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In the we took a look at , the PHP static site generator which is currently the most starred on Github. Today we’re exploring , a tool which promises to bring a Laravel-based approach to the world of PHP static site generators (SSGs). first article of the series Sculpin Jigsaw I’m gonna be honest with you — I’m not the biggest Laravel user. I appreciate what it’s done for PHP, and how it has helped push forward the world of PHP development in a time where older frameworks were struggling to keep up with innovations coming from other platforms. It’s also a prime example of the good kind of cross pollination happening in the PHP world: it employs packages from the Symfony world, The PHP League, Doctrine, and more. It’s a good lesson in building something cool on top of great foundations, without having to continuously reinvent the wheel. Overall, I think that Laravel is an excellent framework, but I’m definitely inexperienced with it. If you think I have overlooked or misjudged something (both Laravel and Jigsaw-related), please feel free to reach out to me on Twitter: constructive criticism is always welcome! Jigsaw (~900★) Just like I did with Sculpin, I’ll jump straight into the action, so let’s create a sample project and play with it! We’ll open the and start from there. official docs Unlike Sculpin, Jigsaw doesn’t provide a skeleton project we can use as quickstart. Instead, we must create a normal project, add as dependency, and use its CLI: tightenco/jigsaw mkdir jigsaw-example && cd jigsaw-examplecomposer require tightenco/jigsaw./vendor/bin/jigsaw init Let’s go through the default directory structure that was just generated. In the top level directory, we have a with this code: config.php <?phpreturn [    'baseUrl' => '',    'production' => false,    'collections' => [],]; I’m not sure yet what this means, but having a configuration file clearly placed seems like a good approach 👍. The second PHP file is called , and it’s empty (only some commented-out code), but it hints at how we could use the event system at some point. bootstrap.php We also have Javascript dependencies. I see a , which lets me know that is being used. So I run and in the meantime I’ll explore the docs to try to understand a bit more of what I’m doing 😉. webpack.mix.js Laravel Mix npm install About 10 dependencies and 300MB in later, we’re back. Now, let’s try to build our site. It appears we have 2 ways of doing so: we can use the Jigsaw CLI to build and then serve, or use npm and its live reload capabilities provided by Browsersync: node_modules # With Jigsaw CLI./vendor/bin/jigsaw build./vendor/bin/jigsaw serve # localhost:8000# With npmnpm run watch # localhost:3000 Regardless, both work and you get this! Naturally, only John Oliver can really convey my reaction to this page. The directory structure Now let’s explore the skeleton project that was generated earlier. The order in which we’re exploring parts of the project might appear to be random because, well, it is. That’s the cool thing about discovering something new, right? The exploratory phase, where you peek at this, take a look at that, and oh, a directory! What lies therein? source Being a Laravel-based project, I’m not surprised to find an file, which contains the shiny from above. The directive hints to me that I should go look in the directory for a template, and lo and behold, there it is. Everything seems nice and tidy with the templates, let’s go check how assets are handled. index.blade.php Hello world! @extends('_layouts.master') _layouts master.blade.php Assets and configuration Laravel Mix provides out of the box support for Sass, so is your starting point. SCSS might not be the latest and shiniest thing on the CSS landscape, but it’s battle-tested and definitely gets the job done, so I approve of its inclusion. Let’s turn that page into something that will get your attention source/_assets/sass/main.scss /* source/_assets/sass/main.scss */$bg-color: red;body {  background-color: $bg-color;} Let’s hit save and webpack should do its magic and turn our background red, right? Yes, it does! I’ll spare you the screenshot for your eyes’ sake, and now let’s continue our exploration. I’d like to set up a basic blog, with posts written in Markdown files. To do that, let’s introduce the concept of , which, as the docs state, . Sounds about right for a blog. Remember the file from earlier? Let’s tweak it to tell Jigsaw about our collection of blog posts: collections give you the ability to access your content at an aggregate level config.php <?phpreturn [    'baseUrl' => '',    'production' => false,    'collections' => [        'posts' => [            'path' => 'blog/{date|Y-m-d}/{filename}',        ],    ],]; Jigsaw will look for the corresponding directory for every collection we define. In our example, will become , so in that directory let’s create a blog post to show our love for one of the greatest songs of all times. posts source/_posts ---extends: _layouts.posttitle: The Fresh Princeauthor: Will Smithdate: 1990-09-10section: content--- Now this is a story all about howMy life got flipped-turned upside downAnd I'd like to take a minuteJust sit right thereI'll tell you how I became the prince of a town called Bel-Air Let’s save this file as , and then let’s create the appropriate template as specified in the part of the front matter: . the-fresh-prince.md extends source/_layouts/post.blade.php @extends('_layouts.master')@section('body')<h1></h1>    <p>By  - </p>    @yield('content')@endsection Let’s run , and we’ll have a nice directory generated with our shiny website, so let’s open the URL (which we still have to build ourselves) and… It works! ./vendor/bin/jigsaw build build_local (Author’s note: at this point I would like to add more GIFs, but I have to keep it professional. Let’s all just pretend to have a GIF of Jake Peralta saying , thank you.) noice Is Jigsaw Contentful-ready? We’ve covered some of the basics, so now the million-dollar question: is Jigsaw Contentful-ready? With this, of course, I mean how easily content stored in Contentful can be integrated in a Jigsaw-powered website. We open the , and with that page open in the tab, we can give this a try. Remember ? It contained some commented-out code which hinted at how events work, so let’s reopen that: documentation page about event listeners bootstrap.php <?phpuse TightenCo\Jigsaw\Jigsaw;/** @var $container \Illuminate\Container\Container *//** @var $events \TightenCo\Jigsaw\Events\EventBus *//*** You can run custom code at different stages of the build process by* listening to the 'beforeBuild', 'afterCollections', and 'afterBuild' events.