What is API's

Oct 21, 2014Download as PPTX, PDF3 likes556 views

API stands for application programming interface. It is a set of routines, protocols, and tools that allows software applications to communicate with each other. APIs specify how different software components should interact and are used when programming graphical user interfaces. They make it easier for programmers to develop applications by providing reusable code blocks. APIs allow different applications to share data and functionality, enabling features like copying text between programs. There are APIs for operating systems, applications, and websites that enable important functions like copy/paste and allow developers to create specialized software solutions.

API stands for application program interface
An API is the interface implemented by an application which
allows other applications to communicate with it.
It is a set of routines, protocols, and tools for building
software applications
The API specifies how software components should interact
and are used when programming graphical user interface
(GUI) components.
 A good API makes it easier to develop a program by
providing all the building blocks. A programmer then puts the
blocks together.

Why Is It Needed?
 It is used for Communication
 Imagine Notepad couldn’t copy-paste to and from
Microsoft Word or Google Chrome
 Imagine having to type each and every time although the
text is already there in some other application.
 This is only one of the examples of communication
between applications and all this communication is made
possible via APIs.

Types of APIs
There are different types of API's used for different
purposes.
These are
 for operating systems
 for Applications
 for websites

Windows, for example, has many API sets that are used by
system hardware and applications
when you copy and paste text from one application to
another, it is the API that allows that to work.
Most operating environments, such as MS-Windows, provide
an API so that programmers can write applications consistent
with the operating environment.
Today, APIs are also specified by websites.
For example, Amazon or eBay APIs allow developers to use the
existing retail infrastructure to create specialized web stores.
Third-party software developers also use Web APIs to create
software solutions for end-users.

What Is It Really?
You cannot run an API like you would run say a Notepad
application. This is because APIs are generally invisible to the end
users like you and me.
APIs are carefully thought out pieces of code created by
programmers for their applications that allow other applications
to interact with their application.
APIs are specially crafted to expose only chosen functionality
and/or data while safeguarding other parts of the application
which provides the interface.
Creating an API is indeed time well spent, because ultimately the
more applications that interact with your application the more
popular it becomes.

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Who Watches the Watchmen (SciFiDevCon 2025)Allon Mureinik

Tests, especially unit tests, are the developers’ superheroes. They allow us to mess around with our code and keep us safe. We often trust them with the safety of our codebase, but how do we know that we should? How do we know that this trust is well-deserved? Enter mutation testing – by intentionally injecting harmful mutations into our code and seeing if they are caught by the tests, we can evaluate the quality of the safety net they provide. By watching the watchmen, we can make sure our tests really protect us, and we aren’t just green-washing our IDEs to a false sense of security. Talk from SciFiDevCon 2025 https://www.scifidevcon.com/courses/2025-scifidevcon/contents/680efa43ae4f5

Proactive Vulnerability Detection in Source Code Using Graph Neural Networks:...Ranjan Baisak

As software complexity grows, traditional static analysis tools struggle to detect vulnerabilities with both precision and context—often triggering high false positive rates and developer fatigue. This article explores how Graph Neural Networks (GNNs), when applied to source code representations like Abstract Syntax Trees (ASTs), Control Flow Graphs (CFGs), and Data Flow Graphs (DFGs), can revolutionize vulnerability detection. We break down how GNNs model code semantics more effectively than flat token sequences, and how techniques like attention mechanisms, hybrid graph construction, and feedback loops significantly reduce false positives. With insights from real-world datasets and recent research, this guide shows how to build more reliable, proactive, and interpretable vulnerability detection systems using GNNs.

Expand your AI adoption with AgentExchangeFexle Services Pvt. Ltd.

AgentExchange is Salesforce’s latest innovation, expanding upon the foundation of AppExchange by offering a centralized marketplace for AI-powered digital labor. Designed for Agentblazers, developers, and Salesforce admins, this platform enables the rapid development and deployment of AI agents across industries. Email: [email protected] Phone: +1(630) 349 2411 Website: https://www.fexle.com/blogs/agentexchange-an-ultimate-guide-for-salesforce-consultants-businesses/?utm_source=slideshare&utm_medium=pptNg

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How to Batch Export Lotus Notes NSF Emails to Outlook PST Easily?steaveroggers

Migrating from Lotus Notes to Outlook can be a complex and time-consuming task, especially when dealing with large volumes of NSF emails. This presentation provides a complete guide on how to batch export Lotus Notes NSF emails to Outlook PST format quickly and securely. It highlights the challenges of manual methods, the benefits of using an automated tool, and introduces eSoftTools NSF to PST Converter Software — a reliable solution designed to handle bulk email migrations efficiently. Learn about the software’s key features, step-by-step export process, system requirements, and how it ensures 100% data accuracy and folder structure preservation during migration. Make your email transition smoother, safer, and faster with the right approach. Read More:- https://www.esofttools.com/nsf-to-pst-converter.html

How to Optimize Your AWS Environment for Improved Cloud PerformanceThousandEyes

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Secure Test Infrastructure: The Backbone of Trustworthy Software DevelopmentShubham Joshi

