The purpose of types:
To define what the program should do.
e.g. read an array of integers and return a double
To guarantee that the program is meaningful.
that it does not add a string to an integer
that variables are declared before they are used
To document the programmer's intentions.
better than comments, which are not checked by the compiler
To optimize the use of hardware.
reserve the minimal amount of memory, but not more
use the most appropriate machine instructions.
The purpose of types:
To define what the program should do.
e.g. read an array of integers and return a double
To guarantee that the program is meaningful.
that it does not add a string to an integer
that variables are declared before they are used
To document the programmer's intentions.
better than comments, which are not checked by the compiler
To optimize the use of hardware.
reserve the minimal amount of memory, but not more
use the most appropriate machine instructions.
Content of slide
Tree
Binary tree Implementation
Binary Search Tree
BST Operations
Traversal
Insertion
Deletion
Types of BST
Complexity in BST
Applications of BST
Lecture 4 principles of parallel algorithm design updatedVajira Thambawita
The main principles of parallel algorithm design are discussed here. For more information: visit, https://sites.google.com/view/vajira-thambawita/leaning-materials
WHAT IS DICTIONARY IN PYTHON?
HOW TO CREATE A DICTIONARY
INITIALIZE THE DICTIONARY
ACCESSING KEYS AND VALUES FROM A DICTIONARY
LOOPS TO DISPLAY KEYS AND VALUES IN A DICTIONARY
METHODS IN A DICTIONARY
TO WATCH VIDEO OR PDF:
https://computerassignmentsforu.blogspot.com/p/dictinpyxii.html
This course is all about the data mining that how we get the optimized results. it included with all types and how we use these techniques.This course is all about the data mining that how we get the optimized results. it included with all types and how we use these techniques.This course is all about the data mining that how we get the optimized results. it included with all types and how we use these techniques.This course is all about the data mining that how we get the optimized results. it included with all types and how we use these techniques.This course is all about the data mining that how we get the optimized results. it included with all types and how we use these techniques
Run-Time Environments: Storage organization, Stack Allocation of Space, Access to Nonlocal Data on the Stack, Heap Management, Introduction to Garbage Collection, Introduction to Trace-Based Collection. Code Generation: Issues in the Design of a Code Generator, The Target Language, Addresses in the Target Code, Basic Blocks and Flow Graphs, Optimization of Basic Blocks, A Simple Code Generator, Peephole Optimization, Register Allocation and Assignment, Dynamic Programming Code-Generation
Content of slide
Tree
Binary tree Implementation
Binary Search Tree
BST Operations
Traversal
Insertion
Deletion
Types of BST
Complexity in BST
Applications of BST
Lecture 4 principles of parallel algorithm design updatedVajira Thambawita
The main principles of parallel algorithm design are discussed here. For more information: visit, https://sites.google.com/view/vajira-thambawita/leaning-materials
WHAT IS DICTIONARY IN PYTHON?
HOW TO CREATE A DICTIONARY
INITIALIZE THE DICTIONARY
ACCESSING KEYS AND VALUES FROM A DICTIONARY
LOOPS TO DISPLAY KEYS AND VALUES IN A DICTIONARY
METHODS IN A DICTIONARY
TO WATCH VIDEO OR PDF:
https://computerassignmentsforu.blogspot.com/p/dictinpyxii.html
This course is all about the data mining that how we get the optimized results. it included with all types and how we use these techniques.This course is all about the data mining that how we get the optimized results. it included with all types and how we use these techniques.This course is all about the data mining that how we get the optimized results. it included with all types and how we use these techniques.This course is all about the data mining that how we get the optimized results. it included with all types and how we use these techniques.This course is all about the data mining that how we get the optimized results. it included with all types and how we use these techniques
Run-Time Environments: Storage organization, Stack Allocation of Space, Access to Nonlocal Data on the Stack, Heap Management, Introduction to Garbage Collection, Introduction to Trace-Based Collection. Code Generation: Issues in the Design of a Code Generator, The Target Language, Addresses in the Target Code, Basic Blocks and Flow Graphs, Optimization of Basic Blocks, A Simple Code Generator, Peephole Optimization, Register Allocation and Assignment, Dynamic Programming Code-Generation
Compiler Construction
Phases of a compiler
Analysis and synthesis phases
-------------------
-> Compilation Issues
-> Phases of compilation
-> Structure of compiler
-> Code Analysis
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The Metaverse and AI: how can decision-makers harness the Metaverse for their...Jen Stirrup
The Metaverse is popularized in science fiction, and now it is becoming closer to being a part of our daily lives through the use of social media and shopping companies. How can businesses survive in a world where Artificial Intelligence is becoming the present as well as the future of technology, and how does the Metaverse fit into business strategy when futurist ideas are developing into reality at accelerated rates? How do we do this when our data isn't up to scratch? How can we move towards success with our data so we are set up for the Metaverse when it arrives?
