observes that people who are good at their jobs are promoted, until they reach a level where they are no longer successful (their "level of incompetence"). At this point, as they are more senior, they are less likely to be removed from the organisation (unless they perform spectacularly badly) and will continue to reside in a role which they have few intrinsic skills at, as their original skills which made them successful are not necessarily the skills required for their new jobs.
This is of particular interest to engineers - who initially start out in deeply technical roles, but often have a career path which leads to _managing_ other engineers - which requires a fundamentally different skills-set.
This is of particular interest to engineers - who initially start out in deeply technical roles, but often have a career path which leads to _managing_ other engineers - which requires a fundamentally different skillset.
@@ -832,7 +922,7 @@ These are key principles in [Object-Oriented Programming](#todo). Design princip
The first of the '[SOLID](#solid)' principles. This principle suggests that modules or classes should do one thing and one thing only. In more practical terms, this means that a single, small change to a feature of a program should require a change in one component only. For example, changing how a password is validated for complexity should require a change in only one part of the program.
Theoretically, this should make the code more robust, and easier to change. Knowing that a component which is being changed has a single responsibility only means that _testing_ that change should be easier. Using the earlier example, changing the password complexity component should only be able to affect the features which relate to password complexity. It can be much more difficult to reason about the impact of a change to a component which has many responsibilities.
Theoretically, this should make the code more robust, and easier to change. Knowing that a component being changed has a single responsibility only means that _testing_ that change should be easier. Using the earlier example, changing the password complexity component should only be able to affect the features which relate to password complexity. It can be much more difficult to reason about the impact of a change to a component which has many responsibilities.
See also:
@@ -864,7 +954,7 @@ See also:
The third of the '[SOLID](#solid)' principles. This principle states that if a component relies on a type, then it should be able to use subtypes of that type, without the system failing or having to know the details of what that subtype is.
As an example, imagine we have a method which reads an XML document from a structure which represents a file. If the method uses a base type 'file', then anything which derives from 'file' should be able to be used in the function. If 'file' supports seeking in reverse, and the XML parser uses that function, but the derived type 'network file' fails when reverse seeking is attempted, then the 'network file' would be violating the principle.
As an example, imagine we have a method which reads an XML document from a structure which represents a file. If the method uses a base type 'file', then anything which derives from 'file' should be usable in the function. If 'file' supports seeking in reverse, and the XML parser uses that function, but the derived type 'network file' fails when reverse seeking is attempted, then the 'network file' would be violating the principle.
This principle has particular relevance for object-oriented programming, where type hierarchies must be modeled carefully to avoid confusing users of a system.
@@ -898,7 +988,7 @@ See also:
> High-level modules should not be dependent on low-level implementations.
The fifth of the '[SOLID](#solid)' principles. This principle states that higherlevel orchestrating components should not have to know the details of their dependencies.
The fifth of the '[SOLID](#solid)' principles. This principle states that higher-level orchestrating components should not have to know the details of their dependencies.
As an example, imagine we have a program which read metadata from a website. We would assume that the main component would have to know about a component to download the webpage content, then a component which can read the metadata. If we were to take dependency inversion into account, the main component would depend only on an abstract component which can fetch byte data, and then an abstract component which would be able to read metadata from a byte stream. The main component would not know about TCP/IP, HTTP, HTML, etc.
@@ -917,7 +1007,7 @@ See also:
> Every piece of knowledge must have a single, unambiguous, authoritative representation within a system.
DRY is an acronym for _Don't Repeat Yourself_. This principle aims to help developers reducing the repetition of code and keep the information in a single place and was cited in 1999 by Andrew Hunt and Dave Thomas in the book [The Pragmatic Developer](https://en.wikipedia.org/wiki/The_Pragmatic_Programmer)
DRY is an acronym for _Don't Repeat Yourself_. This principle aims to help developers reducing the repetition of code and keep the information in a single place and was cited in 1999 by Andrew Hunt and Dave Thomas in the book [The Pragmatic Programmer](https://en.wikipedia.org/wiki/The_Pragmatic_Programmer)
> The opposite of DRY would be _WET_ (Write Everything Twice or We Enjoy Typing).
