Trying ChatGPT as a professional software developer

We are a company of software developers that does not sell a product but provides a wide range of services. Our primary service is developing individual software or maintaining existing software for our customers.

Most of us are polyglot developers each sufficiently fluent in a couple of languages. While I see this as a strength it also means that I do not know the idiomatic solution for a task in all ecosystems in use in our projects by heart.

A few days ago I had a remote-pair-programming session with one of our customers and we wondered how to idiomatically trim certain characters from a string in JavaScript. My customer came up with the idea of asking ChatGPT for a solution while I would have asked Google or stackoverflow.

Being curious we took the ChatGPT route and it delivered a correct solution after I clarified what I mean with “trim”:

function trimCharacterFromStartAndEnd(str, char) {
  // Create a regular expression to match the specified character at the beginning and end of the string
  const regex = new RegExp(`^${char}+|${char}+$`, 'g');
  
  // Use the replace() function to remove the character from the start and end of the string
  const trimmedStr = str.replace(regex, '');
  
  return trimmedStr;
}

// Example usage
const originalString = '###Hello World!###';
const trimmedString = trimCharacterFromStartAndEnd(originalString, '#');
console.log(trimmedString); // Output: Hello World!

But from a professional perspective the code was not simple, concise and idiomatic. I intuitively knew there must be a better way.

So I did what ChatGPT does best: I chatted with it to improve the solution to arrive at a solution a was satisfied with:

function trimCharacterFromStartAndEnd(str, char) {
  return str.replace(/^${char}+|${char}+$/g, '');
}

// Example usage
const originalString = '###Hello World!###';
const trimmedString = trimCharacterFromStartAndEnd(originalString, '#');
console.log(trimmedString); // Output: Hello World!

However, you possibly need to handle regex special characters like '.', '*' etc. if they can part of your characters to trim.

Some of the intermediate steps also have their uses depending on the needed flexibility. See the full conversation at trim character from string chat.

Similarily, stackoverflow provides some comprehensive answers you can adapt to your specific situation.

Evaluation

Using ChatGPT can actually provide you useful results. To make the most out of it, you have to be able to judge the solution provided by the AI and try to push it in the wanted direction.

After my experiment our students got the inofficial advice that their solutions should not be worse than what ChatGPT delivers. 😀

Arriving at a good solution was not faster or easier than the traditional developers’ approach using Google and/or stackoverflow. Nevertheless it was more interactive, more fun and most importantly it worked.

It was a bit disappointing to lose context at some points in the conversation, with the g-flag for example. Also the “shortest” solution is longer than the variant with the regex-literal, so strictly speaking ChatGPT’s answer is wrong…

I will not radically change my style of work and jump on the AI-hype-train but I plan to continue experimenting with it every now and then.

ChatGPT and friends certainly have some potential depending on the use case but still require a competent human to judge and check the results.

My biggest decision as a business owner (yet)

This week, a very fortunate event will take at our company: We all come together to have a summer party in person. This will be the first time in nearly 3 and a half years that we all spend time in the same room. It will be the conclusion of a decision that I call the “biggest one” that I had to come to. This is the very shortened story of that decision.

The end of an era

Our company was founded and set up as a place for direct interaction and short communication distances. We favored office workplaces and open space room plans and often visited customers at their location.

In March 2020, this setup appeared to be the exact opposite of what is advised. I remember the week from the 9th to the 13th March, when every day and every hour, things got worse and more restricted due to the Sars-Cov2 pandemic. On Friday, the 13th of March 2020, I was in a phone call with an employee that lasted 30 minutes. When we began to speak, one federal state had closed the schools. When we stopped, every school was closed in the whole country.

During the weekend, I tried to approach the situation with plans and lists. A list of endangered projects, a list of endangered customers, a list of endangered employees, a list of critical tasks, a plan to stay ahead of circumstances. I came up with a scheme to assess the risk and derive actions, but spent the whole sunday to talk with my employees just to gather some of the information necessary to base any decision on more than fear and hope. I am very grateful that my employees all picked up the phone and went through my questions with me. It helped me to realize that no matter how fitting the lists, how clever the plan, I won’t be able to process the information with the required speed.

Some employees offered to go on holiday to take moving parts out of the equation, but it was still overwhelming. If you know the feeling in a roller coaster when a certain “feel-good” speed limit is exceeded and real fear takes hold of your heart and head, you can imagine how these days felt for me.

The beginning of a different era

And then, on Monday morning, I knew exactly what to do. The situation necessitates that we change everything at the company at once. We need to go “virtual”, to retreat into home offices that didn’t exist yet.