** For example:** $events->beforeBuild(function (Jigsaw $jigsaw) {*     // Your code here* });*/ Ok, seems to be reasonably easy. As extra help, after some googling I found an about creating a sitemap with Jigsaw, and the original for the events feature, so I have enough to figure this out. Let’s and hack this thing together! article pull request composer require contentful/contentful // In bootstrap.phprequire_once 'contentful_fetcher.php';$events->beforeBuild(ContentfulFetcher::class);// In contentful_fetcher.phpuse Contentful\Delivery\Client;use Contentful\Delivery\Resource\Entry;use TightenCo\Jigsaw\Jigsaw;class ContentfulFetcher{    /**     * Jigsaw requires either a callable or the name of     * a class which implements a method called "handle"     *     * @param Jigsaw $jigsaw     */    public function handle(Jigsaw $jigsaw): void    {       // Let's only build for production        if ($jigsaw->getEnvironment() === 'local') {            return;        }        $client = $this->getClient($jigsaw);        foreach ($jigsaw->getCollections() as $collection) {            $this->cleanSourceDir($jigsaw, $collection);            $entries = $this->getPlainEntries($client, $collection);            foreach ($entries as $entry) {                $this->writeEntryToMarkdownFile($jigsaw, $entry, $collection);            }        }    }    private function getClient(Jigsaw $jigsaw): Client    {        return new Client(            $jigsaw->getConfig('contentful.accessToken'),            $jigsaw->getConfig('contentful.spaceId')        );     }    /**     * Before every run, we remove the previous contents of the source directory.     */    private function cleanSourceDir(Jigsaw $jigsaw, string $collection): void    {        $dir = $jigsaw->getSourcePath().'/_'.$collection;        $jigsaw->getFilesystem()->deleteDirectory($dir, true);    }    /**     * We transform objects of type Contentful\Delivery\Resource\Entry     * into plain arrays for ease of use later on.     */    private function getPlainEntries(Client $client, string $collection): array    {        // Convention:        // Every defined collection corresponds to a content type ID in Contentful        $query = (new Contentful\Delivery\Query())            ->setContentType($collection)        ;        $entries = $client->getEntries($query);        if (!count($entries)) {            return [];        }        /** @var Contentful\Delivery\Resource\ContentType $contentType */        $contentType = $entries[0]->getContentType();        return \array_map(function (Entry $entry) use ($contentType) {            // Convention:            // The content types may contain a field called body,            // which will be used as the markdown content of the generated file,            // so we give it a default value            $plainEntry = [                'id' => $entry->getId(),                'body' => '',            ];            foreach ($contentType->getFields() as $field) {                $plainEntry[$field->getId()] = $entry->get($field->getId());            }            return $plainEntry;        }, $entries->getItems());    }    /**     * Converts an entry into a markdown file and writes it to disk.     */    private function writeEntryToMarkdownFile(Jigsaw $jigsaw, array $entry, string $collection): void    {        $contents = '---extends: _layouts.'.$collection.'section: content';        $body = '';        foreach ($entry as $field => $value) {            if ($field === 'body') {                $body = $value;                continue;            }            $contents .= $field.': '.$value."\n";        }        $contents .= '---'."\n\n".$body;        $path = sprintf('_%s/%s.md', $collection, $entry['id']);        $jigsaw->writeSourceFile($path, $contents);    }} This code is more of a proof of concept than complete implementation (it relies a lot on conventions, and it lacks handling of special fields such as locations, links, etc); however, it should get the job done for a basic example. First of all, we pass a fully-qualified class name (FQCN) to , and Jigsaw will know that it must create an instance of that class and execute the method of it. Truth be told, I think there should be an interface in order to have a stronger contract, something like this: $events->beforeBuild() handle namespace TightenCo\Jigsaw;use TightenCo\Jigsaw\Jigsaw;interface EventHandlerInterface{    public function handle(Jigsaw $jigsaw);} Or perhaps just requiring any valid callable (thus including objects implementing ). It works now in its present state but I like strong contracts, and you should know by now that I'm picky—it's in the title of the series! __invoke This is an overview of what actually does: ContentfulFetcher If the environment is detected, the whole process will be stopped. This is done to avoid the performance impact due to having to fetch all data from Contentful on every build (which can likely be very often, if running on watch mode). The idea is to run a initially to fetch all content, and then operate with what’s been stored locally. Of course, a good idea would be to add the generated files to the local , to avoid keeping them in version control (content doesn't belong there). local ./vendor/bin/jigsaw build production .gitignore We create an instance of a client object using the Contentful Delivery SDK for PHP. We iterate through all the defined collections, and we use a convention to map a local collection to a content type ID in Contentful. We then clean the corresponding directory, where we will dump the generated files. We fetch entries for the given content type, and we use the object to get a list of fields. With those fields, we build the appropriate YAML front matter section, and then we add the body at the end (string handling here is very basic and could be improved). Contentful\Delivery\Resource\ContentType We finally dump the contents of the generated file. We use the Contentful ID to save them, as we can define a pretty URL when configuring the collection. There’s a lot of gluing going on, but it works on my machine™️. This could be done a thousand times better, with more flexible configuration, but as a proof of concept I’m reasonably satisfied with it. Verdict Before our final verdict, I think it’s only fair to mention that during the process of writing this article, I experienced a couple of issues which have since been fixed. Before publishing, I got in touch with (one of the people behind Jigsaw) and explained that I was experiencing some difficulties with the handling of assets and events (misconfiguration for the former, and lack of docs for the latter). Over the course of a weekend, both issues have been fixed 👏 Matt Stauffer I quite like Jigsaw, but it’s rather barebones in its out-of-the-box configuration. Unlike Sculpin, it makes no assumption over what kind of use you’ll have for it, which is a double-edged sword: it avoids clutter and gives you complete control, but it also creates a higher barrier of entry for simple use cases such as blog. To solve this issue, Matt revealed to me that they’re building a generator with website skeletons, to address the most common needs (such as a blog, a documentation website, etc), with a to track progress. He also mentioned that they just launched a new , which I encourage you to check out. Github issue showcase of websites built with Jigsaw As a non-Laravel developer, I was afraid that Jigsaw would be difficult to pick up and use, but it definitely wasn’t the case. It is actively being developed (the events system was added just a few months ago) and is on track to quickly become the most popular PHP static site generator, in terms of stars on Github. It provides very good defaults, and assets are preconfigured to use a modern stack (Sass for CSS, and webpack with Babel for JS). The only real criticisms I can make are actually the same as when I discussed Sculpin: content and presentation (assets and templates) could be more separate; instead, they belong to the same directory, and I would love to be able to have a more defined structure for collections, instead of relying exclusively on the YAML bit before the actual Markdown contents. source Next article will be about , which describes itself as a documentation generator. Stay tuned! Couscous Originally published at www.contentful.com on August 1, 2018.