How can you help your company evolve, adapt, and succeed using Artificial Intelligence and the Metaverse to stay ahead of the competition? What are the potential issues, complications, and benefits that these technologies could bring to us and our organizations? In this session, Jen Stirrup will explain how to start thinking about these technologies as an organisation.
Observability Concepts EVERY Developer Should Know -- DeveloperWeek Europe.pdfPaige Cruz
Monitoring and observability aren’t traditionally found in software curriculums and many of us cobble this knowledge together from whatever vendor or ecosystem we were first introduced to and whatever is a part of your current company’s observability stack.
While the dev and ops silo continues to crumble….many organizations still relegate monitoring & observability as the purview of ops, infra and SRE teams. This is a mistake - achieving a highly observable system requires collaboration up and down the stack.
I, a former op, would like to extend an invitation to all application developers to join the observability party will share these foundational concepts to build on:
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Essentials of Automations: The Art of Triggers and Actions in FMESafe Software
In this second installment of our Essentials of Automations webinar series, we’ll explore the landscape of triggers and actions, guiding you through the nuances of authoring and adapting workspaces for seamless automations. Gain an understanding of the full spectrum of triggers and actions available in FME, empowering you to enhance your workspaces for efficient automation.
We’ll kick things off by showcasing the most commonly used event-based triggers, introducing you to various automation workflows like manual triggers, schedules, directory watchers, and more. Plus, see how these elements play out in real scenarios.
Whether you’re tweaking your current setup or building from the ground up, this session will arm you with the tools and insights needed to transform your FME usage into a powerhouse of productivity. Join us to discover effective strategies that simplify complex processes, enhancing your productivity and transforming your data management practices with FME. Let’s turn complexity into clarity and make your workspaces work wonders!
Welcome to the first live UiPath Community Day Dubai! Join us for this unique occasion to meet our local and global UiPath Community and leaders. You will get a full view of the MEA region's automation landscape and the AI Powered automation technology capabilities of UiPath. Also, hosted by our local partners Marc Ellis, you will enjoy a half-day packed with industry insights and automation peers networking.
📕 Curious on our agenda? Wait no more!
10:00 Welcome note - UiPath Community in Dubai
Lovely Sinha, UiPath Community Chapter Leader, UiPath MVPx3, Hyper-automation Consultant, First Abu Dhabi Bank
10:20 A UiPath cross-region MEA overview
Ashraf El Zarka, VP and Managing Director MEA, UiPath
10:35: Customer Success Journey
Deepthi Deepak, Head of Intelligent Automation CoE, First Abu Dhabi Bank
11:15 The UiPath approach to GenAI with our three principles: improve accuracy, supercharge productivity, and automate more
Boris Krumrey, Global VP, Automation Innovation, UiPath
12:15 To discover how Marc Ellis leverages tech-driven solutions in recruitment and managed services.
Brendan Lingam, Director of Sales and Business Development, Marc Ellis
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Generative AI Deep Dive: Advancing from Proof of Concept to ProductionAggregage
Join Maher Hanafi, VP of Engineering at Betterworks, in this new session where he'll share a practical framework to transform Gen AI prototypes into impactful products! He'll delve into the complexities of data collection and management, model selection and optimization, and ensuring security, scalability, and responsible use.
Alt. GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using ...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
A tale of scale & speed: How the US Navy is enabling software delivery from l...sonjaschweigert1
Rapid and secure feature delivery is a goal across every application team and every branch of the DoD. The Navy’s DevSecOps platform, Party Barge, has achieved:
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- Improved developer experience and productivity through actionable findings and reduction of false positives
- Maintenance of superior security standards and inherent policy enforcement with Authorization to Operate (ATO)
Development teams can ship efficiently and ensure applications are cyber ready for Navy Authorizing Officials (AOs). In this webinar, Sigma Defense and Anchore will give attendees a look behind the scenes and demo secure pipeline automation and security artifacts that speed up application ATO and time to production.