Monday, 16th of March was the last day that several people were in our office simultaneously for a long time.

Everything the company was used to do didn’t work anymore. We had to buy new hardware, new furniture, new chairs and everything else that was needed in the home offices. We had to examine every business process and partition it into “on site” and “remote” work steps. We had to introduce new means of communication in the company and with our customers. We had to continue with our project work while transforming everything in our professional and our private lifes. We had to keep up our spirits while experiencing isolation and uncertainty.

And just like that, we replaced the “pre-covid” company with the “during-covid” company. Nobody could say that it would work. Nobody knew how long it would be required to work. Nobody could anticipate how much it would cost us.

The decision

The only thing I was certain of was that if we need to change, we would do it wholeheartedly. I was sure that even if the pandemic suddenly disappears, I don’t want to look back at that time and think of it as a makeshift solution.

My decision was to embrace the uncertainty and let go of any remnant of a masterplan that I might have left. I “jumped into the fog”.

For me, it felt as if I placed a wager on the existence of the whole company: “I bet we can do what we did for twenty years, but totally different and in a time of crisis. And we can start right now and keep going for an indeterminate period of time”.

The outcome

Since then, a long time has passed. The fog has cleared and we have survived. And not only that. The “gamble” has paid off:

We resumed our project work within two days and steadily improved our situation day by day and week by week. Our revenue went up, our productivity went up, our profits went up. New customers called us, new projects were started. Today, we are in a much better place than before.

But that’s not all: We have established new means of collaboration and communication, regardless of workplace. Every employee has a full-fledged home office with as many monitors as are physically possible, fitting furniture, a good webcam, good audio equipment, a powerful notebook or desktop computer and all the accessories that make the difference between “a workplace” and “my own workplace”. So we are fully equipped for any future isolation event that hopefully never comes.

Making the decision, trusting my employees and providing them with the equipment to master the challenge yielded the best outcome I could have hoped for. The whole experience humbled me: I lost any control over the situation early on and it didn’t really matter. What mattered was to keep innovating, investing and improving. And that is a group effort, not the vision of a single mind.

The future

So, here we are, at the natural end of the story. If this was a movie, the credits would begin to roll when we raise our glasses to celebrate our success. To me, it seems that lots of companies operate like this. “The temporarily embarrassing loss of control of upper management is past, now return to the office and commence the old rituals. And don’t forget to bring in that notebook that we borrowed you for your kitchen table home office.”

I’ve seen the potential of this transformation way too clearly to go back. There is nothing gained by reverting to the old ways. We will continue as a “hybrid” company with an attractive office and equally attractive home offices. We will continue to find ways to collaborate with each other and our customers that we didn’t think of before. We will continue to spend time, effort and money to improve our work reality. It might cost 15k euros to equip one workplace in the office and 15k euros more to do it again at home, but that money is the best investment I can think of. The return on investment is amazing.

I witnessed it firsthand.

JSON Web Token (JWT) and Security

General

JWT is an open standard for transmitting information as a JSON object. The most common scenario is authorization.

Unfortunately, the token keeps cropping up in connection with the security vulnerability. For example, it is mentioned in the OWASP top ten under the item “Broken Access Control”. In the following, I would like to briefly explain the JWT and point out a few risks when using it.

The token consists of three parts: the header, payload, and signature. Each part has been encoded with Base64Url, and all parts are joined together, separated by dots.

The type of the token and the signing algorithm is typically defined in the header.

{
  "alg": "HS256",
  "typ": "JWT"
}

The payload contains the information that should be transmitted. In cases of authorization, the user and permissions. It is also possible to define token metadata, like an expiration time. Such information must be checked by the developer. The token itself has no expiration.

{
  "exp": 1516242622,
  "name": "Max Mustermann",
  "admin": true
}

The signature take the encoded header, the encodes payload and a secret and encode it with the algorithm defined in header.

HMACSHA256(
  base64UrlEncode(header) + "." +
  base64UrlEncode(payload),
  secret)

In the authorization scenario, the token is requested from the client and created by the authorization server. The client uses the token to authorize a resource server. Therefore, the token is sent in the authorization header using the bearer schema.

Security Issues

JWT has a lot of attack surfaces, like the None Hashing Algorithm, ECDSA “Psychic Signatures”, Weak HMAC Keys, HMAC vs Public Key Confusion, Attacker Provided Public Key and the plaintext transmitting of the payload. All in all, JWT is vulnerable to replaying or tampering. Especially if the secret is not strong, the token does not expire, or no signature is used at all.