Adobe Marketo Engage Champion Deep Dive - SFDC CRM Synch V2 & Usage DashboardsBradBedford3

Join Ajay Sarpal and Miray Vu to learn about key Marketo Engage enhancements. Discover improved in-app Salesforce CRM connector statistics for easy monitoring of sync health and throughput. Explore new Salesforce CRM Synch Dashboards providing up-to-date insights into weekly activity usage, thresholds, and limits with drill-down capabilities. Learn about proactive notifications for both Salesforce CRM sync and product usage overages. Get an update on improved Salesforce CRM synch scale and reliability coming in Q2 2025. Key Takeaways: Improved Salesforce CRM User Experience: Learn how self-service visibility enhances satisfaction. Utilize Salesforce CRM Synch Dashboards: Explore real-time weekly activity data. Monitor Performance Against Limits: See threshold limits for each product level. Get Usage Over-Limit Alerts: Receive notifications for exceeding thresholds. Learn About Improved Salesforce CRM Scale: Understand upcoming cloud-based incremental sync.

Exceptional Behaviors: How Frequently Are They Tested? (AST 2025)Andre Hora

Exceptions allow developers to handle error cases expected to occur infrequently. Ideally, good test suites should test both normal and exceptional behaviors to catch more bugs and avoid regressions. While current research analyzes exceptions that propagate to tests, it does not explore other exceptions that do not reach the tests. In this paper, we provide an empirical study to explore how frequently exceptional behaviors are tested in real-world systems. We consider both exceptions that propagate to tests and the ones that do not reach the tests. For this purpose, we run an instrumented version of test suites, monitor their execution, and collect information about the exceptions raised at runtime. We analyze the test suites of 25 Python systems, covering 5,372 executed methods, 17.9M calls, and 1.4M raised exceptions. We find that 21.4% of the executed methods do raise exceptions at runtime. In methods that raise exceptions, on the median, 1 in 10 calls exercise exceptional behaviors. Close to 80% of the methods that raise exceptions do so infrequently, but about 20% raise exceptions more frequently. Finally, we provide implications for researchers and practitioners. We suggest developing novel tools to support exercising exceptional behaviors and refactoring expensive try/except blocks. We also call attention to the fact that exception-raising behaviors are not necessarily “abnormal” or rare.

Scaling GraphRAG: Efficient Knowledge Retrieval for Enterprise AIdanshalev

If we were building a GenAI stack today, we'd start with one question: Can your retrieval system handle multi-hop logic? Trick question, b/c most can’t. They treat retrieval as nearest-neighbor search. Today, we discussed scaling #GraphRAG at AWS DevOps Day, and the takeaway is clear: VectorRAG is naive, lacks domain awareness, and can’t handle full dataset retrieval. GraphRAG builds a knowledge graph from source documents, allowing for a deeper understanding of the data + higher accuracy.

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Microsoft AI Nonprofit Use Cases and Live Demo_2025.04.30.pdfTechSoup

In this webinar we will dive into the essentials of generative AI, address key AI concerns, and demonstrate how nonprofits can benefit from using Microsoft’s AI assistant, Copilot, to achieve their goals. This event series to help nonprofits obtain Copilot skills is made possible by generous support from Microsoft. What You’ll Learn in Part 2: Explore real-world nonprofit use cases and success stories. Participate in live demonstrations and a hands-on activity to see how you can use Microsoft 365 Copilot in your own work!

Automation Techniques in RPA - UiPath CertificateVICTOR MAESTRE RAMIREZ

Explaining GitHub Actions Failures with Large Language Models Challenges, In...ssuserb14185

GitHub Actions (GA) has become the de facto tool that developers use to automate software workflows, seamlessly building, testing, and deploying code. Yet when GA fails, it disrupts development, causing delays and driving up costs. Diagnosing failures becomes especially challenging because error logs are often long, complex and unstructured. Given these difficulties, this study explores the potential of large language models (LLMs) to generate correct, clear, concise, and actionable contextual descriptions (or summaries) for GA failures, focusing on developers’ perceptions of their feasibility and usefulness. Our results show that over 80% of developers rated LLM explanations positively in terms of correctness for simpler/small logs. Overall, our findings suggest that LLMs can feasibly assist developers in understanding common GA errors, thus, potentially reducing manual analysis. However, we also found that improved reasoning abilities are needed to support more complex CI/CD scenarios. For instance, less experienced developers tend to be more positive on the described context, while seasoned developers prefer concise summaries. Overall, our work offers key insights for researchers enhancing LLM reasoning, particularly in adapting explanations to user expertise. https://arxiv.org/abs/2501.16495

Not So Common Memory Leaks in Java WebinarTier1 app

This SlideShare presentation is from our May webinar, “Not So Common Memory Leaks & How to Fix Them?”, where we explored lesser-known memory leak patterns in Java applications. Unlike typical leaks, subtle issues such as thread local misuse, inner class references, uncached collections, and misbehaving frameworks often go undetected and gradually degrade performance. This deck provides in-depth insights into identifying these hidden leaks using advanced heap analysis and profiling techniques, along with real-world case studies and practical solutions. Ideal for developers and performance engineers aiming to deepen their understanding of Java memory management and improve application stability.

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