Protractor training

Oct 16, 2015Download as PPTX, PDF1 like898 views

This document discusses end-to-end testing with Protractor.js. It introduces Protractor and describes how it can be used to test Angular applications directly within browsers using WebDriverJS. It also discusses best practices like using page object patterns to organize tests and hide implementation details. Key aspects covered include setting up tests, writing maintainable page objects, and decomposing pages into reusable sections and fields.

Protractor.js
End to End testing
Global Logic

Lets Learn
Bad
Experience
BE
Reflection
R
Theoretical
Base
TB
Practice
P

Fairy Tail about karma
Huge tests
No
Agreements
No
Abstractions
“Should”
Copy/Paste

How it connects
Tests
Jasmine
Protractor
Web
DriverJS
Explorer
Mozilla
Firefox
Google
Chrome
Selenium
InternetNode.js

Node.js
• Blocks execution
• Runs immediately and
return result
• Good for working with data
in memory
Synchronous
• Adds new event in the loop
• Runs after all synchronous
operations are executed.
• Good for heavy operations
like database or filesystem
access
Asynchronous

Promise
asynchrony
try/catch
map
chaining
Abstraction of asynchrony

Why does it look syncronous?
W
C O N T R O L
L
F

Protractor provides...
2
3
4
5
ElemenFinder1
ElementArrayFinder
Waiters for Angular $http and $timeout
Mock modules
Search by css, xpath, repeater, etc

Page Object pattern
2
3
4
5
Hides implementation details1
Maintainable
Reusable
Simplify tests
Extendable

Keep in mind
If you have WebDriver APIs in your test
methods, You're Doing It Wrong
© Simon Stewart

Section methods
2
3
4
5
field(name)1
hasErrorOn(fieldName)
ensure(state, expected).otherwise(act)
try(action)
errorFor(fieldName)

OK, but how to organize code?
test/e2e
├── config
├── lib
│ ├── section
│ │ ├── behavior
│ │ └── field
│ ├── page.js
│ └── section.js
├── features
│ ├── login
│ └── channels
├── shared-specs
│ ├── toolbars
│ └── validators
└── support
└── login.js

What we have learned
Simplicity is prerequisite of reliability
© Edsger Dijkstra

Sergii Stotskyi
sergiy.stotskiy@gmail.com
Any questions?
??

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Fluid mechanics is the branch of physics concerned with the mechanics of fluids (liquids, gases, and plasmas) and the forces on them. Originally applied to water (hydromechanics), it found applications in a wide range of disciplines, including mechanical, aerospace, civil, chemical, and biomedical engineering, as well as geophysics, oceanography, meteorology, astrophysics, and biology. It can be divided into fluid statics, the study of various fluids at rest, and fluid dynamics. Fluid statics, also known as hydrostatics, is the study of fluids at rest, specifically when there's no relative motion between fluid particles. It focuses on the conditions under which fluids are in stable equilibrium and doesn't involve fluid motion. Fluid kinematics is the branch of fluid mechanics that focuses on describing and analyzing the motion of fluids, such as liquids and gases, without considering the forces that cause the motion. It deals with the geometrical and temporal aspects of fluid flow, including velocity and acceleration. Fluid dynamics, on the other hand, considers the forces acting on the fluid. Fluid dynamics is the study of the effect of forces on fluid motion. It is a branch of continuum mechanics, a subject which models matter without using the information that it is made out of atoms; that is, it models matter from a macroscopic viewpoint rather than from microscopic. Fluid mechanics, especially fluid dynamics, is an active field of research, typically mathematically complex. Many problems are partly or wholly unsolved and are best addressed by numerical methods, typically using computers. A modern discipline, called computational fluid dynamics (CFD), is devoted to this approach. Particle image velocimetry, an experimental method for visualizing and analyzing fluid flow, also takes advantage of the highly visual nature of fluid flow. Fundamentally, every fluid mechanical system is assumed to obey the basic laws : Conservation of mass Conservation of energy Conservation of momentum The continuum assumption For example, the assumption that mass is conserved means that for any fixed control volume (for example, a spherical volume)—enclosed by a control surface—the rate of change of the mass contained in that volume is equal to the rate at which mass is passing through the surface from outside to inside, minus the rate at which mass is passing from inside to outside. This can be expressed as an equation in integral form over the control volume. The continuum assumption is an idealization of continuum mechanics under which fluids can be treated as continuous, even though, on a microscopic scale, they are composed of molecules. Under the continuum assumption, macroscopic (observed/measurable) properties such as density, pressure, temperature, and bulk velocity are taken to be well-defined at "infinitesimal" volume elements—small in comparison to the characteristic length scale of the system, but large in comparison to molecular length scale