An extremely picky developer’s take on static site generators for PHP: Part 2 — Jigsaw

My interview with Keith Damiani, Senior Developer at Tighten and Lead Developer on the Jigsaw project. Developed by the team at , is a Static Site Generator that utilises components from the framework for building static websites. Tighten Jigsaw Laravel As part of some research I did into (this was originally part of a university project that I’ve turned into a ), I reached out to , a Senior Developer at , who is also the lead on the Jigsaw project. Jigsaw blog post! Keith Damiani Tighten Keith was kind enough to answer a few of my question regarding the development of Jigsaw and the plans for the future. Here’s what he had to say… RW: Can you please introduce yourself and tell me about your background and your involvement with Jigsaw? KD: I’m a Senior Developer at Tighten, a fully-remote web consultancy based out of Chicago. I live in Charlottesville, VA, and am relatively new to programming, having spent 20 years running a graphic design agency prior to joining Tighten. I’m the lead developer on Jigsaw, taking over from Adam Wathan (who originally wrote Jigsaw while at Tighten) after he left. RW: What was the main motivation for developing Jigsaw? Is it simply a byproduct of a Tighten project, or is it something that you/Matt/Tighten specifically wanted to develop? KD: It definitely had humble beginnings; originally, it was designed purely for internal use, mainly to power our own site. I’d have to ask Adam about his motivation, but I suspect he took a look at the Ruby world, as he often does, and thought it would be nice to have something like Jekyll for the PHP/Laravel world, leveraging Blade’s compiler engine. RW: Is their anything that makes Jigsaw particularly different from other static site generators? Although you might be biased, what sets Jigsaw apart from other products? KD: It’s definitely targeted at developers who are comfortable in the Laravel ecosystem, as it draws so heavily on Blade; so for someone who writes Laravel (or even PHP) all day, it’s a natural choice that involves a pretty short learning curve to get up and running. Blade example, taken from https://jigsaw.tighten.co/ RW: Were there any specific or difficult technical challenges that you had to solve during the development of Jigsaw? KD: The original version had no concept of “collections,” and adding that was a bit of a challenge because it essentially requires processing every page twice (to enable one page to reference another, e.g. in a sidebar menu). Recently, I’ve been working on optimizing the build process to be as efficient (and fast) as possible — particularly for large sites — which has involved digging into the guts of the Blade engine to figure out how to add support for caching. More generally, it’s been a challenge to stretch Jigsaw’s abilities beyond what it was originally intended for, because at its origin it was as a one-trick pony: spin through a bunch of Markdown files and build static HTML using Blade. There are definitely times when this core concept becomes a constraint on what we can do; and as we continue to add features that stretch the limits of what the Blade engine can pull off, the Jigsaw codebase will get so Frankenstein-y that it might be worth a full rewrite :) RW: Regarding the code base, have you been able to leverage many exiting packages and Laravel components or has it been a case of building a lot of things from scratch? KD: Because of its reliance on Blade as its backbone, and the fact that it was written and is maintained by a bunch of Laravel devs, it definitely takes advantage of a lot of Laravel (and Symfony) goodness. In addition to Blade, it relies heavily on Collections, the Laravel container, and the Symfony console component. RW: What do you see as the ideal use case for Jigsaw? Simple blogs? Websites? Have you seen any interesting applications of Jigsaw? KD: It was definitely originally designed for a simple site (not even a blog, before the collections support was added), but as it has grown, we’ve seen all sorts of interesting uses. People have used it to consume remote API-based CMS content (using services like Contentful), one developer has built an entire on top of Jigsaw. A few devs we know have very large sites (with 6,000+ pages) that really stretch the abilities of what was originally a very simple static site generator. But the 90% use-case, and what we think Jigsaw is well-suited for, are blogs, documentation sites, and traditional marketing-type sites (like our own). We created builtwithjigsaw.com to collect some of these great examples. HTML-email framework https://builtwithjigsaw.com/ RW: Is Jigsaw aimed at a specific ‘type’ of developer? For example, is it important to keep it simple to use in order to keep the barrier to entry fairly low for lesser experienced developers? KD: It’s definitely targeted at (1) someone who’s comfortable in Laravel, and (2) someone who’s comfortable on the command line. As it has grown, though, and the audience has become broader, it is a little tricky to balance the desire to add more complicated features, while maintaining a low barrier to entry. Ideally, Jigsaw will always be easy to get started with for a less experienced developer, but robust and extensible enough for advanced developers to continue doing and innovative things with. creative RW: What’s the future of Jigsaw? Are their any exciting features that you are working on at the minute or plan to add? KD: We’re wrapping up of support for starter templates, including two beautiful Tighten-developed ones that will be built-in — one for a blog, one for documentation sites — as well as the ability for third parties to build their own for people to use. Again, the goal here is to make it really simple to get a great site up and running quickly: or and you’re ready to go. The optimization stuff is pretty exciting, at least for those who maintain large sites, as it cuts down build times by about 75%. Beyond this, we have plans to continue building features that allow users to hook in to external API-based CMS’s, and soon I reallllly want to add support for internationalization, which we’ve had many requests for from day 1. development jigsaw init blog jigsaw init docs RW: Following on from that, I personally love the simplicity of Jigsaw, but are there any plans to introduce a ‘plugin’ ecosystem, admin interface, or anything like that? KD: Yes and no; the starter templates are a first step toward extensibility, and we’re looking at ways for people to build reusable plugins for things like commonly-used helper methods. We added support for events to provide hooks for people to run arbitrary code before or after a build, and the file is there to let advanced developers accomplish almost anything they want…but it would be nice to make this more accessible for less-experienced developers, and to allow everyone to take advantage of some of the great ideas in the community. I don’t expect we’ll ever add any kind of admin interface, it’ll always be command-line based (primarily because that’s how we like to work 😊 ) bootstrap.php RW: Anything else exciting or interesting to tell me about Jigsaw? KD: It has been a really fun open source project to work on, precisely because of the way it has grown beyond its original use-case; it was thrown out to the world as something quite simple and limited in functionality, and grew organically as users (including ourselves) came back with lots of “hey, what if Jigsaw could do X” requests. Thank you for reading! 😃 If you enjoyed it, hit that clap button below. I really appreciate your support and it helps other people see the story. I am always happy to hear from like minded people, so feel free to shoot me an email or say hello on . Twitter

