Javascript on Server-Side

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Node.js and Express Typescript NoSQL and MongoDB Blocking and Non-Blocking Basic Server with Express Typescript in detail SQL vs NoSQL Mongoose

Topics
• Node.js and Express
• Typescript
• NoSQL and MongoDB

Node.js
• Server side Javascript
• Platform build on Chrome’s v8 JS Engine
• Lightweight
• Event-driven (Non-blocking)
• Can handle thousands of connectios

Express
• Express is a lightweight framework on top of ‘connect’ module
• Request / Response enhancements
• Routing
• View Support
• Content Negotiation

Typescript
• Typescript is a typed superset of Javascript
• Compiles into plain Javascript code
• Typescript adds Static Typing and structuring (class, module) to
Javascript
• For large and complex applications

Typescript
• The idea is to help in large scale Javascript application development
• Typescript is Javascript
• Open Source
• Borrows ideas from ES6 Harmony

Typescript Features
• Type Annotation / Static Typing
• Type Inference

Typescript Features
• Types for function parameters, return type, rest parameters etc.

SQL vs NoSQL
• SQL is the standard language for Relational Databases.
• MySQL, Oracle, MsSQL, Sybase etc.
• NoSQL is a non-relational database management system.
• MongoDB, Redis, Cassandra etc.

When to use SQL
• SQL is the easiest language used to communicate with the RDBMS
• Preferred when you want to use joins and execute complex queries

When to use NoSQL
• When data needs a flexible schema
• Constraints and validations logic not required inside database
• Logging data from distributed sources
• It should be used to store temporary data (shopping carts, wish list
session data)

$Example Queries • {borough:"Bronx"} • {borough:{$eq:"Bronx"}} • {borough:{$ne:"Bronx"}} • {borough:"Bronx", cuisine:"Bakery"} • {$or:[{"borough": "Bronx"}, {"cuisine":"Japanese"}]} • {name: /^Deli/} • {"address.coord": {$gt:41}} • {"address.coord":{$gte:41, $lte:-60}}$

Mongoose
• Mongoose provides a straight-forward, schema-based solution to
model the application data for Node.js
• It includes built-in
• Type casting
• Validation
• Query building
• Business logic hooks

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Societal challenges of AI: biases, multilinguism and sustainabilityJordi Cabot

How Valletta helped healthcare SaaS to transform QA and compliance to grow wi...Egor Kaleynik

This case study explores how we partnered with a mid-sized U.S. healthcare SaaS provider to help them scale from a successful pilot phase to supporting over 10,000 users—while meeting strict HIPAA compliance requirements. Faced with slow, manual testing cycles, frequent regression bugs, and looming audit risks, their growth was at risk. Their existing QA processes couldn’t keep up with the complexity of real-time biometric data handling, and earlier automation attempts had failed due to unreliable tools and fragmented workflows. We stepped in to deliver a full QA and DevOps transformation. Our team replaced their fragile legacy tests with Testim’s self-healing automation, integrated Postman and OWASP ZAP into Jenkins pipelines for continuous API and security validation, and leveraged AWS Device Farm for real-device, region-specific compliance testing. Custom deployment scripts gave them control over rollouts without relying on heavy CI/CD infrastructure. The result? Test cycle times were reduced from 3 days to just 8 hours, regression bugs dropped by 40%, and they passed their first HIPAA audit without issue—unlocking faster contract signings and enabling them to expand confidently. More than just a technical upgrade, this project embedded compliance into every phase of development, proving that SaaS providers in regulated industries can scale fast and stay secure.

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What Do Contribution Guidelines Say About Software Testing? (MSR 2025)Andre Hora

Software testing plays a crucial role in the contribution process of open-source projects. For example, contributions introducing new features are expected to include tests, and contributions with tests are more likely to be accepted. Although most real-world projects require contributors to write tests, the specific testing practices communicated to contributors remain unclear. In this paper, we present an empirical study to understand better how software testing is approached in contribution guidelines. We analyze the guidelines of 200 Python and JavaScript open-source software projects. We find that 78% of the projects include some form of test documentation for contributors. Test documentation is located in multiple sources, including CONTRIBUTING files (58%), external documentation (24%), and README files (8%). Furthermore, test documentation commonly explains how to run tests (83.5%), but less often provides guidance on how to write tests (37%). It frequently covers unit tests (71%), but rarely addresses integration (20.5%) and end-to-end tests (15.5%). Other key testing aspects are also less frequently discussed: test coverage (25.5%) and mocking (9.5%). We conclude by discussing implications and future research.