In the following, I will take a closer look at the none hashing algorithm issue as an example:

JWT allows you to set the algorithm in the header to none. So the signature part that tries to detect tampering is missing. It is just the first two parts and the point of waiting for a signature, which does not come.

eyJhbGciOiAibm9uZSIsICJ0eXAiOiAiSldUIn0K.eyJ1c2VybmFtZSI6ImFkbWluaW5pc3RyYXRvciIsImlzX2FkbWluIjp0cnVlLCJpYXQiOjE1MTYyMzkwMjIsImV4cCI6MTUxNjI0MjYyMn0.

All security precautions are already suspended, and the attacker can create his own tokens or modify intercepted ones at his leisure.

Some frameworks forbid this configuration, but in the JWT standard, it is possible. Although many applications and libraries that use JWT have disabled the option or at least tried to do so, there are still security vulnerabilities due to the configuration option. For example, because only case-sensitive “none”  was checked, settings like “None” or “NoNe” could still be used as an attack surface. So if you want to forbid this setting, it is important to do it case-insensitively.

Since this is a big problem that also occurs again and again, there is a website that counts the days since the last none algorithm problem: https://www.howmanydayssinceajwtalgnonevuln.com/.

The none algorithm is not the only attack surface on the algorithm usage. Most of the before named issues are related to the algorithm part.

How to use most secure

At best, the token should only be used once to confirm authentication and authorization. It should not be used for session management and has a short lifespan. Thus, the time span for attacks can be minimized. Also, the algorithm none option should be prevented, and a proper signature algorithm should be used. Additional information and configuration recommendations can be found under: https://jwt.io/ and OWASP cheatsheet.

Do Not Just Eat That Frog!

It is surely remarkable how much advice on Software Development is actually advice on Project Management, sometimes bordering into the psychological field and being more like management of personal Energy, Attention or Motivation. But this does make sense, considering how so often, some seemingly simple task can blow up to something difficult to manage, then becoming trivial again, then mathematically impossible, then simple again.

All of that within a context where somewhere, some customers enjoy their day, not being inclined to be part of these emotional loops at all. Just solve their problems. Which is our job.

So, one of the frequent Time Management tips passed around is “Eat That Frog” (Originally by Brian Tracy with some help from Mark Twain). The main idea is that some seriously demanding task (“having to eat a live frog”) will not become more attractive during the day, so it’s important to make it your very first priority to gulp that thing down, first thing the morning.

I found this approach quite helpful, and it can be part of a larger strategy known as “Risk First” as commonly mentioned by other authors around here.

However, any good advice can only be applied within boundaries and recently, I was dealing with several harder issues that made me refine the original thesis quite a bit.

I did not find this knowledge somewhere else, so feel free to discuss and correct me on my points of view. Not that I could be mistaken, though ¯\_(ツ)_/¯

It turns out, there are several cases where it would be straightway destructive just to Eat the next-best Frog, and I will try to explain this to you using my impressive drawing skills:

Point being, there are at least two boundaries of application:

  • Clarity of Approach: How clearly-defined is it, as opposed to requiring one or multiple experimental, creative approachs?
  • Relation to other Tasks: How isolated is your task, is it heavily interwoven with other tasks?

Why these distinctions? Maybe we can agree on

  • Overwhelming Frog tasks can act stifling on your creativity, so if that very mindset is required for your approach, you will not succeed by pressuring through.
  • Thinking yourself into a complex topic first thing in the morning might require some warm up time for your brain, booting every relevant detail into your cloud of thoughts.
  • Parkinson’s Law states “Work expands so as to fill the time available for its completion.” – from which I derive: If your task is too large but it could be divided into sub-tasks, you might use any available time to do something related to your giant Frog, but not necessarily the most precise thing to do.
  • The motivation of having done multiple small tasks can provide you with the energy of finishing “That Frog” within the near future.

So to relate that to the Frogophage subject at hand; my findings are:

  • Bottom Right: If your task is quite isolated from other tasks, but still it’s approach isn’t very clear, do not think of your problem as a frog to be eaten right now. You will have to eventually have eaten it, but take your time, don’t choke on it – don’t destroy your creative thinking by believing that you can rush through it.
  • Top Left: If your Frog is defined as one well-defined task, but can actually be seen as a composition of many Sub-Frogs, stop for a minute and invest your time in actually resolving the atomic issues. This might feel like slowing you down, but there is no honor in having eaten That Disgusting Frog, if actually you could have eaten a tasty buffet of small snacks instead.
  • Top Right: Interwoven Tasks that also require an Experimental Approach are hard because you might just waste your time trying to upfront define your smaller snacks, and you might not have all the relevant information booted into your brain at the time of your supposed Frog Breakfast, so: Try to warm up yourself by solving some smaller of the connected issues first; by bringing your consciousness into the right state it can very well appear what can be tried.
    • Bonus Point: It can also render your whole Frog irrelevant when it becomes clear that your whole problem has to be redefined by Customer Intervention. Sometimes you just have to explain the poor guys that something is complicated (costly for them), and they might come up with a request that is completely different from your original frog.
  • Bottom Left: However, if none of thse apply and there’s just a nauseating thing in front of you, that you just know has to be done, you have somewhat of a clear idea how to start, it does not depend on many other things done first or simultaneously – better Eat That Frog. It likely won’t go away and you can then use the resulting feel-good moment to inspire the rest of your day.
Conclusion

