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Taxonomie des anti-modèles Scrum

La taxonomie des anti-modèles Scrum est une classification des pratiques qui sont contraires à l’approche Scrum. Découvrons comment ces pratiques peuvent nuire à l’efficacité de votre équipe.

TL; DR : Taxonomie des anti-patterns Scrum

TL; DR: Taxonomie des anti-patterns Scrum

Alors que le processus d’édition du Guide des anti-patterns Scrum est sur le point de se terminer, il est temps de passer à l’étape suivante. Le tout nouveau Guide des anti-patterns Scrum offre plus de 180 anti-patterns organisés par rôles, événements, artefacts et engagements. Cependant, le guide ne crée pas une taxonomie d’anti-patterns Scrum de niveau métal ou abstrait. Par conséquent, le guide ne fournit pas de stratégie globale pour contrer ou éviter les anti-patterns Scrum à un niveau personnel, culturel, structurel ou organisationnel. La question est de savoir s’il est possible de créer une telle taxonomie.

Lisez la suite et en apprenez plus sur les premières étapes de la finalisation du grand tableau des anti-patterns Scrum.

La taxonomie des anti-patterns Scrum est un outil précieux pour les développeurs et les équipes qui cherchent à améliorer leur processus de développement et à éviter les erreurs courantes. Une taxonomie des anti-patterns Scrum peut être utilisée pour identifier les problèmes courants et les solutions possibles. Elle peut également être utilisée pour comprendre comment les différents aspects du développement peuvent interagir et affecter le processus global. Une taxonomie des anti-patterns Scrum peut également aider à identifier les bonnes pratiques et à définir des objectifs pour améliorer le processus de développement.

Une taxonomie des anti-patterns Scrum peut être divisée en quatre catégories principales : le code, le processus, l’organisation et la culture. Chaque catégorie peut être divisée en sous-catégories plus spécifiques. Par exemple, la catégorie « code » peut être divisée en sous-catégories telles que le codage, la documentation, la qualité et la sécurité. La catégorie « processus » peut être divisée en sous-catégories telles que la planification, l’estimation, le suivi et la gestion des changements. La catégorie « organisation » peut être divisée en sous-catégories telles que la structure organisationnelle, la communication et la collaboration. Enfin, la catégorie « culture » peut être divisée en sous-catégories telles que l’apprentissage, l’innovation et l’amélioration continue.

Une fois que les différentes catégories et sous-catégories sont identifiées, il est possible de créer une taxonomie des anti-patterns Scrum. Cette taxonomie peut être utilisée pour identifier les problèmes courants et les solutions possibles. Elle peut également être utilisée pour comprendre comment les différents aspects du développement peuvent interagir et affecter le processus global. Enfin, elle peut aider à identifier les bonnes pratiques et à définir des objectifs pour améliorer le processus de développement.

La taxonomie des anti-patterns Scrum est un outil précieux pour les développeurs et les équipes qui cherchent à améliorer leur processus de développement et à éviter les erreurs courantes. En créant une taxonomie des anti-patterns Scrum, il est possible d’identifier les

Source de l’article sur DZONE

Reap the full benefits of enhanced code quality, better testing practices, and early error detection with proper implementation of continuous integration processes. This Refcard explains detailed patterns and anti-patterns for core areas of CI, including version control, the build stage, pipeline monitoring, documentation, as well as communication and collaboration across teams and within the organization.
Source de l’article sur DZONE

It is important to invest time and effort in understanding why a system performs the way it does and how we can improve it. Companies continue with practices that yield successful results but ignoring anti-patterns can be far worse than choosing rigid processes. In this article, we will explore anti-patterns in incident response and why you should unlearn those.

Common Anti-Patterns in Incident Response 

Just Get Everyone on the Call 

Alerting everyone each time an incident is detected is not the best of practices. Sometimes notifying everyone is easier or adds value. For example:

Source de l’article sur DZONE

Knowing anti-patterns and pitfalls is often more useful than knowing patterns when designing a system, so I decided to write this blog post about factors that I think will lead to producing unreliable systems from my experiences in designing (mostly) distributed enterprise applications.
I’ll be pleased to know your related experiences and comments on the matter.

What Is Modeling?