We will cover:
- How to remove silos in DevSecOps
- How to build efficient development pipeline roles and component templates
- How to deliver security artifacts that matter for ATO’s (SBOMs, vulnerability reports, and policy evidence)
- How to streamline operations with automated policy checks on container images
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Elizabeth Buie - Older adults: Are we really designing for our future selves?
Ch6
1. Static Checking and Type Systems Chapter 6 COP5621 Compiler Construction Copyright Robert van Engelen, Florida State University, 2007-2009
2. The Structure of our Compiler Revisited Lexical analyzer Syntax-directed static checker Character stream Token stream Java bytecode Yacc specification JVM specification Lex specification Syntax-directed translator Type checking Code generation
3.
4.
5. Type Checks, Overloading, Coercion, and Polymorphism int op(int), op(float); int f(float); int a, c[10], d; d = c+d; // FAIL *d = a; // FAIL a = op(d); // OK: overloading (C++) a = f(d); // OK: coersion of d to float vector<int> v; // OK: template instantiation
6. Flow-of-Control Checks myfunc() { … break; // ERROR } myfunc() { … switch (a) { case 0: … break; // OK case 1: … } } myfunc() { … while (n) { … if (i>10) break; // OK } }
7. Uniqueness Checks myfunc() { int i, j, i; // ERROR … } cnufym(int a, int a) // ERROR { … } struct myrec { int name; }; struct myrec // ERROR { int id; };
8. Name-Related Checks LoopA: for (int I = 0; I < n; I++) { … if (a[I] == 0) break LoopB; // Java labeled loop … }
9.
10.
11. Graph Representations for Type Expressions int *f(char*,char*) fun args pointer char int pointer char pointer Tree forms fun args pointer char int pointer DAGs
12. Cyclic Graph Representations struct Node { int val; struct Node *next; }; struct val pointer int Internal compiler representation of the Node type: cyclic graph next Source program
13.
14.
15.
16. Constructing Type Graphs in Yacc Type *mkint() construct int node if not already constructed Type *mkarr(Type*,int) construct array-of-type node if not already constructed Type *mkptr(Type*) construct pointer-of-type node if not already constructed
17. Syntax-Directed Definitions for Constructing Type Graphs in Yacc %union { Symbol *sym; int num; Type *typ; } %token INT %token <sym> ID %token <int> NUM %type <typ> type %% decl : type ID { addtype($2, $1); } | type ID ‘[’ NUM ‘]’ { addtype($2, mkarr($1, $4)); } ; type : INT { $$ = mkint(); } | type ‘*’ { $$ = mkptr($1); } | /* empty */ { $$ = mkint(); } ;
18.
19. Type Rules in Post System Notation e 1 : integer e 2 : integer e 1 + e 2 : integer Type judgments e : where e is an expression and is a type Environment maps objects v to types : ( v ) = ( v ) = v : e : v := e : void ( v ) =
20. Type System Example y + 2 : integer x := y + 2 : void Environment is a set of name , type pairs, for example: = { x , integer , y , integer , z , char , 1, integer , 2, integer } From and rules we can check types: type checking = theorem proving The proof that x := y + 2 is typed correctly: ( y ) = integer y : integer ( x ) = integer ( 2 ) = integer 2 : integer
21. A Simple Language Example P D ; S D D ; D id : T T boolean char integer array [ num ] of T ^ T S id := E if E then S while E do S S ; S E true false literal num id E and E E + E E [ E ] E ^ Pascal-like pointer dereference operator Pointer to T
22. Simple Language Example: Declarations D id : T { addtype ( id .entry, T .type) } T boolean { T .type := boolean } T char { T .type := char } T integer { T .type := integer } T array [ num ] of T 1 { T .type := array (1.. num .val, T 1 .type) } T ^ T 1 { T .type := pointer ( T 1 ) Parametric types: type constructor