I guess this all boils down to “whatever advice there is, there are some limits to its applications”. I hope you already weren’t the type of person who would just think of any problem as some big unquestionable Frog to be gobbled up without reconsideration…

… but nonetheless, maybe this can help in evaluating your strategy when facing the next difficult thing.

And don’t just eat frogs, please.

Finding refactoring candidates using reflection

If some of your types are always used together, that is probably a sign that you are missing an abstraction that bundles them. For example, if I always see the types Rectangle and Color together, it’s probably a good idea to create a ColoredRectangle class that combines the two. However, these patterns tend to emerge over time, so it’s hard to actually find them manually.

Reflection can help find these relationships between types. For example, you can look at all the function/method parameter lists in your code and mark all types appearing there as ‘being used together’. Then count how often these tuples appear, and you might have a good candidate for refactoring.

Here’s how to do that in C#. First pick a few assemblies you want to analyze. One way to get them is using Assembly.GetAssembly(typeof(SomeTypeFromYourAssembly)). Then get all the methods from all the types:

IEnumerable<MethodInfo> GetParameterTypesOfAllMethods(IEnumerable<Assembly> assemblies)
{
  var flags = BindingFlags.Instance | BindingFlags.Static | BindingFlags.Public
    | BindingFlags.NonPublic | BindingFlags.DeclaredOnly;
  foreach (var assembly in assemblies)
  {
    foreach (var type in assembly.GetTypes())
    {
      foreach (var method in type.GetMethods(flags))
      {
        yield return method;
      }
    }
  }
}

The flags are important: the default will not include NonPublic and DeclaredOnly. Without those, the code will not report private methods but give you methods from base classes that we do not want here.

Now this is where things become a little more muddy, and specific to your application. I am skipping generated methods with “IsSpecialName”, and then I’m only looking at non-generic class parameters:

foreach (var method in GetParameterTypesOfAllMethods(assemblies))
{
  if (method.IsSpecialName)
    continue;

  var parameterList = method.GetParameters();

  var candidates = parameterList
      .Select(x => x.ParameterType)
      .Where(x => !x.IsGenericParameter)
      .Where(x => x.IsClass);

  /* more processing here */
}

Then I convert the types to a string using ToString() to get a nice identifier that includes filled generic parameters. I sort and join the type ids to get a key for my tuple and count the number of appearances in a Dictionary<string, int>:

var candidateNames = candidates
    .Select(x => x.ToString())
    .OrderBy(x => x)
    .ToList();

if (candidateNames.Count <= 1)
  continue;

if (candidateNames.Any(string.IsNullOrWhiteSpace))
  continue;

var key = string.Join(",", candidateNames);

if (!lookup.ContainsKey(key))
{
  lookup.Add(key, 1);
}
else
{
  lookup[key]++;
}

Once that is done, you can sort the resulting lookup, print out all the tuples, and see if there are any good candidates.

There’s much room for improvement with a method like this. For example, skipping non-class types is a pretty arbitrary choice. And you will not find new tuples built from built-in types this way. However, because those types offer very little semantic by themselves, it can be hard to correlate multiple occurrences simply by their types.

Using the File System as an Interaction Device

In a recent project, my job was to build a scientific data processing pipeline for a new algorithm that wasn’t set in stone yet. Part of my work would be to explore different mathematical formulas interactively with the customer.

My usual approach to projects is a “risk first” strategy. I try to identify the riskiest or most demanding part of the project and deal with it first. This approach essentially resembles the “fail fast” mindset, just that we haven’t failed yet.

In the case of the calculation pipeline, the riskiest part and at the same time the functionality that matters to the customer most, was the pipeline itself. If we were able to implement a system that can transform the given entry data into the desired results, we had an end-to-end prototype and the means to explore different mathematical approaches.

The pipeline consists of different steps that can be described as a complex transformation each. The first step/transformation takes a proprietary data format file and converts it into a big JSON file. The main effort of this step is a deep physical analysis of the data contained in the proprietary format. This analysis requires a lot of thought, exploration and work, but can be seen as a black box that the data traverses on its way from proprietary format to JSON.

