Digital Garden
My Digital Garden - after an idea from so many others. Because I could not express it in any better way, I quote Joel Hooks
While not everybody has or works in a dirt garden, we all share a familiarity with the idea of what a garden is.
A garden is usually a place where things grow.
Gardens can be very personal and full of whimsy or a garden can be a source of food and substance.
(...)
Like with real gardens, our digital gardens are a constant ebb and flow towards entropy.
Weeds take over. Left untended the Earth will reclaim what belongs to it.
The same is true for our digital gardens here on the internet.
I try to work with my garage door up, so feel free to have a look.
This is me, in case you wondered.
Except where otherwise noted ("non-cc"), is this work by Raphael Sprenger licensed under CC BY-NC 4.0
Algorithms
The first entry on this page should be a link to Nick's damn cool algorithms. Because algorithms can be damn cool. The rest of links on this page come in no specific order (for now).
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CORDIC efficient calculation of trigonometric functions. Easy to implement on hardware as it only requires shift and add operations and is way simpler than for example Taylor Series. Some scientific calculators still implement this algorithm today. (mentioned in Analogrechnen) Comparison of different implementations of Cosine, including CORDIC and Taylor Series
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Zsh and Fish’s simple but clever trick for highlighting missing linefeeds Terminals do not provide a lot of options to work with missing linefeeds. One reason is that shells do not read processe's output
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Conflict-free replicated data type for example for Etherpad. I read someone suggesting Firebase but for conflict-free data, which makes sense considering syncing between mobile apps and the web. In addition a practical guide for data syncing on iOS
-
Normalizing Unicode If strings look the same, they do not necessarily have the same byte representation, so normalization is required
-
How random can you be? Game to predict user inputs, because human behaviour is (usually) not random. The algorithm behind is rather simple. Every possible sequence of five user choices is in a database. Under each sequence, there are two counters, one for "user choice 1", the other for "user choice 2". Whenever the user chooses between two options, the software takes the last five entries, looks that sequence up in the database, and updates the counter according to the user's choice. Before the next user input, the algorithm can look up the sequence of the last five button presses, check which counter is higher, and based on the higher counter, predict which choice the user is likely to make.
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JMAP (is not IMAP) new e-mail protocol
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Negative base number system without the (positive/negative) sign, but with increased complexity for calculations
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Fallacies of distributed computing false assumptions programmers have, collected by Sun Microsystems
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Magnetic ink character recognition is still a thing when it comes to automatic character recognition, for example my amateur radio club uses it for paper mail processing
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QR-Codes explained step by step and because you will need it: Explanation of Reed-Solomon
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Book Review: A Philosophy of Software Design contains a good summary, which is good, because I never found time to read the book
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The Illustrated TLS Connection Step by step walk-through the protocol
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Let’s talk about PAKE which stands for Password Authenticated Key Exchange. Could be a handy way of web authentication, as people agree on a pre-shared key with almost every authenticated web service. Sharing the secret is not required for this protocol, so phishing would get a lot harder (Compare WebAuthn)
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High Density Wi-Fi Deployments almost complete guide for an industrial wifi network and another article on the same topic
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Functional programming with the most popular functional programming language: JavaScript
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Image Discovery on Netflix How Netflix automatically generates preview images for movies
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Eller's Algorithm for perfect mazes
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Thinking for programmers talk by Leslie Lamport
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Choosing random points inside a sphere is harder than you think, as spheres are hardly linear
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How Not To Sort By Average Rating Websites like to present public user inputs in some sort of rating. The best solution I know is explained here.
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HyperLogLog — A probabilistic data structure Count distinct elements in a set in an efficient (but not exact) way
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Mann–Whitney U test Check if two samples are from the same distribution
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Zero knowledge proofs link collection
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Rendezvous hashing for agreeing from a set of options
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Heap's algorithm for all permutations of a set
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Sussman anomaly and the quirks of planning in artificial intelligence
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Union find data structure how social networks solve "You and your friend both know person X"
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Traveling Salesman solved not really of course, but a self-organizing map helps
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Bresenham's Algorithm explained. Drawing straight lines on pixelated displays
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The tricky nature of formatting a programmer's jouney on a seemingly simple task
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Floyd-Warshall Algorithm to find the shortest path between two nodes in a graph
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Zooko's Triangle the law that came across my programming journeys most often I think. For names in a network, you can only pick two: Human-Meaningful; Secure; Decentralized
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Observed Failures by NASA. All of them in the category "that can't happen". All of them could have been found by formal analysis
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Detection and handling of state flapping, a common problem mainly in monitoring
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Exactly once approach Doing things exactly once in a distributed system is easy and sometimes inevitable, for example when billing customers
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Surprising statistical effect when sharing money randomly in a group (original source is not available anymore)
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Allen's interval algebra event start times and their relations
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Closest pair of points problem one of the first problems treated in computational complexity
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Fisher-Yates Shuffle or, how to efficiently shuffle a playlist
Artificial Intelligence
These are mostly reading notes from the wonderful book Artificial Intelligence by Melanie Mitchell.
Monte Carlo Tree
The path of a tree is followed from the root towards one leaf. The path is chosen at random. At every branching node, a random branch is chosen. This approach is useful for huge decision trees, for example in the game of Go. Evaluating every path is computationally not feasible. When evaluating a big amount of paths, it is likely to find a good enough solution. In contrast, when evaluating all paths, the optimum solution will be found.
Genetic Algorithms
Genetic algorithms can find a good solution in a non-gradient environment. This is possible whenever a program can follow a rule set. Rules are changed for every iteration and the outcome is evaluated. Rules have to have a binary representation, so that a binary String can be genetically modified. The general pattern is:
- Initialisation with a random rule set
- Select best performing rules
- Apply genetic operators such as Crossover and Mutation
- Terminate under a condition, for example after a number of rounds or at a cost-threshold
Q-Tables
First a word about what Q-Tables are good for. Whenever a program has to reach one single goal, and the way to achieve this goal is unknown, Q-Tables can do the trick. An intuitive example is to find the exit of a maze: One final reward without the evaluation of intermediate steps.
There are States the program can be in, the rows of the Q-Table. For any given State, there are Options the algorithm can choose from, the columns. To stay with the maze example, if the player is in a State of being placed in the middle of an open field, then the options are to move in any direction (North, East, South, …).