Jigsaw — the Laravel Static Site Generator.

In a we essentially introduced as a Java classloader capable of loading and running classes directly from Maven repositories and resolve dependencies at runtime. Today we`ll go a little bit further in pitching as a useful versatile tool helping Java developers release, (un)install, run, and upgrade Java apps, whilst also addressing some problems that the so — called ` ` did not solve yet (as far as we are aware). previous post ModRun ModRun Project Jigsaw If you are a Java developer we don`t need to remind you about the challenges and the hassle involved when installing and running Java applications. Yes there are several models out there trying to tackle this problem, but in our opinion none of them have really succeeded in making Java application installation and launch as easy as what we ought to do with . Especially if you keep multiple servers up-to-date with the latest versions of various services. ModRun Before we proceed we`ll extend the definition of as a Java application installer/launcher/class loader that can load and run modules directly from a Maven repository. Another way to picture ModRun is as NPM or RPM just for Java apps. Now that we have extended the definition of ModRun, let us share with you how we plan to solve the following problems over coming weeks/months as the project matures: ModRun Release of Java applications. Installation of Java applications from remote repositories. Running of Java applications stored in a local Maven repository. Upgrading Java applications. Uninstalling Java applications. Release of Java Applications Since ModRun can download applications directly from Maven repositories, all a developer needs to do to release a Java application is to publish its Maven artifact (JAR file) to a Maven repository. ModRun can download it from there, resolve its dependencies and download them, too. Publishing an application to a Maven repository makes the release very standardised and small. Developers only have to upload their application’s JAR file, assuming that all dependencies are already stored in the Maven repository. Installation of Java Applications As mentioned already, ModRun will be able to download application’s JAR files directly from a Maven repository. ModRun stores the JAR files locally in what corresponds to a local Maven repository (the same directory structure and location of JAR and POM files). This makes installation of applications and their dependencies pretty standardised. Keeping application JAR files and their dependencies in a local Maven repository structure makes it easy to have multiple versions of an application installed at the same time. Running Java Applications Once a Java application’s JAR file is located in the local Maven repository structure, ModRun can load and run the application from there. All what is needed is to then give ModRun the path to the local Maven repository directory, and the groupId, artifactId, artifactVersion and main class to run, plus any additional command line arguments the application needs. Running Java applications using ModRun makes the classPath very simple. Only ModRun’s JAR file is needed on the classpath. The application artifact and its dependencies are all resolved at runtime, and loaded using ModRun’s special ClassLoader structure. ModRun’s special ClassLoader structure can resolve and load the dependencies of a Maven artifact at runtime. The ClassLoader structure is capable of isolating the dependencies of a module (artifact) from the dependencies of other artifacts. That means that it is possible to load different versions of the same artifact into memory, even within the same application (provided certain conditions are met). ModRun can also load the same application into the same JVM multiple times (or different applications), and keep them completely isolated from each other. Good from a security point of view!:) Upgrading Java Applications Upgrading a Java application with ModRun is no more difficult than installing it in the first place! The new version is downloaded from a remote Maven repository and installed in the local, along with any new dependencies. Uninstalling Java Applications and Dependencies When ModRun installs artifacts in the local Maven repository structure, it keeps track of what artifacts are applications and what are just dependencies. This way, ModRun can easily uninstall an application — or a specific version of an application. After uninstalling an application ModRun can traverse the whole local Maven repository structure and find out what dependencies are no longer referenced by any applications. These dependencies can then be deleted too (they can always be downloaded easily again, if needed in the future). ModRun vs. Jigsaw ModRun solves some of the same problems as project Jigsaw in Java 9. However, Jigsaw does not solve artifact versioning, nor provide a standardised Java application/module repository structure, nor provides standardised installation and uninstallation procedures (as far as we know). ModRun provides all that! ModRun works with Java 8 of course, and we will make sure it will also work with Java 9. Finally, in addition to the features described in the sections above, we have many other ideas for ModRun. For instance, features for keeping large grids of servers up-to-date with the same Java applications ( ), or upgrade the servers in groups (alpha servers, beta servers and the rest). e.g. microservices ModRun GitHub Repository ModRun is open source (Apache license 2.0) and can be found on . Please feel free to check it out and star it if you like it and there are also some written by our Co — Founder and CTO at , Jakob Jenkov. GitHub here tutorials Nanosai

