JavaScript for ABAP Programmers - 1/7 Introduction

Feb 18, 20144 likes6,374 views

JavaScript was originally created as Mocha in 1995 by Brendan Eich at Netscape in 10 days and was renamed LiveScript and then JavaScript to complement Sun Microsystem's Java, though it is not the same as Java. It borrows elements from languages like Scheme and Perl. JavaScript is standardized by ECMA and various JavaScript engines like SpiderMonkey, Chakra, V8, and Nitro execute it client-side in browsers or server-side in implementations like HANA XSJS. The main differences between JavaScript and ABAP are that JavaScript is weakly typed, has lexical scope, treats functions as first-class citizens, uses prototypal inheritance, and allows both imperative and functional programming.

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JavaScript for ABAP Programmers
Introduction
Chris Whealy / The RIG

JavaScript’s Name – And the Resulting Confusion…
JavaScript was first developed by Brendan Eich at Netscape in 1995 (in 10 days). Originally this new
scripting language was called “Mocha”.
When Netscape Navigator 2.0 was shipped in September 1995, the language was renamed to
“LiveScript”.
However, when Netscape Navigator 2.0B3 was released on December 4th, 1995, Netscape made a
joint announcement with Sun Microsystems to the effect that Netscape’s new scripting language would
complement Sun Microsystem’s new Web application language Java; therefore, the new scripting
language would be called “JavaScript” – and this has caused no end of confusion ever since…
The bottom line is simply this…

JavaScript is NOT Java!

© 2013 SAP AG. All rights reserved.

2

JavaScript’s Linguistic Heritage
Over the course of the language’s development, various conceptual elements have been borrowed
from other languages to form what is now called JavaScript.

JavaScript

© 2013 SAP AG. All rights reserved.

3

JavaScript Standards
JavaScript was standardised by the European Computer Manufacturer’s Association (ECMA) in 1997.
JavaScript used in browsers is now considered to be only one implementation of the ECMA-262
specification.

Edition

Date
1 June 1997
2 June 1998
3 December 1999
4 Abandoned
5 December 2009

5.1 June 2011
6 (Harmony) Work in progress
7 Work in progress

© 2013 SAP AG. All rights reserved.

7

JavaScript Runtime Engines
In order to execute a JavaScript program, a JavaScript Engine is needed.
Multiple implementations of JavaScript engines are available, with the most widely used being:

JavaScript Engine
Rhino (Mozilla)
SpiderMonkey (Mozilla)
Chakra (Microsoft)

V8 (Google)
Nitro (Apple)

© 2013 SAP AG. All rights reserved.

8

JavaScript Runtime: Client Side Implementations
Modern JavaScript engines have been designed to run either from within a web browser or as stand
alone, server-side execution engines.

Browser

JavaScript Engine

Mozilla Firefox

SpiderMonkey (Mozilla)

Microsoft Internet Explorer

Chakra (Microsoft)

Google Chrome

V8 (Google)

Apple Safari

Nitro (Apple)

© 2013 SAP AG. All rights reserved.

9

JavaScript Runtime: Server Side Implementations
There are multiple server-side implementations of JavaScript, many of which are based on Mozilla
Rhino (Java based). When speed is required however, Mozilla SpiderMonkey or the Google V8
engine are used instead.

Server Side Implementation

JavaScript Engine
SpiderMonkey (Mozilla)

HANA XSJS
Accessible via

Chakra (Microsoft)

V8 (Google)
Nitro (Apple)

© 2013 SAP AG. All rights reserved.

10

In A Nutshell – The Main Differences Between ABAP & JavaScript
Understanding the differences between ABAP and JavaScript is fundamental to transferring your
existing programming skills into JavaScript. Some of the main differences are as follows:

ABAP

JavaScript

Strongly typed

Weakly typed

Syntax similar to COBOL

Syntax derived from Java (and C)

Block scope

Lexical scope

No equivalent concept

Functions are 1st class citizens

OO using class based inheritance

OO using referential inheritance

Imperative programming

Imperative or Functional programming

© 2013 SAP AG. All rights reserved.

11

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This presentation will showcase an adapter for FME Flow that provides REST endpoints for FME Workspaces following the OGC API Processes specification. The implementation delivers robust, user-friendly API endpoints, including standardized methods for parameter provision. Additionally, it enhances security and user management by supporting OAuth2 authentication. Join us to discover how these advancements can elevate your enterprise integration workflows and ensure seamless, secure interactions with FME Flow.