At first, the moves start from a random location and happen randomly in order to find the reward. Only the action that led to the reward gets stored with a high number of points in the Q-Table (for example 100 points. This is up to the fine tuning of the use-case). For example, the State is “One step straight ahead towards the exit” and the chosen Option was “Move straight”, which unlocks the reward, will lead to a high number in this State-Option combination.
In the second round, not finding the reward counts, as the solution was already found. More important is, how does the algorithm find the State that led to the reward. In the example, what comes before standing right in front of the exit? If this pre-reward step was found, another high number is stored in the Q-Table for the respective State-Option combination.
This pattern of finding the pre-step to every previous round continues. There is one exception: With a low chance, the algorithm can choose an Option that is not associated with a (high) number of points. In that way, it will find potentially better solutions and try moves it never tried before.
Deep (convolutional) networks
Whenever the output for an input of n values is known, this algorithm strikes. That means the input needs to be quantifiable and the output has to be known already, at least for a training set. Between Input and Output is a “deep” or “hidden” layer. This layer multiplies the Inputs and forwards the result to the Outputs. Every node in the hidden layer is connected to every Input and every Output.
When training the network, the multipliers at the hidden layer(s) are gradually adapted to best match all Inputs to their expected result.
This technique is conceptually easy to understand, but extremely hard to master, as it requires fine-tuning and a good intuition on how to apply changes.
Reenforced learning
As well known as “self learning”. Good behaviour is rewarded, while bad behaviour is ignored. An example will give an intuition on how reenforced learning works in practice. AlphaZero, the Go playing machine, uses a combination of deep neural networks and Monte Carlo trees (at least one of the earlier versions of AlphaZero did. The approach was changed later). The deep neural network suggests, which Monte Carlo trees to try. The best performing Monte Carlo tree is fed back into the neural network, so that in a next iteration, the neural network can make even better suggestions which Monte Carlo trees to try for a similar situation. This technique only works if the output of the round can be clearly scored, so that the neural network only trains itself with good inputs.
Natural language processing
A language is natural if humans speak it.
Recurring neural networks
An early approach for natural language processing was the use of recurring neural networks. A recurring neural network feeds back its own values into the network, together with another input. Let’s say, every word in the dictionary gets a value. A sentence, now formed of a String of values, is fed into the recurring neural network, one at a time. To keep track of the sentence’ state, the output from the previous words are fed back into the network together with the value of the current word. This technique is also called one-hot input, as only always one word is active at a time. After years of experimentation, the results are not as good as with other techniques for language processing.
Long short-term memory
Unfortunately not furhter explained in Mitchell's book and only briefly referenced in Translation. The LSTM addresses the deficites of sequential inputs in recurring neural networks. The cell state is the information transportation system from step to step. The information can stay the same over time or gradually change. It is used to generate unit output together with other operations explained below. LSTMs have four hidden layers. The first layer decides about which information to "forget" from cell state. The next two layers figure out, what to add to the cell state. The fourth layer renders the output from the cell state and the cell's input for this particular step.
Word vectors
Before explaining how word vectors are generated, I start with a motivating example: Word vectors give the similarity of meaning between to words. Words that are more closely related have a shorter distance than words that have very different meanings. A surprising property is the distance between word correlations. Measuring the distance Man -> Prince yields almost the same distance as Woman -> Princess. To make use of this property, the word cloud can answer questions. Asking Fish -> Water; Bird -> ? will give the answer Air. This is possible by measuring the distance Fish -> Water and then checking what lays in the same distance from the word Bird. Google released a 300 dimensional word cloud called word2vec. How did they create it?
Start with a neural network with one hidden layer containing 300 (hidden) units. The input and output layers have a unit for every word from the dictionary, so it is a rather huge input/output layer. From a sentence, feed adjacent words into the network. For example, feed Burger and train for Restaurant. Also train for the opposite case. Once the training is done, extract the word vector. To do that, every word from the dictionary is “lit up” in the network. The “illumination” of the hidden layer will mark the position in the 300-dimensional space.
It is possible to project a higher-dimensional space into two or three dimensions, so that humans can visualise and inspect them more easily.
Translation
Traditionally, translation systems were composed of human made rules. Google drastically changed this in 2016 with the release of the machine learning translation system.
The outline of this idea is to have an encoder- and a decoder neural network. The encoder is fed with a sentence, using the one-hot approach (see recurring neural networks) . At the end, a stop sequence is used and the activation of units in the network is extracted. This activation is fed into the decoder network for the target language, which converts the sequence of values back into a sequence of words. In contrast to simple neural networks, the units in these encoder/decoder networks are made from “long short-term memory” LSTM units. These units account for inputs that come over time and autonomously decide which inputs to generously “forget”. The length of the sentence from the original language can be different from the length of the resulting language.
Understanding text
How to evaluate that a machine can really understand the contents of a sentence, in contrast to simply react on it in a trained way? A powerful approach is to ask a question like “The couch did not fit through the hallway, because it was too narrow. What was too narrow?”. A machine neither understanding what a couch or a hallway is nor knowing its dimensions and relations, will never be able to answer this question. This test has an infinite amount of possibilities as new questions can simply be created: “Water was filled from the bottle into the glass until it was empty. What was empty?”. By creating enough questions in this pattern, only a machine that clearly understands text can score at about 100%, otherwise it will be roughly 50% for random choices.
References
Aviation
VFR flight preparation
- KNMI - Weerbulletin kleine luchtvaart Dutch weather forecast for general aviation
- FMC Poster (in Dutch), the new Frequency Monitoring Code system in the Netherlands
- Interactive VFR Chart Netherlands
- 3D route planning with CONFIDENT a software I wrote to simplify flying through complex airspace
Other links
Automation
Digital Garden
One of my needs is an easy setup for gardening. I need to be able to write notes on all of my devices, including my phone. gitea has a built-in Markdown editor, so I can edit text and work with git at the same time. The content is rendered by mdBook.
Using git hooks
Git hooks are run on the server while commits are being applied to a repository. This is a low resource approach because it only runs when the garden received an update. It is quite limited to the machine that hosts the git repository though.
Gitea has an option to manage git hooks. I read they only run if Gitea manages the SSH keys. I didn't test with local SSH keys. To enable git hooks, change the app.ini
and add DISABLE_GIT_HOOKS = false
, default is true
. Restart gitea.
Caution! : Users who can access git hooks can run arbitrary commands on the server. Only allow this option if you can fully trust the user.