The human brain is a pattern-seeking device. However, it’s a costly process, and the main goal of thinking is to terminate/resolve what caused this process to start in the first place; so it has developed several mechanisms to prevent it from happening too often; the one related to our discussion here is the mental model. Reality is complex, chaotic, and too messy for our limited brain capabilities and resources to comprehend as it is (if that’s even possible); so our minds will try to create an alternative reality which is very simple and (most of the time) easily understandable, and that’s what modeling is all about! from how we think about how nature works, in science for example, to proper social behavior, to what to be afraid of or seek for, all are the results of our mental model. It is noteworthy that models are neither objective reality nor meant to be so!

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The goal for a successful continuous delivery process is to minimize the time it takes for development teams to go from idea to usable software by practicing agile techniques and automating the entire software delivery system: build, deploy, test, release. This Refcard explains detailed patterns and anti-patterns for core areas of CD, including the delivery and deployment phases, rollbacks, pipeline observability and monitoring, documentation, as well as communication across teams and within the organization.
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The reasons Scrum Masters violate the spirit of the Scrum Guide are multi-faceted. Typical Scrum Master anti-patterns run from ill-suited personal traits to complacency to pursuing individual agendas to frustration with the team itself.

Read on and learn in this post on Scrum anti-patterns how you can identify if your Scrum Master needs support from the team.

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The best way to protect your Java code from avoidable bugs is to use static code analysis tools that can help you find and fix problematic code before it reaches production. Let’s look at some popular static code analysis tools that can be used to test code from a number of different angles.

DeepSource

DeepSource delivers what is probably the best static code analysis you can find for Java. The DeepSource Java analyzer detects 190+ code quality issues, including performance bugs, security risks, bug risks, and anti-patterns. Currently, It supports Gradle Java projects, and in the future, DeepSource will add support for Maven and Android too. DeepSource is also working on bringing Autofix support to the Java analyzer, which will let developers fix issues without writing a single code line.

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Starting with Django 3.1, the latest version that dropped a couple of weeks ago, Django now supports fully asynchronous request path. This is exciting for everyone who’s been waiting on the edge of their seats ever since Andrew Godwin’s DEP 0009 was approved by Django Technical Board in July 2019. Read on to know all about what this release means if you have a Django application in production and looking to add async support. At DeepSource, we’re working on adding more Django issues in our Python analyzer, which will also include async-specific bug risks and anti-patterns.

Support for Asynchronous Views and Middleware

In Django 3.1, async features are now supported across the request-response cycle. This means you can define fully asynchronous views using the async keyword:

Source de l’article sur DZONE


Agile 

AI

Big Data

Cloud

Database

DevOps

Integration

  • Mulesoft 4: Continuous Delivery/Deployment With Maven by Ashok S — This article is a great example of what we want every tutorial to look like on DZone. The main aim of this article is to provide a standard mechanism to release project artifacts and deploy to Anypoint Platform, from the local machine or configure in continuous delivery pipelines.
  • Integration With Social Media Platforms Series (Part 1) by Sravan Lingam — This article helps you to build a RESTful API through MuleSoft that integrates with LinkedIn and shares a post on behalf of one’s personal account. I like this article because, in the age of social media, it’s so important for businesses to be connected and integrated!

IoT

Java

Microservices

Open Source

Performance

  • What Is Big O Notation? by Huyen Pham — Aside from a silly name, this article is an example of an in-depth analysis on a little-spoken-about concept. In this article, take a look at a short guide to get to know Big O Notation and its usages.
  • Is Python the Future of Programming? by Shormisthsa Chatterjee — Where is programming going? This article attempts to answer this question in a well-rounded way. The author writes, "Python will be the language of the future. Testers will have to upgrade their skills and learn these languages to tame the AI and ML tools".

Security

Web Dev

  • A Better Way to Learn Python by Manas Dash: There’s so many resources available for learning Python — so many that it’s difficult to find a good and flexible place to start. Check out Manas’ curated list of courses, articles, projects, etc. to get your Python journey started today. 
  • Discovering Rust by Joaquin Caro: I’m a sucker for good Rust content, as there’s still so many gaps in what’s available. Joaquin does a great job of giving readers his perspective of the language’s features in a way that traditional docs just 

Source de l’article sur DZONE