Making Life Easier for Java Devs: ModRun vs. Project Jigsaw

Recently, more people are consciously choosing solitude, and not only because they fear romantic relationships, had a traumatic experience in the past, or as with the situation in countries like Japan, find it hard to socialize and are prone to having an AI-powered partner. And the world’s most popular dating apps don’t help - they’re more like mobile games now than potential “partner finders.” For some, solitude feels more comfortable, allowing them to focus on their interests and self-realization. However, there is another category of people: those who convince themselves that they are happy being alone, even though this is likely not true. These individuals may adopt this mindset because they have struggled for a long time to find a suitable partner. Consciously chosen singleness may bring them comfort, but only temporarily. Their pain and discomfort will eventually take over. Since AI is in every part of our lives now, it is obvious that it becomes the norm in our love lives too. Let’s look at how needs and values can help people identify the reason for their involuntary solitude and how AI-powered partner selection can help throughout this journey. Singleness as a Temporary Solution Individuals who struggle to find a suitable partner often experience frustration and begin to doubt their ability to build a happy relationship. Initially, they may chalk the situation up to bad luck, believing that they will soon meet the right person. However, eventually, they start to question their own worth: "What if something is wrong with me?" No one likes to think badly of themselves, so denial as a form of psychological defence kicks in. It manifests itself as the stance: "I don't need a relationship at all. I'm fine on my own." In such cases, solitude becomes a temporary solution rather than a conscious choice. To move beyond this stage and find a suitable partner, it is crucial to understand one's needs, values, and personality traits. Why Do We Seek Relationships and What Needs Do They Fulfill People start relationships for various reasons, but for all of us, a harmonious and stable partnership serves as a source of positive emotions and helps satisfy a range of needs. Relationships filled with love and understanding help satisfy our need for support and care. They provide the feelings of closeness and intimacy with another human being. For some, relationships also serve as a source of confidence and security, making them feel more safe knowing they have a reliable partner by their side. In some cultures, having a partner is perceived as a marker of social status. People may seek relationships to meet societal norms and expectations. Additionally, starting a family and having children is often seen as a logical extension of romantic relationships. The desire to continue one's lineage can be deeply rooted in cultural and family traditions, often driving people to seek a partner. Relationships can foster personal growth, as interacting with a partner provides feedback on our behavior and emotions, promoting self-improvement. Many people look for a partner with whom they can share common goals and aspirations, whether in career ambitions, travel, or hobbies. The desire for intimacy and sexual satisfaction is a significant motivator for entering relationships. In healthy couples, physical needs, as well as immaterial ones, are always satisfied. For some, relationships help find meaning and purpose in life. They feel that their life becomes more complete and significant with a partner. Additionally, having a partner helps overcome feelings of loneliness and isolation, providing a sense of belonging and connection. Understanding which needs you seek to fulfil in a relationship will help you find a partner able to satisfy them. Self-knowledge as the Key to Successful Relationships Knowing your personality, values and motives for starting a relationship can significantly ease the process of finding a partner. Ask yourself why you need a relationship now. Sometimes, people realize that they do not need a relationship at the moment, and the problem resolves itself along with unpleasant emotions and worries. Also, articulate your long-term expectations from a relationship. Identify your needs and values. Make a list of what is important to you in life, both material and immaterial aspects, such as self-realization or a sense of belonging to a group. This will help you understand what kind of person with which values will suit you best. Analyze past relationships. Reflect on your previous relationships to understand which traits in partners you liked and which you did not. This will help you avoid repeating past mistakes. Formulate a new relationship scenario. Identifying your true needs and values and pointing out which mistakes to avoid will make it easier to form a new vision of a future relationship and your role in it. Develop emotional intelligence. Learn to understand and express your emotions, as well as recognize the emotions of others. Emotional intelligence plays a crucial role in building strong and healthy relationships. Seek professional help if needed. A psychologist can help you gain deeper self-awareness and understand why long-term relationships have not worked out. How AI-Powered Partner Solutions Can Help AI can analyze your personality and offer recommendations for developing certain qualities. It can also suggest what type of partner you should be looking for. AI-based online platforms offer various tests that provide a deep analysis of your personality. These tests are based on scientific knowledge and can help you better understand yourself. AI can analyze large volumes of data to offer more accurate recommendations. Platforms like BestFitMe or YouMatch can analyze your personality and even give behavior predictions based on your photograph. Some studies employ neural networks to analyze and quantify personality traits based on individuals' portrait photographs. Based on the analysis of your data, AI can offer personalized advice and strategies to improve your social skills, including interactions with potential partners. By choosing AI-powered apps with a more profound approach to connecting people, you can increase your chances of meeting the right person. For example, Rizz app uses AI to help users start dialogue and engage in an interesting and deep conversation to get to know each other better. You might also consider Jigsaw, an app that doesn't let users see their matches' faces before they have a conversation. This allows users the chance to connect on a deeper level than just physical attraction. YouMatch leverages technology to analyze people's personalities and connect couples with a higher level of compatibility, giving them a greater chance to build a joyful and lasting relationship. The Convergence of Self-Discovery and AI in the Pursuit of Love In the ever-evolving landscape of human connection, the fusion of self-awareness and AI-powered partner selection is reshaping the way we approach relationships. Whether solitude is a conscious choice or a temporary state, understanding our needs, values, and personalities remains paramount in the quest for a fulfilling partnership. AI, with its ability to analyze vast amounts of data and provide tailored recommendations, is emerging as a powerful ally in this journey. By embracing self-discovery and harnessing the potential of AI, we can navigate the complexities of modern dating and increase our chances of finding a partner who truly complements our unique selves. After all, love, in its many forms, is a fundamental human need, and in this digital age, AI may well hold the key to unlocking deeper connections and lasting happiness. Recently, more people are consciously