Go to the repo settings and define the post-receive git hook:
#!/bin/sh
echo "removing old deployment"
targetdir=/yourwebdir
cd $targetdir
rm -rf *
echo "running deployment"
git --work-tree=$targetdir --git-dir=/path-to-your/garden.git checkout -f
/usr/local/bin/mdbook build
rm *
rm -rf src/
cp -r book/* .
rm -rf book/
echo "new mdbook built and deployed"
The directory /yourwebdir
needs to have read/write permissions for the user running gitea which is usually git
.
Using deploy-keys and a cron job
On my server I created a user
useradd --system --create-home --home-dir /var/lib/mdbook --shell /usr/sbin/nologin --comment "mdbook Digital Garden" mdbook
For this user, I create a new ssh-key. When asked where to store it, I choose /var/lib/mdbook/.ssh
ssh-keygen -t rsa -b 4096 -C "your_email@example.com"
In gitea, I use the option for deploy-keys and add above key. Deploy keys are read only for a specific repository.
To /var/lib/mdbook I add a build.sh script
#!/bin/bash
cd /var/lib/mdbook/garden
/usr/bin/git pull -q
/usr/bin/mdbook build -d /usr/share/garden /var/lib/mdbook/garden
And a cronjob in /etc/crontab
* * * * * mdbook /var/lib/mdbook/build.sh
Books I read
No particular order yet
Bedside table
My bedside table is empty. Reading the magazine Brand Eins occasionally.
English
Science
- A Philosophy of Software Design - John Ousterhout
- Artificial intelligence - Melanie Mitchell (my reading notes)
- Six impossible things (The 'Quanta Solace' and the Mysteries of the Subatomic World) - John Gribbin
- Designing Data-Intensive Applications (The big ideas behin reliable, scalable, and maintainable systems) - Martin Kleppmann
- Complexity (A guided tour) - Melanie Mitchell (See also Machine Learning’s ‘Amazing’ Ability to Predict Chaos)
- Game feel (A game designer's guide to virtual sensation) - Steve Swink
Fiction
- The sound of rain - Paul Honkani
- House of leaves - Mark Z. Danielewski
- The garden of bad dreams - Christopher Hope
German
Science
- Das Ende des Individuums - Gaspard Koenig
- Grenzen der Demokratie(Teilhabe als Verteilungsproblem) - Stephan Lessenich
- Ethik in KI und Robotik - Chrisoph Bartneck, Christoph Lütge, Alan Wagner, Sean Welsh
- Der Sprachverführer (Die deutsche Sprache: was sie ist, was sie kann) - Thomas Steinfeld
- Lean Brain Management (Erfolg und Effizienzsteigerung durch Null-Hirn) - Gunter Dueck
- Schwarmdumm (So blöd sind wir nur gemeinsam) - Gunter Dueck
- Eine kurze Geschichte der Zeit - Stephen Hawking
- Eine kurze Geschichte von fast allem - Bill Bryson
- Das Neue und seine Feinde (Wie Ideen verhindert werden und wie sie sich trotzdem durchsetzen) - Gunter Dueck
- Keine Ahnung von der Materie (Physik für alle!) - Hans Graßmann
- Die Philosophie des Abendlandes - Bertrand Russel
Fiction
- Offene See - Ben Myers
- Ein ganzes Leben - Robert Seethaler
- Der Sonntag, an dem ich Weltmeister wurde - Friedrich Christian Delius
- Die Besteigung der Eiger-Nordwand unter einer Treppe - Max Scharnigg
- Die Entdeckung der Langsamkeit - Sten Nadolny
- Der Kampf geht weiter! (Nicht weggeschmissene Briefe) - Harry Rowohlt
- Pu der Bär - A. A. Milne (Audiobook - Harry Rowohlt)
- Mir kocht die Blut! (Die wunderbare Welt der Querulanten und Sonderlinge) - Roger Willemsen (Audiobook - Anke Engelke, Roger Willemsen)
- Der leidenschaftliche Zeitgenosse (Zum Werk von Roger Willemsen) - Insa Wilke
- Die Enden der Welt - Roger Willemsen
- Momentum - Roger Willemsen
- Wer wir waren - Roger Willemsen
- Afghanische Reise - Roger Willemsen
- Deutschlandreise - Roger Willemsen
- Bangkok Noir - Roger Willemsen
- Die wundersamen Irrfahrten des William Lithgow - publisher Roger Willemsen
- Das süße Gift der Sünde - publisher Roger Willemsen
- Auf Schwimmen-zwei-Vögel - Flann O'Brien
- Die Hauptstadt - Robert Menasse
- Das Muschelessen - Birgit Vanderbeke
- Der satanarchäolügenialkohöllische Wunschpunsch - Michael Ende
Dutch
Fiction
- Het smelt - Lize Spit
Publisher
- Mikrotext e-book publisher in Berlin
Cheat Sheets
Complexity
Notes from the book A Philosophy of Software Design, which is about managing complexity in software designs.
Causes of complexity: Accumulation of dependencies and obscrurities. A single occurence of these doesn't make a system complex. It is always the accumulation of these factors.
Results of complexity:
- Change amplification (A small change requires a big refactoring)
- High cognitive load
- Unknown unknowns (sometimes you don't even know what you need to know to safely apply a change)
Which lead to:
- More code modifications for new features
- requiring more time to gather information
- risk of modification
Digital Gardens
Digital Gardens live somewhere in the space of personal wikis and experimental knowledge systems, as Mappletons describes it in a twitter thread. This garden runs on gitea and mdbook.
As we may think
As we may think is the title of an article published by The Atlantic in July 1945, written by Vannevar Bush. Bush makes a prediction about how we will use technology in the future as an external thinking device. He elaborates lengthy on the feasability of his suggestion, something that would not be necassary today, as we all know that microelectronic storage of information, search-algorithms, text-to-speech and speech-to-text, cameras and displays are part of the daily life for many. In Bush's oppinion, mature thought can't be replaced. In contrast, he believes that creative thought and repetitive thought can be supported by mechanical aids. (I am sure, the word mechanical was used in lack of foreseeing an electronic revolution, enabled by the invention of transistors.) He calls such a mechanical aid a Memex. A machine that is equipped with research papers, encyclopedias and so forth. Furthermore it can be fed with own input like writing, pictures and voice recodings. The user can build so called trails of information. That is, whenever they see two references on the screen, the user hits a button and joins the two articles. These joins can grow to a trail. Bush even speaks about branching out, whenever a trail needs to follow a sub-topic.