The next step takes the JSON input and extracts the necessary information required by the following step. It is essentially a data reduction operation.

The third step feeds the analyzed, reduced data into the formulas and stores the calculation result.

The fourth step aggregates the calculation results into a daily time series report in a format that can be read by a spreadsheet application. This report is the end product of the pipeline and will be used to make decisions and to rule out certain environmental hazards.

The main difference of this project to virtually every project before is that I didn’t write any user interface code. The application’s main window is still blank. The whole interaction of the system with other systems that provide the entry data, of the pipeline steps among each other and with the human user is based on files in the file system.

The system periodically checks for the existence of new entry data. If some is found, it is copied in the “inbox” directory of the first step. The first step periodically checks for the existence of files in its inbox and processes them into its “outbox” that conveniently serves as the inbox of the second step. You probably get the idea by now. All the steps in the system, including the upstream data fetching routine, are actors in an file-based actor model. The files serve as messages from one actor to another. The file system and its directory structure is the common communication channel that passes the messages around.

Each processing step is an actor node with input and output storages

One advantage of this approach is that the file system viewer application of the operating system can be used as the (graphical) user interface. By opening the appropriate directories and viewing their content, the user can supervise the operating state of the system. The system can report problems by moving the incoming message not in the step’s “done” directory , but into its “failed” or “problem” directory. If several directories are on display at once, the user can follow a specific piece of data through the pipeline and view the intermediate results. For domain specific reasons, the actors in this project also have the result directory “omitted” for data that will not be processed any further because some domain rules have determined a cancellation.

An user can even manipulate the data’s flow by moving files away or into a specific directory. Let’s say that we want to calculate a certain amount of data again, we can just copy the files from the “done” directory of the first step into its “inbox” and the system will process it again.

Because the analysis step takes some time while the calculation step is surprisingly fast, we can perform just the calculation again by not moving the initial data files, but the analyzed and reduced entry files for the calculation step. Using this approach, we can try different mathematical formulas by stopping the system, swapping the calculation step with a new version, starting the system again and moving the desired entry files into its inbox.

Using the file system as an interaction device for the user and the system’s parts has many immediate advantages, but some drawbacks, too. One drawback is performance. Using the harddisk for data transfer is the slowest possible way to bring data from step X to step X+1. If your system is required to have high throughput or low latency, this approach isn’t suitable. My project has a low, forecastable throughput and a latency requirement that is measured in minutes or seconds, but not in milliseconds or even nanoseconds. It can spend some time in the filesystem, because the first step alone takes several seconds for each file.

Another drawback is a certain fragility of the communication medium, the file system. You have to account for concurrent reads, writes or even deletes. The target platform of my system (Microsoft Windows) exhibits signs of exhaustion if the amount of files in one directory grows too large. This means that your file selection, already a costly operation, becomes more costly if the systems is put under pressure. If your throughput is usually steady, which is the case in my project, this won’t be a problem. Until you manually copy 100k files in an inbox for swift recalculation and discover that the file copy process alone takes several minutes.

Of course, the system cannot operate without a graphical user interface forever. But some basic interactions with the system will probably just result in some files being copied from one directory to another one in the background.

Avoid fragmenting your configuration

Nowadays configuration often is done using environment (aka ENV) variables. They work great using docker/containers, in development and production, on all platforms and using all languages. In short I think environment variables are great for configuration of many aspects of an application.

However, I encountered a pattern in several different applications that I really dislike: Several, fragmented ENV variables for one configurable aspect of the application.

Let us have a look at two examples to see what I mean, then I will try to explain where it could come from and why I think it is bad practice. Finally I will show a better alternative – at least in my opinion.

First real world example

In one javascript app a websocket url was made configurable using 4 (!) ENV variables like this:

WS_PREFIX || "wss://";
WS_HOST || "hostname";
WS_PORT || "";
WS_PATH || "/ws";

function ConnectionString(prefix, host, port, path) {
  return {
    attrib: {
      prefix, 
      host,
      port,
      path,
    },
    string: prefix + host + port + path,
  };
}

We immediately see, that the author wrote a function to deal with the complex configuration in the rest of the application. Not only the devops team or administrators need to supply many ENV variables but they have to supply them in a peculiar way:

The port needs to be specified as :8888, using a leading colon (or the host needs a trailing colon…) which is more than unexpected. The alternative would be a better and more sophisticated implementation of ConnectionString…

Another real example

In the following example the code there are again three ENV variables dealing with hosts, urls and websockets. This examples feels quite convoluted, is hard to understand and definitely needs a refactoring.