23. Simple Language Example: Checking Statements S id := E { S .type := if id .type = E .type then void else type_error } e : v := e : void ( v ) = Note: the type of id is determined by scope’s environment: id .type = lookup ( id .entry)
24. Simple Language Example: Checking Statements (cont’d) S if E then S 1 { S .type := if E .type = boolean then S 1 .type else type_error } s : if e then s : e : boolean
25. Simple Language Example: Statements (cont’d) S while E do S 1 { S .type := if E .type = boolean then S 1 .type else type_error } s : while e do s : e : boolean
26. Simple Language Example: Checking Statements (cont’d) S S 1 ; S 2 { S .type := if S 1 .type = void and S 2 .type = void then void else type_error } s 2 : void s 1 ; s 2 : void s 1 : void
27. Simple Language Example: Checking Expressions E true { E .type = boolean } E false { E .type = boolean } E literal { E .type = char } E num { E .type = integer } E id { E .type = lookup ( id .entry) } … ( v ) = v :
28. Simple Language Example: Checking Expressions (cont’d) E E 1 + E 2 { E .type := if E 1 .type = integer and E 2 .type = integer then integer else type_error } e 1 : integer e 2 : integer e 1 + e 2 : integer
29. Simple Language Example: Checking Expressions (cont’d) E E 1 and E 2 { E .type := if E 1 .type = boolean and E 2 .type = boolean then boolean else type_error } e 1 : boolean e 2 : boolean e 1 and e 2 : boolean
30. Simple Language Example: Checking Expressions (cont’d) E E 1 [ E 2 ] { E .type := if E 1 .type = array ( s , t ) and E 2 .type = integer then t else type_error } e 1 : array ( s , ) e 2 : integer e 1 [ e 2 ] :
31. Simple Language Example: Checking Expressions (cont’d) E E 1 ^ { E .type := if E 1 .type = pointer ( t ) then t else type_error } e : pointer ( ) e ^ :
32. A Simple Language Example: Functions T T -> T E E ( E ) Example: v : integer; odd : integer -> boolean; if odd(3) then v := 1; Function type declaration Function call
33. Simple Language Example: Function Declarations T T 1 -> T 2 { T .type := function ( T 1 .type, T 2 .type) } Parametric type: type constructor
34. Simple Language Example: Checking Function Invocations E E 1 ( E 2 ) { E .type := if E 1 .type = function ( s , t ) and E 2 .type = s then t else type_error } e 1 : function ( , ) e 2 : e 1 ( e 2 ) :
35.
36. Syntax-Directed Definitions for Type Checking in Yacc %{ enum Types {Tint, Tfloat, Tpointer, Tarray, … }; typedef struct Type { enum Types type; struct Type *child; // at most one type parameter } Type; %} %union { Type *typ; } %type <typ> expr %% …
37. Syntax-Directed Definitions for Type Checking in Yacc (cont’d) … %% expr : expr ‘+’ expr { if ($1->type != Tint || $3->type != Tint) semerror(“non-int operands in +”); $$ = mkint(); emit(iadd); }
44. Example Type Inference Append concatenates two lists recursively: fun append ( x, y ) = if null ( x ) then y else cons ( hd ( x ) , append ( tl ( x ), y )) where null : ∀α.list(α) -> bool hd : ∀α.list(α) -> α tl : ∀α.list(α) -> list(α) cons : ∀α.(α × list(α)) -> list(α)
45. Example Type Inference fun append ( x, y ) = if null ( x ) then y else cons ( hd ( x ) , append ( tl ( x ), y )) The type of append : ∀ σ ,τ, φ . ( σ × τ) -> φ is: type of x : σ = list(α 1 ) from null ( x ) type of y : τ = φ from append ’s return type return type of append : list(α 2 ) from return type of cons and α 1 = α 2 because cons ( hd(x), append ( tl ( x ), y )) : list(α 2 ) hd ( x ) : α 1 x : list(α 1 ) append ( tl ( x ) , y ) : list(α 1 ) tl ( x ) : list(α 1 ) y : list(α 1 ) x : list(α 1 )
46. Example Type Inference fun append ( x, y ) = if null ( x ) then y else cons ( hd ( x ) , append ( tl ( x ), y )) The type of append : ∀ σ ,τ, φ . ( σ × τ) -> φ is: σ = list(α) τ = φ = list(α) Hence, append : ∀α.(list(α) × list(α)) -> list(α)