Managing digital stuff
The Science of Managing Our Digital Stuff is a talk given by Ofer Bergman at Microsoft. The way it is presented is not really easy to follow due to sound and image quality. The content is dense and interesting though. Bergman argues that managing data inside file hierarchies is not the best approach. Files get hidden in nested folder structures. Files that could logically be sorted into multiple places can only take one place. There are no conventions for folder structures and people tend to forget even their own structures after a few weeks. Modern operating systems offer better systems than folder structures. The two prominent ones are quick full text search and file tagging. In his research, Bergman found that most people still prefer navigating through a folder structure, even when they were free to choose one of the other systems. Is it just habit? Bergman found that formulating a search query requires a context switch whereas navigation activates a different part in the brain. The context switch makes people forget what they worked on initially. His research is backed by fMRI scans where he could prove the activation of different parts of the brain. Bergman concludes that we need improved navigation instead of improved search and tagging. He developed prototypes to showcase how it could look like. An address book on a phone would show the most dialed contacts on top and keep all other contacts below. A shared drive would highlight the subjectively most important documents on top and render all other files below, slightly greyed out.
Links
Gardens
- Brendex' Garden Well organized digital garden
- Nikita Voloboev The biggest garden I know
- MaggieAppleton digital-gardeners Links and resources to gardens / gardening
- KasperZutterman Second-Brain Long list of gardens
- Andy Matuschak Well maintained garden without a global index, you need to find your way into it, and then it is an insightful place. Andy published a video about his writing habits as well
Patterns
- Open Transclude Pattern for including iframe previews with plain HTML/CSS/JS
- Andy Matuschak Thoughts about knowledge and thinking (he has a nice garden too, see above)
- Freeing the web from the browser with open hypermedia
- Book review: How to Take Smart Notes? gives an overview of the book's concepts and linking it to academic writing, including criticism of academic writing like the increasing pattern of "publish or perish", quoting a study that the academic output doubles every 5 years.
- Digital Tools I wish existed Jonathan has some thoughts about his workflow of processing information, and what he would need to do so more efficiently.
Private Garden
There are some notes, ideas, thoughts, ... that I want to keep private and others, for example e-books, that I have to keep private for legal reasons.
I think about creating a private garden with the same setup as this public garden, but behind a basic auth and under a different sub-domain. That way, I can cross-reference my notes.
Unfortunately, this would lead to a lot of "not for public"-links. Something, I don't want my visitors encounter too often.
Distributed Systems
Links
-
In Search of Five 9s - Calculating Availability of Complex Systems
-
Testing Distributed Systems | Curated list of resources on testing distributed systems
-
Distributed architecture concepts I learned while building a large payments system
-
The Log: What every software engineer should know about real-time data's unifying abstraction I re-discovered this blog post and it is a fantastic resource for understanding why Kafka came into existence and how it supports the "integration of everything" approach. It is a longer read. It took me several days to work through it. I think this text should be part of the standard literature about logs. It also presents how far one can drive a rather simple idea like a log. Check out the references at the end of the post as well.
-
Event-driven Data or: How I Learned to Stop Living in the Present and Travel Through Time
-
Microservices are hard — an invaluable guide to microservices
The cloud native maturity model
Consistency Models
(Summary of Strong consistency models)
Concurrent Histories
With several processes, I write to one common storage, that can be spread across multiple nodes.
Light Cones
There is a time slot for the task to write to acknowledge the write. Same for read access.
Linearizability
If a write task was acknowledged, the result is visible for all reading clients.
Sequential Consistency
If something was given to the system in a certain sequence, the visibility will be in the same sequence. Example: posts (A, then B) to a social network are not visible immediately. But if A becomes visible, only after that, B will become visible.
Causal Consistency
Only if operations are dependent from another, they will be given in the correct sequence. For example can read access only be allowed after certain conditions are met.
Serializable Consistency
Is weak because reads and writes can travel to the past and to the future. Is strong because it requires a linearization and certain conditions. The reading history is determined.
Food, Restaurants, Cafes
Cafe
-
Evermore around my corner
-
Kaffeerösterei in Hamburg, known for Deathpresso
Food
Cola I found in Oslo, listing all of its ingredients, and a recepy for 90 liters of it
Mayo I like
Recepies
FreeBSD
Install notes for IBM Thinkpad T60
I am new to FreeBSD so I am not saying this is the way to do it, but it works for me:
- Install pkg drm_kmod
- load radeon drivers on boot with rc.conf 'kld_list="radeonkms"' (don't use the recommended option of loading /boot/modules/radeonkms.ko, as this crashes during boot with a page fault)
- adduser - add an unprivileged user. While running this command, answer the question to join additional groups with "video" to make use of a graphical user interface and "wheel" to allow the command "su".
- Install pkg xorg, xinit and xfce
- Enable dbus in rc.conf 'dbus_enable="YES"' as required by xfce
- Start xfce with "startxfce4" command
Btw sound worked out of the box, which I not always had with a fresh Linux.
Unsolved problems
Running sway: It works when started from whithin xfce. Started outside, it fails with a DRM warning message.
WIFI: It seems there are compatibility problems between FreeBSD and OpenWRT. Using an old "cheap plastic router" works. Also, DHCP is not always responsive and takes two or three trials. I also had the feeling I had to switch off "powerd" on FreeBSD first (which I enabled during the FreeBSD install process) in order to get WIFI working at all, even with the plastic router. This behaviour is not confirmed though and might be coincidence.
Thinkpad Trackpad: The trackpoint (little red dot) works for mouse interactions, but the trackpad is dead
Link list
- FreeBSD graphics (and graphics card) guide https://wiki.freebsd.org/Graphics
- FreeBSD desktop environment guide (with xfce at the end) https://www.freebsd.org/doc/handbook/x11-wm.html
- FreeBSD WIFI guide https://www.freebsd.org/doc/handbook/network-wireless.html (the quickstart already does the trick for me, only that I removed the DHCP option and run it manually after boot. Otherwise, I usually don't get a Lease at all)
Change keyboard layout
kbdmap
or in rc.conf with keymap="de.kbd"
Jail
man jail
is a great resource including examples on how to get started.