TANGOGQL_SOCKET=ws://${TANGO_HOST}:5004/socket

const defaultHost = window.TANGOGQL_HOST ?? "localhost:5004";
const defaultSocketUrl = window.TANGOGQL_SOCKET ?? ws://${defaultHost}/socket;

// dealing with config peculiarities somewhere else
const socketUrl = React.useMemo(() =>
        config.host.replace(/.*:\/\//, "ws://") + "/socket"
    , [config.host]);

Discussion

The examples show clearly that something simple like a configuration for an URL can lead to complicated and hard to use solutions. Most likely the authors tried to not repeat themselves and factored the URLs into the smallest sensible components. While this may sound like a good idea it puts burden on both the developers and the devops team configuring the application.

In my opinion it would be much simpler and more usable for both parties to have complete URLs for the different use cases. Of course this could mean repeating protocols, hostnames and ports if they are the same in the different situations. But just having one or two ENV variables like

WS_URL=wss://myhost:8080/ws
HOST_URL=https://myhost:8080

would be straightforward to use in code and to be configured in the runtime environment. At the same time the chance for errors and the complexity in the configuration is reduced.

Even though certain parts of the URLs are duplicated in the configuration I highly prefer this approach over the presented real world solutions.

Useful background metrics: Distance to Disaster

This blog post would not have happened without my wife, who, upon learning that I use this metric in my everyday life, urged me to write about it.

I often categorize events that happen in my life. Due to my nature, I analyze detrimental events more thorough than things that “worked as intended”. One tool for my analysis is a measurement that I call “Distance to Disaster” (DtD). It indicates the “distance” or “bad faith work” or “bad decisions” that needs to be invested in order for disaster to happen. Let me explain:

If we wait on a train, we can stand in the middle of the platform and maximize the physical distance to the tracks before and behind us. Or we can stand right at the edge and minimize the physical distance to one track. If the track we chose for our position is the one where our train will arrive, we have a very low distance to distaster. We can lose our balance and fall onto the tracks. We can misjudge the physical dimensions of the train and get hit with something. In short: Nobody wants to wait on a train with a minimized (physical) distance to disaster.

Another measurement unit for the metric is “bad faith work”. Let’s assume you want to steal my most priced possession. That would be a disaster for me. You need to gain access to my home (step 1), then open the safe (step 2) and then find the key to the safe desposit box at my bank (no-brainer, not a step on its own). Afterwards, you need to gain access to the bank room before I recognize my loss (step 3) and open the box that has a two-lock system (step 4). It is probably easier to come up with a plan to circumvent some steps and attack the bank directly. If you just succeeded with step 1, my most priced possession is probably still very secure because a DtD of 3 is rather high.

And then, there are “bad decisions”. Let’s say you write code and accidentally hit “load” instead of “save”. If you are me in the early nineties, you just overwrote your code with an empty file. I still remember that day and it didn’t help that “save” was bound to F5 and “load” to F6. One bad decision lead to disaster.

Now imagine you still use the same shitty IDE (it was the GWBasic editor), but with modern version control. You commit early and often. You accidentally hit “load” instead of “save” and lose your last few minutes of work. Sad, but not a disaster. Even if you delete the whole file, you can restore your last commit as often as you want. Using version control adds +1 to your “bad decision distance” to disaster.

You probably understand the concept by now. You can specify what a “disaster” is and then measure your current distance to it by trying to come up with the least steps that lead to it.

In our normal everyday life, we are surprisingly often only one step away from disaster, but it never happens. That’s a reassuring reality, but shouldn’t keep us from thinking about how to increase the step count without much effort.

One typical implementation of this approach is a modest backup strategy for all data that you intend to keep. Another one is to have spare parts for crucial devices in stock (the “hardware backup”).

Don’t get me wrong: It’s not about maximizing the DtD. It’s about recognizing the cheap and easy opportunity to add one more step to the distance.

And it’s not about “disaster” in the meaning of life-altering, stop-the-world events. A “disaster” can be everything you don’t want to happen. Try to bring a reasonable distance between you and this thing if possible.

Now that you know about the concept, can you find examples of cheap and easy DtD improvements in software development? Let us know in the comments!

Addendum for my co-workers: Our ETOD metrics is the DtD metrics applied on financial resources.

And another addendum: I find a lot of similarities in the field and mindset of accident prevention. For example, airplane cockpits are designed in a way that dangerous actions require the actuation of two control elements like switches or buttons that are located on different sides of the room. Making it two buttons instead of one adds “bad decision” distance. Placing the buttons in different directions adds “intent distance”.

