Asp.net c# mvc Training-Day-5 of Day-9

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The document discusses LINQ (Language Integrated Query), which provides a uniform query syntax in C# and VB.NET to retrieve data from different sources. LINQ allows querying of objects, XML documents, SQL databases, and other data formats using the same basic coding patterns. It offers benefits like a familiar language, less coding, readable code, standardized querying across sources, compile-time type safety, and IntelliSense support. The document covers LINQ query syntax, method syntax using lambda expressions, standard query operators like Where, OrderBy, GroupBy, Join, and Aggregate functions. Examples are provided of LINQ queries and expression trees.

AHM Pervej Kabir
Analyst Programmer
pervej_kabir@yahoo.com
Cell:+8801757051005 Day-5: 18 October 2017
ASP.Net C#- MVC-5 Training

Introduction
 What is LINQ?
Why LINQ?
LINQ Query & Method Syntax
Anatomy of the Lambda Expression
Standard Query Operators:
Expression in LINQ
Expression Tree
Immediate Execution of LINQ Query
let & into keyword
Sample LINQ Queries

 What Is LINQ
LINQ (Language Integrated Query) is uniform query syntax in C# and VB.NET used to save and retrieve data from
different sources. It is integrated in C# or VB, thereby eliminating the mismatch between programming languages and
databases, as well as providing a single querying interface for different types of data sources.
 For example, SQL is a Structured Query Language used to save and retrieve data from a database. In the same
way, LINQ is a structured query syntax built in C# and VB.NET used to save and retrieve data from different types
of data sources like an Object Collection, SQL server database, XML, web service etc.
 LINQ always works with objects so you can use the same basic coding patterns to query and transform data in
XML documents, SQL databases, ADO.NET Datasets, .NET collections, and any other format for which a LINQ
provider is available.

 Why LINQ?
 Familiar language: Developers don’t have to learn a new query language for each type of
data source or data format.
 Less coding: It reduces the amount of code to be written as compared with a more
traditional approach.
 Readable code: LINQ makes the code more readable so other developers can easily
understand and maintain it.
 Standardized way of querying multiple data sources: The same LINQ syntax can be
used to query multiple data sources.
 Compile time safety of queries: It provides type checking of objects at compile time.
 IntelliSense Support: LINQ provides IntelliSense for generic collections.
 Shaping data: You can retrieve data in different shapes.

C# 3.0(.NET 3.5) introduced the lambda expression along with LINQ.
Example:
Lamda Expression:

 Standard Query Operators in query
 Standard Query Operators in Method

 Where Clause:
 Where Extension Method:

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Mastering Fluent Bit: Ultimate Guide to Integrating Telemetry Pipelines with ...Eric D. Schabell

It's time you stopped letting your telemetry data pressure your budgets and get in the way of solving issues with agility! No more I say! Take back control of your telemetry data as we guide you through the open source project Fluent Bit. Learn how to manage your telemetry data from source to destination using the pipeline phases covering collection, parsing, aggregation, transformation, and forwarding from any source to any destination. Buckle up for a fun ride as you learn by exploring how telemetry pipelines work, how to set up your first pipeline, and exploring several common use cases that Fluent Bit helps solve. All this backed by a self-paced, hands-on workshop that attendees can pursue at home after this session (https://o11y-workshops.gitlab.io/workshop-fluentbit).

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Copy & Link Here 👉👉 http://drfiles.net/ Adobe Illustrator is a vector graphics editor and design software, developed and marketed by Adobe, used for creating logos, icons, illustrations, and other graphics that can be scaled without loss of quality. It's a powerful tool for graphic designers, web designers, and artists who need to create crisp, scalable artwork for various applications like print, web, and mobile.

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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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.

Meet the Agents: How AI Is Learning to Think, Plan, and CollaborateMaxim Salnikov

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.

Mastering OOP: Understanding the Four Core PillarsMarcel David

Visit for updated note: https://www.notion.so/Four-Pillars-of-Object-Oriented-Programming-OOP-1e2d7d9612808079b7c5f938afd62a7b?pvs=4 Dive into the essential concepts of Object-Oriented Programming (OOP) with a detailed explanation of its four key pillars: Encapsulation, Inheritance, Polymorphism, and Abstraction. Understand how these principles contribute to robust, maintainable, and scalable software development.

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