PyData - Graph Theory for Multi-Agent Integrationbarqawicloud

Graph theory is a well-known concept for algorithms and can be used to orchestrate the building of multi-model pipelines. By translating tasks and dependencies into a Directed Acyclic Graph, we can orchestrate diverse AI models, including NLP, vision, and recommendation capabilities. This tutorial provides a step-by-step approach to designing graph-based AI model pipelines, focusing on clinical use cases from the field.

The State of Web3 Industry- Industry ReportLiveplex

Web3 is poised for mainstream integration by 2030, with decentralized applications potentially reaching billions of users through improved scalability, user-friendly wallets, and regulatory clarity. Many forecasts project trillions of dollars in tokenized assets by 2030 , integration of AI, IoT, and Web3 (e.g. autonomous agents and decentralized physical infrastructure), and the possible emergence of global interoperability standards. Key challenges going forward include ensuring security at scale, preserving decentralization principles under regulatory oversight, and demonstrating tangible consumer value to sustain adoption beyond speculative cycles.

Kubernetes Security Act Now Before It’s Too LateMichael Furman

In today's cloud-native landscape, Kubernetes has become the de facto standard for orchestrating containerized applications, but its inherent complexity introduces unique security challenges. Are you one YAML away from disaster? This presentation, "Kubernetes Security: Act Now Before It’s Too Late," is your essential guide to understanding and mitigating the critical security risks within your Kubernetes environments. This presentation dives deep into the OWASP Kubernetes Top Ten, providing actionable insights to harden your clusters. We will cover: The fundamental architecture of Kubernetes and why its security is paramount. In-depth strategies for protecting your Kubernetes Control Plane, including kube-apiserver and etcd. Crucial best practices for securing your workloads and nodes, covering topics like privileged containers, root filesystem security, and the essential role of Pod Security Admission. Don't wait for a breach. Learn how to identify, prevent, and respond to Kubernetes security threats effectively. It's time to act now before it's too late!

Integration of Utility Data into 3D BIM Models Using a 3D Solids Modeling Wor...Safe Software

Jacobs has developed a 3D utility solids modelling workflow to improve the integration of utility data into 3D Building Information Modeling (BIM) environments. This workflow, a collaborative effort between the New Zealand Geospatial Team and the Australian Data Capture Team, employs FME to convert 2D utility data into detailed 3D representations, supporting enhanced spatial analysis and clash detection. To enable the automation of this process, Jacobs has also developed a survey data standard that standardizes the capture of existing utilities. This standard ensures consistency in data collection, forming the foundation for the subsequent automated validation and modelling steps. The workflow begins with the acquisition of utility survey data, including attributes such as location, depth, diameter, and material of utility assets like pipes and manholes. This data is validated through a custom-built tool that ensures completeness and logical consistency, including checks for proper connectivity between network components. Following validation, the data is processed using an automated modelling tool to generate 3D solids from 2D geometric representations. These solids are then integrated into BIM models to facilitate compatibility with 3D workflows and enable detailed spatial analyses. The workflow contributes to improved spatial understanding by visualizing the relationships between utilities and other infrastructure elements. The automation of validation and modeling processes ensures consistent and accurate outputs, minimizing errors and increasing workflow efficiency. This methodology highlights the application of FME in addressing challenges associated with geospatial data transformation and demonstrates its utility in enhancing data integration within BIM frameworks. By enabling accurate 3D representation of utility networks, the workflow supports improved design collaboration and decision-making in complex infrastructure projects

Reducing Conflicts and Increasing Safety Along the Cycling Networks of East-F...Safe Software

In partnership with the Belgian Province of East-Flanders this project aimed to reduce conflicts and increase safety along a cycling route between the cities of Oudenaarde and Ghent. To achieve this goal, the current cycling network data needed some extra key information, including: Speed limits for segments, Access restrictions for different users (pedestrians, cyclists, motor vehicles, etc.), Priority rules at intersections. Using a 360° camera and GPS mounted on a measuring bicycle, we collected images of traffic signs and ground markings along the cycling lanes building up mobile mapping data. Image recognition technologies identified the road signs, creating a dataset with their locations and codes. The data processing entailed three FME workspaces. These included identifying valid intersections with other networks (e.g., roads, railways), creating a topological network between segments and intersections and linking road signs to segments and intersections based on proximity and orientation. Additional features, such as speed zones, inheritance of speed and access to neighbouring segments were also implemented to further enhance the data. The final results were visualized in ArcGIS, enabling analysis for the end users. The project provided them with key insights, including statistics on accessible road segments, speed limits, and intersection priorities. These will make the cycling paths more safe and uniform, by reducing conflicts between users.