choosing solitude, and not only because they fear romantic relationships, had a traumatic experience in the past, or as with the situation in countries like Japan, find it hard to socialize and are prone to having an AI-powered partner . And the world’s most popular dating apps don’t help - they’re more like mobile games now than potential “partner finders.” For some, solitude feels more comfortable, allowing them to focus on their interests and self-realization. an AI-powered partner an AI-powered partner world’s most popular dating apps world’s most popular dating apps However, there is another category of people: those who convince themselves that they are happy being alone, even though this is likely not true. These individuals may adopt this mindset because they have struggled for a long time to find a suitable partner. Consciously chosen singleness may bring them comfort, but only temporarily. Their pain and discomfort will eventually take over. Since AI is in every part of our lives now, it is obvious that it becomes the norm in our love lives too. Let’s look at how needs and values can help people identify the reason for their involuntary solitude and how AI-powered partner selection can help throughout this journey. Singleness as a Temporary Solution Individuals who struggle to find a suitable partner often experience frustration and begin to doubt their ability to build a happy relationship. Initially, they may chalk the situation up to bad luck, believing that they will soon meet the right person. However, eventually, they start to question their own worth: "What if something is wrong with me?" No one likes to think badly of themselves, so denial as a form of psychological defence kicks in. It manifests itself as the stance: "I don't need a relationship at all. I'm fine on my own." In such cases, solitude becomes a temporary solution rather than a conscious choice. To move beyond this stage and find a suitable partner, it is crucial to understand one's needs, values, and personality traits. Why Do We Seek Relationships and What Needs Do They Fulfill People start relationships for various reasons, but for all of us, a harmonious and stable partnership serves as a source of positive emotions and helps satisfy a range of needs. Relationships filled with love and understanding help satisfy our need for support and care. They provide the feelings of closeness and intimacy with another human being. For some, relationships also serve as a source of confidence and security, making them feel more safe knowing they have a reliable partner by their side. In some cultures, having a partner is perceived as a marker of social status. People may seek relationships to meet societal norms and expectations. Additionally, starting a family and having children is often seen as a logical extension of romantic relationships. The desire to continue one's lineage can be deeply rooted in cultural and family traditions, often driving people to seek a partner. Relationships can foster personal growth, as interacting with a partner provides feedback on our behavior and emotions, promoting self-improvement. Many people look for a partner with whom they can share common goals and aspirations, whether in career ambitions, travel, or hobbies. The desire for intimacy and sexual satisfaction is a significant motivator for entering relationships. In healthy couples, physical needs, as well as immaterial ones, are always satisfied. For some, relationships help find meaning and purpose in life. They feel that their life becomes more complete and significant with a partner. Additionally, having a partner helps overcome feelings of loneliness and isolation, providing a sense of belonging and connection. Understanding which needs you seek to fulfil in a relationship will help you find a partner able to satisfy them. Self-knowledge as the Key to Successful Relationships Knowing your personality, values and motives for starting a relationship can significantly ease the process of finding a partner. Ask yourself why you need a relationship now. Sometimes, people realize that they do not need a relationship at the moment, and the problem resolves itself along with unpleasant emotions and worries. Also, articulate your long-term expectations from a relationship. Identify your needs and values. Make a list of what is important to you in life, both material and immaterial aspects, such as self-realization or a sense of belonging to a group. This will help you understand what kind of person with which values will suit you best. Analyze past relationships. Reflect on your previous relationships to understand which traits in partners you liked and which you did not. This will help you avoid repeating past mistakes. Formulate a new relationship scenario. Identifying your true needs and values and pointing out which mistakes to avoid will make it easier to form a new vision of a future relationship and your role in it. Develop emotional intelligence. Learn to understand and express your emotions, as well as recognize the emotions of others. Emotional intelligence plays a crucial role in building strong and healthy relationships. Seek professional help if needed. A psychologist can help you gain deeper self-awareness and understand why long-term relationships have not worked out. How AI-Powered Partner Solutions Can Help AI can analyze your personality and offer recommendations for developing certain qualities. It can also suggest what type of partner you should be looking for. AI-based online platforms offer various tests that provide a deep analysis of your personality. These tests are based on scientific knowledge and can help you better understand yourself. AI can analyze large volumes of data to offer more accurate recommendations. Platforms like BestFitMe or YouMatch can analyze your personality and even give behavior predictions based on your photograph. Some studies employ neural networks to analyze and quantify personality traits based on individuals' portrait photographs. Based on the analysis of your data, AI can offer personalized advice and strategies to improve your social skills, including interactions with potential partners. studies studies By choosing AI-powered apps with a more profound approach to connecting people, you can increase your chances of meeting the right person. For example, Rizz app uses AI to help users start dialogue and engage in an interesting and deep conversation to get to know each other better. You might also consider Jigsaw, an app that doesn't let users see their matches' faces before they have a conversation. This allows users the chance to connect on a deeper level than just physical attraction. YouMatch leverages technology to analyze people's personalities and connect couples with a higher level of compatibility, giving them a greater chance to build a joyful and lasting relationship. The Convergence of Self-Discovery and AI in the Pursuit of Love In the ever-evolving landscape of human connection, the fusion of self-awareness and AI-powered partner selection is reshaping the way we approach relationships. Whether solitude is a conscious choice or a temporary state, understanding our needs, values, and personalities remains paramount in the quest for a fulfilling partnership. AI, with its ability to analyze vast amounts of data and provide tailored recommendations, is emerging as a powerful ally in this journey. By embracing self-discovery and harnessing the potential of AI, we can navigate the complexities of modern dating and increase our chances of finding a partner who truly complements our unique selves. After all, love, in its many forms, is a fundamental human need, and in this digital age, AI may well hold the key to unlocking deeper connections and lasting happiness.