- Dedicate a directory (/usr/jail/myjail; /data/jail/myjail etc) or a new zfs dataset (zfs create zroot/myjail) to the new jail.
- Load the directory with FreeBSD files by running
bsdinstall jail /usr/jail/myjail
. - Start a simple jail with
jail -c path=/usr/jail/myjail mount.devfs host.hostname=testhostname ip4.addr=192.0.2.100 command=/bin/sh
It is possible to copy a binary into the jail filesystem and execute it from whithin the jail.
Delete a jail directory
When doing rm -rf
on the jail directory, even as root, it fails to execute on a few files. The reason is that some files are marked with the "system immutable" flag. To remove it run chflags -R noschg /jaildir
and try rm
again. It could still fail if devices got mounted. Check mount
and unmount in that case.
Go
Private Repository
Not all packages are public but go mod
kind of expects that. There is a way around it.
- Modify .gitconfig (convince git to use ssh (and its key) instead of https)
[url "ssh://git@git.example.com/"]
insteadOf = https://git.example.com/
- Set these environment variables, so go knows to not verify checksums for the private repo against the public checksum API; not use the go package proxy
GOPROXY=direct;GOPRIVATE=git.example.com
GOOS and GOARCH
Type go tool dist list
or check Go (Golang) GOOS and GOARCH · GitHub
String formatting cheat sheet
fmt.Printf formatting tutorial and cheat sheet
String formatting with padding (Christopher Oezbek CC BY-SA 4.0)
Use the Printf function from the fmt package with a width of 6 and the padding character 0:
fmt.Printf("%06d", 12) // Prints to stdout '000012'
Setting the width works by putting an integer directly preceeding the format specifier ('verb'):
fmt.Printf("%d", 12) // Uses default width, prints '12'
fmt.Printf("%6d", 12) // Uses a width of 6 and left pads with spaces, prints ' 12'
The only padding characters supported by Golang (and most other languages) are spaces and 0:
fmt.Printf("%6d", 12) // Default padding is spaces, prints ' 12'
fmt.Printf("%06d", 12) // Change to 0 padding, prints '000012'
It is possible to right-justify the printing by prepending a minus -:
fmt.Printf("%-6d", 12) // Padding right-justified, prints '12 '
Beware that for floating point numbers the width includes the whole format string:
fmt.Printf("%6.1f", 12.0) // Prints '0012.0' (width is 6, precision is 1 digit)
It is useful to note that the width can also be set programmatically by using * instead of a number and passing the width as an int parameter:
myWidth := 6
fmt.Printf("%0*d", myWidth, 12) // Prints '000012' as before
This might be useful for instance if the largest value you want to print is only known at runtime (called maxVal in the following example):
myWidth := 1 + int(math.Log10(float64(maxVal)))
fmt.Printf("%*d", myWidth, nextVal)
Last, if you don't want to print to stdout but return a String, use Sprintf also from fmt package with the same parameters:
s := fmt.Sprintf("%06d", 12) // returns '000012' as a String
Links
-
Functional options for friendly APIs First time I read about functional options was here. In my opinion looks nice but hard to debug
-
Code Review Comments Patterns for code reviews
-
Standard Go Project Layout Reference for folder structure and directory names
Movies
-
Victoria - One-shot movie, playing in Berlin
-
Blau ist eine warme Farbe (orig. La vie d’Adèle) - Love story of two girls
-
Nocturnal Animals by Tom Ford - Intensive colors and costumes
Optimization
Designing systems that optimize a set of metrics subject to constraints.
The optimization process
minimize f(x) subject to x ∈ X
Minimize f(x) can be replaced by maximize -f(x)
+------+
+---+Change<-----+
| |Design| |no
| +------+ |
+---------+ +-----v-----+ +--+--+
Design +---> Initial+--->Evaluate +------->Good?|
Specifications | Design | |Performance| | |
+---------+ +-----------+ +--+--+
|
|yes
v
Final
Design
Optimize with respect to data, as intuition can be misleading.
Translating real world problems
There are some books describing the process to transform real world optimization problems to optimization problems
- Optimization: Algorithms and Applications (R.K. Arora)
- Optimization Concepts and Applications in Engineering (2nd edition, A. Keane, P. Nair)
- Computational Approaches for Aerospace Design (P.Y. Papalambros, D.J. Wilde)
- Principals of Optimal Design (Cambridge University Press, 2017)
Constraints
Constraints can be numerical (for example x ⋝ 4) but should always include the boundary (in the example 4). Excluding it (x > 4), the solution can move infinitely close to 4 without ever reaching it, which means no solution can be found.
Critical Points
A function f(x) may have a global minimum but may have multiple local minima. A zero derivative is a necessary condition for a local minimum but not a sufficient condition. The second derivative has to be >0, so the point is at the bottom of the bowl.
Podcasts
Usually available (sometimes exclusively) on Spotify
German
- Fest & Flauschig
- Baywatch Berlin
- Hotel Matze
- Codestammtisch
- Sprechen wir über Mord?! - Der SWR2 True Crime Podcast
- Podschalk
- Wie war der Tag, Liebling? - Anke Engelke, Kristian Thees
- Alles gesagt?
- Apokalypse und Filterkaffee
- Cui Bono: WTF happened to Ken Jebsen?
- JOKES mit Till Reiners
- Podcasts - der Podcast
- Wirecard: 1,9 Milliarden Lügen
Dutch
- De Brand in het Landhuis - (Documentary about a wealthy Dutch man who died in a fire in his villa under mysterious circumstances)
Projects
The things I work(ed) on
-
Self-hosted Git With a number of public repositories
-
Codestammtisch An episode of Codestammtisch that I was guest in (in German)
(Mostly) Code Snippets
AWS
It's not obvious to find out under which ARN you operate in the AWS web frontend.
If you have CLI access with the same account, type aws sts get-caller-identity
to find the ARN.
⚠️ You can't use wildcards in an "assumed-role" ARN. If you use an assumed-role ARN, it has to be complete.
Remove Role History from Console
After assuming roles, the roles end up in the "Role History". There is no easy way to remove this history.
When a name or color was chosen, it can't be changed anymore.
The only way I found to alter the Role History is by deleting the cookie noflush_awsc-roleInfo
.
In Safari this can be done via the Web Inspector -> Storage -> Cookies.
Bash
Create a random string cat /dev/urandom | tr -dc 'a-zA-Z0-9' | fold -w 8 | head -n 1
Brew
Install old versions of packages
General Software
Git
Multi-line commit messages with -m "..." -m "..."