@@ -925,7 +1015,7 @@ In practice, if you have the same piece of information in two (or more) differen
- [Foraging for the Fallacies of Distributed Computing (Part 1) - Vaidehi Joshi
on Medium](https://medium.com/baseds/foraging-for-the-fallacies-of-distributed-computing-part-1-1b35c3b85b53)
### The Principle of Least Astonishment
[The Principle of Least Astonishment on Wikipedia](https://en.wikipedia.org/wiki/Principle_of_least_astonishment)
> People are part of the system. The design should match the user's experience, expectations, and mental models.
>
> Frans Kaashoek
This principle proposes that systems and interfaces should be designed in a way that features and functionality is easily discovered and matches users expectations. Features that 'surprise' users should be discouraged in favour of features that can be intuitively reasoned about based on existing patterns and practices.
Many examples are present in user interfaces, such as a 'pull down' gesture on a mobile appliation to refresh content. Another example would be command line tools, where many standards exist for how parameters are named, common parameters that should be available and so on.
See also:
- [Convention Over Configuration](#todo)
## Reading List
If you have found these concepts interesting, you may enjoy the following books.
@@ -1022,6 +1128,7 @@ Thanks to a number of wonderful contributors, Hacker Laws is available in a numb
| [🇺🇦 українська мова / Ukrainian](./translations/uk.md) | [Nazar](https://github.com/troyane), [Helga Lastivka](https://github.com/HelgaLastivka) | [](https://gitlocalize.com/repo/2513/uk?utm_source=badge) |
| [🇻🇳 Tiếng Việt / Vietnamese](./translations/vu.md) | [Nguyên](https://github.com/truonghoangnguyen), [Trương Hoàng](https://github.com/truonghoangnguyen) | [](https://gitlocalize.com/repo/2513/vi?utm_source=badge) |
If you would like to update a translation, follow the [Translators Contributor Guide](https://github.com/dwmkerr/hacker-laws/blob/main/.github/contributing.md#translations).
@@ -499,7 +499,7 @@ Les principes sont généralement des lignes directrices liés à la conception.
> Les entreprises tendent à promouvoir systématiquement les employés incompétents afin de les sortir du workflow.
> *Scott Adams*
Un concept de gestion inventé par Scott Adams (créateur du comic strip Dilbert) inspiré par le [principe de Peter](#principe-de-peter). Suivant le principe de Dilbert, les employés qui n'ont jamais montré de compétence dans leur travail sont promus à des postes de management afin de limité les dommages qu'ils peuvent causer. Adams expliqua initialement le principe dans un article du Wall Street Journal datant de 1995, et élabora le concept dans son livre de 1996: [The Dilbert Principle](#a-lire).
Un concept de gestion inventé par Scott Adams (créateur du comic strip Dilbert) inspiré par le [principe de Peter](#principe-de-peter). Suivant le principe de Dilbert, les employés qui n'ont jamais montré de compétence dans leur travail sont promus à des postes de management afin de limiter les dommages qu'ils peuvent causer. Adams expliqua initialement le principe dans un article du Wall Street Journal datant de 1995, et élabora le concept dans son livre de 1996: [The Dilbert Principle](#a-lire).
リクエストしたい場合は [Raise an Issue](https://github.com/dwmkerr/hacker-laws/issues) rをクリックするか、トピックの定義案を提出したい場合は [Open a Pull Request](https://github.com/dwmkerr/hacker-laws/pulls) をクリックしてください。
リクエストしたい場合は [Raise an Issue](https://github.com/dwmkerr/hacker-laws/issues) をクリックするか、トピックの定義案を提出したい場合は [Open a Pull Request](https://github.com/dwmkerr/hacker-laws/pulls) をクリックしてください。
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