From Solitude to Connection: Leveraging Self-Knowledge and AI-Powered Partner Selection

Beyond the Screen: How Modern Technology Is Redefining Our Relationships and Love

FRAUD: The Blind Spot That Could Blindside Your Business

জালিয়াতি: ব্লাইন্ড স্পট যা আপনার ব্যবসাকে অন্ধ করে দিতে পারে

BETRUG: Der blinde Fleck, der Ihr Unternehmen überraschen könnte

FRAUDE: El punto ciego que podría sorprender a su negocio

FRAUDE : L'angle mort qui pourrait aveugler votre entreprise

धोखाधड़ी: वह अंधी जगह जो आपके व्यवसाय को चौपट कर सकती है

詐欺：あなたのビジネスを脅かす盲点

사기: 비즈니스를 방해할 수 있는 맹점

FRAUDE: o ponto cego que pode cegar sua empresa

МОШЕННИЧЕСТВО: «слепое пятно», которое может поставить под угрозу ваш бизнес

SAHTEKARLIK: İşinizi Körleştirebilecek Kör Nokta

LỪA ĐẢO: Điểm mù có thể làm mờ mắt doanh nghiệp của bạn

欺诈：可能让你的企业蒙受损失的盲点

Cryptographic Ransomware Encryption Detection: Survey: on Crypto-ransomware Behavior and Methodology