. Bash (and other shells) allow for typing -m "... ⏎ ..."
Checkout a file from a branch with checkout <branch> -- <file or directory>
to get the state of a branch's file or directory into the current branch.
Gitea
Access to an account over https
Create an access token for this user and use it for git like https://user:token@git...
Big files over https
Gitea supports ssh access and has no file size limitations that I am aware of. Access via an Nginx proxy can lead to a 413 status code. Nginx has to accept bigger bodies client_max_body_size 100M;
or any other reasonable size.
Java Web Start
JNLP files can be executed under linux with icedtea-web.
Linux
grep
grep -E -o ".{0,5}pattern.{0,5}" file.txt
shows 5 characters before and after the found pattern.
Intel 3945AGB WiFi adapter
An old laptop has the 3945 integrated. On CentOS 8, the installation is as follows:
- Make sure the 3945 firmware is installed (search with dnf. Was installed for me by default)
- Enable the ElRepo, which contains the package kmod-iwlegacy
Explanation iwlegacy: Usually the kernel module iwlwifi contains the drivers for the chipset. Support for 3945 was removed not too long ago, so a lot of documentation still refers to the iwlwifi package. Only iwlegacy still supports the chipset.
- Install kmod-iwlegacy
- Install package crda, which contains the 'regulatory.db' file, so the wifi chip knows which local regulations to follow.
- Install NetworkManager-wifi or other preferred way of handling wifi connections
If things don't work, check lspci
, dmesg
, journalctl -u NetworkManager -e
and other logs for hints.
PXE Boot OpenWRT
How to install Debian via PXE using an OpenWRT router only:
First it's handy to have more storage on a USB drive attached to the router. My drive was formatted with NTFS, so I had
to install the ntfs-3g package to be able to mount the drive on the router opkg install ntfs-3g
(then mount /dev/sda /mnt
).
Next step is to enable PXE boot on dnsmasq. The GUI has a tab for TFTP. Enable the TFTP server and configure the mounted USB drive as TFTP root.
Debian has a handy package ready for downloading called "netboot". After unpacking, it reveals the pxelinux.0 file and a folder structure that is preconfigured to PXE boot Debian. Only make sure the pxelinux.0 resides in the TFTP root folder together with everything else that was included in the netboot archive. Link to the pxelinux.0 from the GUI. Now PXE is ready in the network.
Miniflux
My RSS reader miniflux supports Auth Proxy, which means any header can be used to pass an (existing) username. I use an internal PKI anyway, so I wanted to authenticate myself with a certificate on my server.
Nginx config snippet
ssl_client_certificate /etc/nginx/client_certs/ca.crt;
ssl_verify_client on;
Inside the location section I put proxy_set_header X-Forwarded-For $ssl_client_s_dn;
The problem here is that $ssl_client_s_dn
extracts the Common Name (CN) from the client certificate like this
CN=username
which miniflux does not understand.
To solve this, I wrote a variable mapping for Nginx
map $ssl_client_s_dn $ssl_client_s_dn_cn {
default "";
~CN=(.*) $1;
}
And used the new variable $ssl_client_s_dn_cn
inside the location section.
What the map does:
- Take the original
CN=...
string - If anything goes wrong, return "" by default
- Match a regex
~
, capture everything after theCN=
in a group and return the first group$1
Miniflux only needs one configuration parameter AUTH_PROXY_HEADER="X-Forwarded-For"
OSX
Remove quarantine attribute from executable xattr -rd com.apple.quarantine <executable-file>
Alternatively you can locate the Application, ctrl-click -> Open to override the security permissions for this App.
Force Quit Window: CMD + Option + Esc
PostgreSQL
- PostgreSQL Datatypes official documentation
- Some SQL Tricks of an Application DBA Collection of rather non-trivial tips and tricks to speed up queries
Streaming
Stream like a CTO Very professional, expensive setup for streaming. I like the tooling advise. And once money is very little object, this home office setup seems to be a lot of fun, including camera, microfone, UPS, screens, Lenovo ThinkStation and what so not.
VPN
SSH
Use SSH SOCKS proxy ssh -D 1337 -q -C -N user@server
(-D Socks, -q quiet, -C compress -N no output (-i private key))
Certificates
Convert .pfx / .p12 to .pem openssl pkcs12 -in client.pfx -out client.pem
, as used with anyconnect or openconnect.
Or the other way round, crt to pfx openssl pkcs12 -export -out certificate.pfx -inkey privateKey.key -in certificate.crt -certfile more.crt
Swift Learning
Location Services
There are three types of location services
- Visits location
- Significant Change
- Standard
The first two don’t rely on GPS location and are power-efficient. They are not meant for real-time applications or precision. Every location service needs authorisation.
Authorization
Apple Developer Documentation Add the required Description to the Info.plist
file. The description does not need to contain the App’s name. It should be friendly in tone and possibly give an example why the data is needed.
In the code, create a user dialog and ask for permission with CLLocationManager().requestWhenInUseAuthorization
.
Standard location service
Create a Class implementing NSObject, CLLocationManagerDelegate. NSObject is required. I am not sure at the moment why, but what I read is that the underlying Objective-C of the Apple-provided imports needs this declaration as well.
Link the delegation handler to an instance of CLLocationManager. clman.delegate = myDelegatedInstance
Swift Language
Attributes
Attributes have the @
operator. Attributes provide additional information about a declaration or type.
A widely used case for an attribute is the @State
in SwiftUI.
Delegation
Delegation is a design pattern to hand off responsibilities to an instance of another class. To use this pattern, a few steps are necessary:
Define a protocol
protocol MyDelegate {
func myfunc()
}
Use this protocol for an assignment in another Class
class MyClass {
var delegate:MyDelegate?
}
So delegate is ready to receive any class that conforms to the MyDelegate protocol. Now implement this Class
class MyDelegationClass: MyDelegate {
func myfunc() {
// function implementation
}
}
The delegation can be linked with the calling Class
let caller = MyClass()
let delegater = MyDelegationClass()
caller.delegate = delegater
Opaque Type
The Opaque Type was introduced in Swift 5.1 and comes into play whenever the concrete type is unknown but conforms to the protocol or protocol composition.
Optional
As in Rust, Swift knows Optionals that are enums consisting of a none and a some type. It is used if the presence of a variable is optional.