In software user interaction designs, we try to replicate the second button with a confirmation dialog (“Are you sure?”). It adds to the “bad decision” distance but often lacks in the “intent distance” dimension. I don’t want to be responsible for cumbersome “maximized mouse distance” dialogs, though.

Using Message Queuing Telemetry Transport (MQTT) for communication in a distributed system

If you have several participants who are interested in each other’s measurements or events, you can use the MQTT protocol for this. In the following, I will present the basics.

The Mqtt protocol is based on publish and subscribe with asynchronous communication. Therefore it can also be used in networks with high latency. It can also be operated with low bandwidth.

At the center is an MQTT broker. It receives published messages and forwards them to the subscribing clients. The MQTT topics are used for this purpose. Each message is published to a topic. The topics look like a file path and can be chosen almost freely. The only exception are names beginning with $, because these are used for MQTT-own telemetry data. An example for such a topic would be “My/Test/Topic”. Attention, the topic is case sensitive. Every level of the topic can be subscribed to. For example “My/Test/Topic/#”, “My/Test/#” or “My/#”. In the latter case, a message published to “My/Productive/Things” would also be received by the subscriber. This way you can build your own message hierarchy using the Topics.

In the picture a rough structure of the MQTT infrastructure is shown. Two clients have subscribed to a topic. If the sensor sends data to the topic, the broker forwards it to the clients. One of the clients writes the data into a database, for example, and then processes it graphically with a tool such as Grafana.

How to send messages

For the code examples I used Python with the package paho-mqtt. First, an MQTT client must be created and connected.

self.client = mqtt.Client()
self.client.connect("hostname-broker.de", 1883)
self.client.loop_start()

Afterwards, the client can send messages to the MQTT broker at any time using the publish command. A topic and the actual message are sent as payload. The payload can have any structure. For example Json format or xml. In the code example json is used

self.client.publish(topic="own/test/topic", payload=json.dumps(payload))

How to subscribe topics

Even when subscribing, an MQTT client must first be created and a connection established. However, the on_connect and on_message functions are also used here. These are always called when the client establishes a connection or a new message arrives. It makes sense to make the subscriptions in the on_connect method, since they are created so with a new connection also always new and are not lost.

self.client = mqtt.Client()
self.client.on_connect = on_connect
self.client.on_message = on_message
self.client.connect("hostname-broker.de", 1883)
self.client.loop_start()

Here you can see an example on_connect method that outputs the result code of the connection setup and subscribes to a topic. For this, only the respective topic must be specified.

def on_connect(client, userdata, flags, rc):
      print(Connected with result code " + str(rc))
      self.client.subscribe("own/test/topic/#")

In the on_message method you can specify what should happen to an incoming message.

Conclusion

MQTT is a simple way to exchange data between a variety of devices. You can customize it very much and have a lot of freedom. All messages are TSL encrypted and you can set up client authentication in the broker, which is why it is also considered secure. For asynchronous communication, this is definitely a technology to consider.

Developing for Cordova + SQLite in a standard Browser environment

As any developer, who doesn’t just love it when a product that has grown over the years suddenly needs to target a new platform (e.g. operating system) because some customer demands changed, some dependency broke or some other totally unexpected thing called “progress” happened?

Fortunately, there are some approachs to cross-platform development and if one expects such a change of direction, one can early on adopt a suitable runtime environment such as Apache Cordova or Capacitor/Ionic or similar, who all promise you a Write-Once-Run-Anywhere experience, decoupling the application logic from the lower-level OS interactions.

Unfortunately though, this promise is a total lie and usually, after starting such a totally platform-agnostic project, really soon you will want to use a dependency that will only work for one platform and then your options are limited.

One such example is a Cordova project we are currently moving from Android to iOS, and in that process also redesigning a nice, modern frontend to replace a very outdated (read: unmaintainable) Vanilla JS application. So now we have set it up smoothly (React + Vite + Typescript – you name it!), so technically we do not need anything iOS-specific yet, so we can work on our redesign in a pure-browser environment with hot reloading and the likes – life is good!

Then comes the realization that our application is quite data heavy and uses an on-device SQL database to persist its data, and we don’t have that in the browser – so, life turned bad.

What to do? There had been a client-side WebSQL database specification once, but this was unofficial and never fully implemented, abandoned in 2010, still present in Chrome but they are even live announcing how they are removing it, so this is not the future-proof way to go.

We crave a smooth flow of development.