Authors:
(1) Simon R. Davies, School of Computing, Edinburgh Napier University, Edinburgh, UK (s.davies@napier.ac.uk);
(2) Richard Macfarlane, School of Computing, Edinburgh Napier University, Edinburgh, UK;
(3) William J. Buchanan, School of Computing, Edinburgh Napier University, Edinburgh, UK. Table of Links Abstract and 1 Introduction
2. Related Work
3. Methodology and 3.1. File Content Analysis
3.2. File Name Analysis
3.3. Executable Analysis
3.4. Behaviour Analysis
4. Evaluation and Discussion
4.1. Majority Voting
5. Conclusion
5.1. Limitations
5.2. Future Work
References and Appendix 4.1. Majority Voting When reviewing the results from the separate tests mentioned above, it can be seen that several tests achieved a high degree of accuracy in differentiating between benign and malicious programs, using both static and dynamic tests. The results from some tests such as attempting to identify cryptographic artefacts, ransom note identification within the process and executable or Windows API enumeration, delivered inconclusive results and these tests would require some more investigation, analysis and modification. It is proposed that a system could be developed that uses a combination of the tests that have been found to be accurate in identifying ransomware. Each test’s vote would contribute to an overall malice score for the target file or process, and based on the maximum number of votes the system would classify the target as either malicious or benign. For example, a system could be developed that used the following tests: created file name and extension entropy, well-known extensions, file magic number and printable characters, file content BitByte and entropy values, ransom note creation detection and system restore point removal detection. Based on the findings from this research, a system configured with these tests would have an accuracy of 0.9989 on the dataset used. Some of the interesting test results are highlighted in Figure 7. When reviewing the results for benign programs shown in Figure 7, it can be seen that the majority of tests consider the processes/files to be benign. Even in cases where some of the individual tests do occasionally give false positives, in all cases, the majority of the tests vote correctly resulting in a correct overall classification. For example, when looking at the classification for WEBP file types, it can be seen that the individual file entropy and BitByte tests, result in a classification accuracy of around 55%, and 45% of the samples are incorrectly classified as malicious. However, as the remaining six tests correctly vote that the file is benign, these files are ultimately classified as benign. Likewise, when reviewing the result for the ransomware files, in most cases the majority of tests classify the file/process as malicious. The only exception would be on the very rare occasion, the files generated by the Jigsaw ransomware strain, may theoretically receive a false positive classification if the majority of the tests vote that the file/process is benign. A major strength of the majority voting approach to ransomware detection is that not every test needs to correctly classify a malicious program every time. With equal weighting on the result of each test, it would be sufficient for just a majority of tests to correctly classify the target, for the system to work successfully. Some work could also be performed to investigate whether a weighting or bias could also be applied to the test results meaning that some tests would then have a greater influence on the overall outcome of the classification, than others. As the detection technique relies on well-known discrete tests, it is also easier for the detection model to be modified, updated and tuned as opposed to a machine learning model where the weightings and strengths of the learned model can be unknown or difficult to influence. This paper is available on arxiv under CC BY 4.0 DEED license. Authors: (1) Simon R. Davies, School of Computing, Edinburgh Napier University, Edinburgh, UK (s.davies@napier.ac.uk); (2) Richard Macfarlane, School of Computing, Edinburgh Napier University, Edinburgh, UK; (3) William J. Buchanan, School of Computing, Edinburgh Napier University, Edinburgh, UK. Authors: Authors: (1) Simon R. Davies, School of Computing, Edinburgh Napier University, Edinburgh, UK (s.davies@napier.ac.uk); (2) Richard Macfarlane, School of Computing, Edinburgh Napier University, Edinburgh, UK; (3) William J. Buchanan, School of Computing, Edinburgh Napier University, Edinburgh, UK. Table of Links Abstract and 1 Introduction 2. Related Work 3. Methodology and 3.1. File Content Analysis 3.2. File Name Analysis 3.3. Executable Analysis 3.4. Behaviour Analysis 4. Evaluation and Discussion 4.1. Majority Voting 5. Conclusion 5.1. Limitations 5.2. Future Work References and Appendix Abstract and 1 Introduction Abstract and 1 Introduction 2. Related Work 2. Related Work 3. Methodology and 3.1. File Content Analysis 3. Methodology and 3.1. File Content Analysis 3.2. File Name Analysis 3.2. File Name Analysis 3.3. Executable Analysis 3.3. Executable Analysis 3.4. Behaviour Analysis 3.4. Behaviour Analysis 4. Evaluation and Discussion 4. Evaluation and Discussion 4.1. Majority Voting 4.1. Majority Voting 5. Conclusion 5. Conclusion 5.1. Limitations 5.1. Limitations 5.2. Future Work 5.2. Future Work References and Appendix References and Appendix 4.1. Majority Voting When reviewing the results from the separate tests mentioned above, it can be seen that several tests achieved a high degree of accuracy in differentiating between benign and malicious programs, using both static and dynamic tests. The results from some tests such as attempting to identify cryptographic artefacts, ransom note identification within the process and executable or Windows API enumeration, delivered inconclusive results and these tests would require some more investigation, analysis and modification. It is proposed that a system could be developed that uses a combination of the tests that have been found to be accurate in identifying ransomware. Each test’s vote would contribute to an overall malice score for the target file or process, and based on the maximum number of votes the system would classify the target as either malicious or benign. For example, a system could be developed that used the following tests: created file name and extension entropy, well-known extensions, file magic number and printable characters, file content BitByte and entropy values, ransom note creation detection and system restore point removal detection. Based on the findings from this research, a system configured with these tests would have an accuracy of 0.9989 on the dataset used. Some of the interesting test results are highlighted in Figure 7. When reviewing the results for benign programs shown in Figure 7, it can be seen that the majority of tests consider the processes/files to be benign. Even in cases where some of the individual tests do occasionally give false positives, in all cases, the majority of the tests vote correctly resulting in a correct overall classification. For example, when looking at the classification for WEBP file types, it can be seen that the individual file entropy and BitByte tests, result in a classification accuracy of around 55%, and 45% of the samples are incorrectly classified as malicious. However, as the remaining six tests correctly vote that the file is benign, these files are ultimately classified as benign. Likewise, when reviewing the result for the ransomware files, in most cases the majority of tests classify the file/process as malicious. The only exception would be on the very rare occasion, the files generated by the Jigsaw ransomware strain, may theoretically receive a false positive classification if the majority of the tests vote that the file/process is benign. A major strength of the majority voting approach to ransomware detection is that not every test needs to correctly classify a malicious program every time. With equal weighting on the result of each test, it would be sufficient for just a majority of tests to correctly classify the target, for the system to work successfully. Some work could also be performed to investigate whether a weighting or bias could also be applied to the test results meaning that some tests would then have a greater influence on the overall outcome of the classification, than others. As the detection technique relies on well-known discrete tests, it is also easier for the detection model to be modified, updated and tuned as opposed to a machine learning model where the weightings and strengths of the learned model can be unknown or difficult to influence. This paper is available on arxiv under CC BY 4.0 DEED license. This paper is available on arxiv under CC BY 4.0 DEED license. available on arxiv

Majority Voting Approach to Ransomware Detection: Majority Voting

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