# Declare Optional
var optInt: Int? # Short-hand declaration
var optInt: Optional<Int> # Complete declaration
An Optional can be unwrapped with the unsafe short-hand optInt!
which results in runtime error if it can’t be unwrapped, for example if the variable contains nil
. The complete declaration is Optional<optInt>
Variables
A constant value is declared with let
whereas variables are declared with var
.
SwiftUI
To describe a view, structs are used. Swift uses modifiers for structs which can programatically change them, which in turn changes the layout. Updates happen asynchronously. States will not always propagate immediately.
struct ContentView: View {
var body: some View {}
}
The struct implements the protocol View
with the required variable body
.
some
declares an Opaque Type. The structure View
can have as many different implementations as there are layouts. That’s why a some
is given, so that any structure conforming to the View
protocol can be used.
@State Attribute
The State attribute is used for variables that define the single source of truth for a state in a _View_. A State property should only be accessed by the View itself or accessed by a function that’s called from inside the View. Calling states is thread safe. Whenever a State variable changes, the body of the View is recomputed.
A State is a means of reading and writing a value and is not the value itself.
Projecting a value works by prepending a $
. It will pass the value to another View.
WindowGroup
The WindowGroup is a container. It can contain more than one View. It declares a hierarchy of Views. Each Window allocates its own State. Depending on the platform, the WindowGroup can allow to present the different Windows simultaneously, for example on macOS and iPadOS.
References
Things to think
- Engineering productivity can be measured is a bold statement, after so many years of trying to quantify software development. In this article, the author states that most metrics you try to get from a team, can - and will be challenged by engineers. The most simple example is to measure lines of code. Engineeres will find ways to improve the number of lines of code tremendously, without affecting effectivity. On the other hand, not measuring at all won't help either. The bottom line of the article is to measure blockers:
Engineering should instead be about effectiveness: "How able is this engineer to effect positive impact?"
- Quality of developer tools
- Frequency and quality of internal activities (like meetings or code reviews)
- Focused maker time (free from disruptive meetings)
- Easy access to documentation
- Psychological safety on the team
- Work-life balance
- Presence of other high-performers
- A fair system of rewards
-
LoRa two-way pager a concept I even once realized on a breadboard. This project goes a few steps further in terms of portability and reproducability.
-
Modern retro computer terminals A collection of self-made 3-D printed computer housings.
-
Analogrechnen (German) Fun and entertaining talk about analog computers, especially electronic analog computers. A quick way to calculate otherwise hard to implement operations like integrations on digital computers. Requires special hardware though. (The speaker mentions CORDIC)
-
Blogger Peer Review Thoughts and links about peer reviews for blog articles. Also mentions knowledge graphs
-
My Second Year as a Solo Developer Main take-away for me is that having less income than spendings is okay for a while because it makes the savings last longer
-
Many Strategies Fail Because They Are Not Actually Strategies
-
First You Make the Maps Visualization of Map history (see Books - Mapmakers)
-
The Tao of HashiCorp Patterns inspiring me to use in software development
-
Simulating identification by zip code, gender, birthdate Seemingly not very personal data can be used to identify persons (also see Differential Privacy for Dummies for a solution)
-
Engineered Materials Arrestor System – Wikipedia Systems to stop rolling objects, for example airplanes overshooting the runway
-
Hype Tech Presentation from fefe
-
Sales Deck Five steps for a sales narrative
-
Label Schema | Bringing Structure To Labels Organize labels and tags. Standard to make collaboration easier
-
Apple’s New Map and their path to a better looking, better working digital map
-
iPhones Are Allergic to Helium Helium has so small particles, that it can travel through a membrane. A story of a weird bug discovery
-
David Patterson says its time for new computer architectures and software languages, talking about the RISC architecture
-
You don't need stand-ups "My advice for all teams is to not start by complicating things."
-
The open-plan office is a terrible, horrible, no good, very bad idea Underlying what I dislike about open offices
-
BATNA Best Alternative to a Negotiated Agreement
-
Are interruptions really worse for programmers than for other knowledge workers?
-
Admin Anti-patterns Presentation from fefe
-
Superellipse – Wikipedia Basically the "round corners" Apple uses
-
Over 150 People Tried To Draw 10 Famous Logos From Memory, And The Results Are Hilarious
-
DuckDuckGo: The Former Solopreneur That Is Beating Google at Its Game
-
The Evolution of Trust Interactive game theory
-
Complexity of the immune system (Also see books -> Complexity by Melanie Mitchell)
Screenshot from a talk Gunter Dueck gave about Intrapreneuring
Documentation done right
There are four categories of documentation:
- Tutorials (learning oriented)
- How-to guides (problem oriented)
- Reference (information oriented)
- Discussions (understanding oriented)
These categories need structurally be kept apart.
Tutorials
Tutorials are supposed to be the hardest part of a documentation to create. Let a beginner do an exercise to learn using the software. The point is practical knowledge, not theoretical knowledge. Tutorials need to be concrete and not abstract. There should be no explanation. There should be no options or choices of the path. The tutorial writer is in charge of that path. The tutorial must be reproducable under all circumstances.
How-to guides
Recipes to solve a problem to achieve an outcome. In contrast to a tutorial, the learner would not even be able to formulate a problem to solve. How-to guides do not need to start at the beginning. They can assume basic knowledge of the domain. Again, no explanations. They get in the way of actions. Choose practicability over completeness.
Reference
References are purely descriptive. They are supposed to describe the machinery. A reference should not explain what can be assumed as general knowledge of the topic. The reference’s structure should resemble the code base. The wording should be consistent.
Discussions / Background material / Explanation
Clarify and illuminate a topic. Give context and discuss alternatives. Outline conflicting opinions. Make connections. It should not contain guides or technical reference.
Reference
- YouTube Video about this topic
- The documentation system — Documentation system documentation
Why incentive plans cannot work
This is an article by Alfie Kohn published in 1993 in the Harvard Business Review Magazine. It cought my interest because of its relevance today.
Kohn claims that many companies and their managers believe in a reward system to motivate employees for better performance. He gives a number of reasons, based on scientific research, for rewards to miss the point every time. Rewards are for example
piece-work pay for factory workers, stock options for top executives, special privileges accorded to Employees of the Month, and commissions for salespeople
Rewards only achieve one thing: temporary compliance. They will lead to movement but not motivation. So the question is, do we strive for excellence? For long term growth? Or just for a quick, short-term goal.