  • It is not an option to re-build the app at every change.
  • It is not an option to have the production system use its SQLite DB and the development environment to use a totally different one like IndexedDB – certain SQLite queries are too ingrained in our application.
  • It’s only probably an option to use an experimental technology like absurd-sql, which aims to fill in that gap but then again needs advanced API features like Web Workers, SharedArrayBuffer, Atomics API which we wouldn’t require else
  • It is possible to use in-memory SQLite via sql.js but for persistence, it wasn’t instantly obvious to me how to couple that with the partially supported Origin Private File System API

So after all, this is the easiest solution that still gave me most of my developer smoothness back: Use sql.js in memory and for development, display two nice buttons on the UI which let me download the whole DB and upload one from file again. This is the sketch:

We create a CombinedDatabase class which, depending on the environment, can hand out such a database in a Singleton-like manner

class CombinedDatabase {

    // This is the Singleton-part

    private static instance: CombinedDatabase;

    public static get = async (): Promise<CombinedDatabase> => {
        if (!this.instance) {
            const {db, type} = await this.createDatabase();
            this.instance = new CombinedDatabase(db, type);
        }
        return this.instance;
    };

    private static createDatabase = async () => {
        if (inProductionEnvironment()) {
            return {
                db: createCordovaSqliteInstance(),
                type: "CordovaSqlite"
             };
        } else {
            const sqlWasmUrl = (await import("../assets/sql-wasm.wasm?url")).default;
            // we extend the window object for reasons I tell you below
            window.sqlJs = await initSqlJs({locateFile: () => sqlWasmUrl});
            const db = new window.sqlJs.Database();
            return {db, type: "InMemory"};
        }
    }


    // This is the actual flesh, i.e. a switch of which API to use

    private readonly type: string;
    private cordovaSqliteDb: SQLitePlugin.Database | null = null;
    private inMemorySqlJsDb: SqlJsDatabase | null = null;

    private constructor(db: SQLitePlugin.Database | SqlJsDatabase, type: string) {
        this.type = type;
        switch(type) {
            case "CordovaSqlite":
                this.cordovaSqliteDb = db as SQLitePlugin.Database;
                break;
            case "InMemory":
                this.inMemorySqlJsDb = db as SqlJsDatabase;
                break;
            default:
                throw Error("Invalid CombinedDatabase type: " + type);
        }
    }

   // ... and then there are some methods

}

(This is simplified – in actual, type is an enum for me , and there’s also error handling, but you know – not the point here).

This structure is nice, because you can now implement low-level methods like some executeQuery(...) etc. which just decide depending on the type, which of the private DB instances it can address, and even if they work differently, return a unified response format.

The rest of our application does not know anything about any Cordova-SQLite-dependency, or sql.js, or whatever. Life is good again.

So How do Import / Export work?

I gave the CombinedDatabase some interfacing methods, similar to


    public async export() {
        switch (this.type) {
            case "CordovaSqlite":
                throw Error("Not implemented for cordova-sqlite database");
            case "InMemorySqlJs":
                return this.inMemorySqlJsDb!.export();
            default:
                throw Error("DB not initialized, cannot export.");
        }
    }

    public async import(binaryData: Uint8Array) {
        if (this.type !== CombinedDatabaseType.InMemorySqlJs) {
            throw Error("DB import only implemented for the in-memory/sql.js database, this is a DEVELOPMENT feature!");
        }
        await this.close();
        this.inMemorySqlJsDb = new window.sqlJs.Database(binaryData);
    }

This is also the reason why I monkey-patched the window object earlier, so I still have this API around outside the Singleton instantiation (createDatabase). Yes, this is a global variable and a kind of hack, but imo is what can safely be done inside the Browser within some good measure.

Remember, in Typescript you need to declare this e.g. in some global.d.ts file

import {SqlJsStatic} from "sql.js";

declare global {
    interface Window {
        sqlJs?: SqlJsStatic
    }
}

Or go around the Window interface by casting (window as any).sqlJs – you decide what you prefer.

Anyway, the export() functionality can then be used quite handily, it returns the in-memory database as a binary array and you can make the browser download that via a Blob URL:

api.db.export().then((array: Uint8Array) => {
    const blob = new Blob([array], {type: "application/x-sqlite3"});
    const link = document.createElement("a");
    link.href = URL.createObjectURL(blob);
    link.download = `bonpland${Date.now()}.db`;
    link.target = "_blank";
    link.click();
});

And similarly, you can use import() by reading a Uint8Array from a temporary <input type="file"> element with a FileReader() (somewhat common solution, but just comment below if you want the details).

To be exact, I don’t even use the import() button anymore because I pass my development DB as an asset to the dev server. This is nice (and only takes a few seconds on hot reloading because our DB is like 50 MB in size), but somewhat Vite-specific, which is why I will postpone this topic to some later blog time.