Rewards do not create a lasting commitment. They merely, and temporarily, change what we do.
At least two dozen studies have shown that rewards will not lead to better outcomes. A study by McKinsey could not find any difference in return for shareholders among 90 companies that use rewards and those which don't.
- People doing excellent work are not driven by money. They are excellent because they intrinsically love what they do.
- Rewards and Punishment are two sides of the same coin. They are manipulative. Being controlled has a punitive character over time. Not receiving an expexted reward has the same effect as a punishment. This ultimately leads to a controlled workplace and not one that empowers learning, exploration and progress.
- Rewards only know winners and losers. They divide what was used to be a team into rewarded and punished people.
- Rewards hide underlying reasons. It is not wise to introduce rewards if there are causes for bad performance. Reasons for bad performance, among others, are too strict hierarchies, workers unable to collaborate, inadequatly prepared workers for the job, sacrifice long-term growth for short-term goals.
- Rewards discourage risk taking. With "This for that", people facing a reward will focus on the "this", not the "that".
- Any form of pay-per-performance makes people less enthusiastic. There are a few theories trying to explain this observed behaviour.
The number one casualty of rewards is creativity. As the late John Condry put it, rewards are the “enemies of exploration.”
UI / UX
Aviation
A typical action sequence is
- Reformulation of the mission task
- Access desired inputs
- Format data for proper input
- Find the place where to insert data
- Verify and monitor the process
The workload and thus the perceived complexity to perform a task is a function of the volume of memorized action sequences. To keep workload low, it is adviced to perform a mission task analysis as the starting point of the design process. This will enable pilots to access functions easily, which are sometimes not directly implemented in FMS, for example Descent to crossing restriction, Change of departure runway etc. Pilots are well trained for tasks in the pattern "aviate / navigate / communicate" and "manual / tactical / strategical control of the aircraft". Still, these patterns hardly appear as a visual breakdown in FMS.
Links and Articles
-
Laws of UX is a collection of short introductions to UX laws and linking to further references
-
The Layouts of Tomorrow Grid based approach that Windows 10 uses (and used to use more)
-
How can I allow users to easily pair items from long lists? - Stack Exchange
Spacial Orientation
Web
-
Designing Game Controls Not purely about controls, but also about human attention space and other psychologic aspects (see Books Game feel)
-
No design Link collection for developers with little design skills
References
- Designing user-interfaces for the cockpit: Five common design errors and how to avoid them (Lance Sherry, Peter Polson, Michael Feary)
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For the avoidance of doubt, this Section 4 supplements and does not replace Your obligations under this Public License where the Licensed Rights include other Copyright and Similar Rights.
Section 5 – Disclaimer of Warranties and Limitation of Liability.
a. Unless otherwise separately undertaken by the Licensor, to the extent possible, the Licensor offers the Licensed Material as-is and as-available, and makes no representations or warranties of any kind concerning the Licensed Material, whether express, implied, statutory, or other. This includes, without limitation, warranties of title, merchantability, fitness for a particular purpose, non-infringement, absence of latent or other defects, accuracy, or the presence or absence of errors, whether or not known or discoverable. Where disclaimers of warranties are not allowed in full or in part, this disclaimer may not apply to You.
b. To the extent possible, in no event will the Licensor be liable to You on any legal theory (including, without limitation, negligence) or otherwise for any direct, special, indirect, incidental, consequential, punitive, exemplary, or other losses, costs, expenses, or damages arising out of this Public License or use of the Licensed Material, even if the Licensor has been advised of the possibility of such losses, costs, expenses, or damages. Where a limitation of liability is not allowed in full or in part, this limitation may not apply to You.
c. The disclaimer of warranties and limitation of liability provided above shall be interpreted in a manner that, to the extent possible, most closely approximates an absolute disclaimer and waiver of all liability.
Section 6 – Term and Termination.
a. This Public License applies for the term of the Copyright and Similar Rights licensed here. However, if You fail to comply with this Public License, then Your rights under this Public License terminate automatically.
b. Where Your right to use the Licensed Material has terminated under Section 6(a), it reinstates:
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automatically as of the date the violation is cured, provided it is cured within 30 days of Your discovery of the violation; or
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upon express reinstatement by the Licensor.
For the avoidance of doubt, this Section 6(b) does not affect any right the Licensor may have to seek remedies for Your violations of this Public License.
c. For the avoidance of doubt, the Licensor may also offer the Licensed Material under separate terms or conditions or stop distributing the Licensed Material at any time; however, doing so will not terminate this Public License.
d. Sections 1, 5, 6, 7, and 8 survive termination of this Public License.
Section 7 – Other Terms and Conditions.
a. The Licensor shall not be bound by any additional or different terms or conditions communicated by You unless expressly agreed.
b. Any arrangements, understandings, or agreements regarding the Licensed Material not stated herein are separate from and independent of the terms and conditions of this Public License.
Section 8 – Interpretation.
a. For the avoidance of doubt, this Public License does not, and shall not be interpreted to, reduce, limit, restrict, or impose conditions on any use of the Licensed Material that could lawfully be made without permission under this Public License.
b. To the extent possible, if any provision of this Public License is deemed unenforceable, it shall be automatically reformed to the minimum extent necessary to make it enforceable. If the provision cannot be reformed, it shall be severed from this Public License without affecting the enforceability of the remaining terms and conditions.
c. No term or condition of this Public License will be waived and no failure to comply consented to unless expressly agreed to by the Licensor.
d. Nothing in this Public License constitutes or may be interpreted as a limitation upon, or waiver of, any privileges and immunities that apply to the Licensor or You, including from the legal processes of any jurisdiction or authority.
Creative Commons is not a party to its public licenses. Notwithstanding, Creative Commons may elect to apply one of its public licenses to material it publishes and in those instances will be considered the “Licensor.” Except for the limited purpose of indicating that material is shared under a Creative Commons public license or as otherwise permitted by the Creative Commons policies published at creativecommons.org/policies, Creative Commons does not authorize the use of the trademark “Creative Commons” or any other trademark or logo of Creative Commons without its prior written consent including, without limitation, in connection with any unauthorized modifications to any of its public licenses or any other arrangements, understandings, or agreements concerning use of licensed material. For the avoidance of doubt, this paragraph does not form part of the public licenses.
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