Raish Khanji GTU 8th sem Internship Report.pdfRaishKhanji

This report details the practical experiences gained during an internship at Indo German Tool Room, Ahmedabad. The internship provided hands-on training in various manufacturing technologies, encompassing both conventional and advanced techniques. Significant emphasis was placed on machining processes, including operation and fundamental understanding of lathe and milling machines. Furthermore, the internship incorporated modern welding technology, notably through the application of an Augmented Reality (AR) simulator, offering a safe and effective environment for skill development. Exposure to industrial automation was achieved through practical exercises in Programmable Logic Controllers (PLCs) using Siemens TIA software and direct operation of industrial robots utilizing teach pendants. The principles and practical aspects of Computer Numerical Control (CNC) technology were also explored. Complementing these manufacturing processes, the internship included extensive application of SolidWorks software for design and modeling tasks. This comprehensive practical training has provided a foundational understanding of key aspects of modern manufacturing and design, enhancing the technical proficiency and readiness for future engineering endeavors.

Mathematical foundation machine learning.pdfTalhaShahid49

IntroSlides-April-BuildWithAI-VertexAI.pdfLuiz Carneiro

Development of MLR, ANN and ANFIS Models for Estimation of PCUs at Different ...Journal of Soft Computing in Civil Engineering

Passenger car unit (PCU) of a vehicle type depends on vehicular characteristics, stream characteristics, roadway characteristics, environmental factors, climate conditions and control conditions. Keeping in view various factors affecting PCU, a model was developed taking a volume to capacity ratio and percentage share of particular vehicle type as independent parameters. A microscopic traffic simulation model VISSIM has been used in present study for generating traffic flow data which some time very difficult to obtain from field survey. A comparison study was carried out with the purpose of verifying when the adaptive neuro-fuzzy inference system (ANFIS), artificial neural network (ANN) and multiple linear regression (MLR) models are appropriate for prediction of PCUs of different vehicle types. From the results observed that ANFIS model estimates were closer to the corresponding simulated PCU values compared to MLR and ANN models. It is concluded that the ANFIS model showed greater potential in predicting PCUs from v/c ratio and proportional share for all type of vehicles whereas MLR and ANN models did not perform well.

QA/QC Manager (Quality management Expert)rccbatchplant

Smart_Storage_Systems_Production_Engineering.pptxrushikeshnavghare94

ELectronics Boards & Product Testing_Shiju.pdfShiju Jacob

ADVXAI IN MALWARE ANALYSIS FRAMEWORK: BALANCING EXPLAINABILITY WITH SECURITYijscai

With the increased use of Artificial Intelligence (AI) in malware analysis there is also an increased need to understand the decisions models make when identifying malicious artifacts. Explainable AI (XAI) becomes the answer to interpreting the decision-making process that AI malware analysis models use to determine malicious benign samples to gain trust that in a production environment, the system is able to catch malware. With any cyber innovation brings a new set of challenges and literature soon came out about XAI as a new attack vector. Adversarial XAI (AdvXAI) is a relatively new concept but with AI applications in many sectors, it is crucial to quickly respond to the attack surface that it creates. This paper seeks to conceptualize a theoretical framework focused on addressing AdvXAI in malware analysis in an effort to balance explainability with security. Following this framework, designing a machine with an AI malware detection and analysis model will ensure that it can effectively analyze malware, explain how it came to its decision, and be built securely to avoid adversarial attacks and manipulations. The framework focuses on choosing malware datasets to train the model, choosing the AI model, choosing an XAI technique, implementing AdvXAI defensive measures, and continually evaluating the model. This framework will significantly contribute to automated malware detection and XAI efforts allowing for secure systems that are resilient to adversarial attacks.

introduction to machine learining for beginersJoydebSheet

Artificial Intelligence (AI) basics.pptxaditichinar

International Journal of Distributed and Parallel systems (IJDPS)samueljackson3773

The growth of Internet and other web technologies requires the development of new algorithms and architectures for parallel and distributed computing. International journal of Distributed and parallel systems is a bimonthly open access peer-reviewed journal aims to publish high quality scientific papers arising from original research and development from the international community in the areas of parallel and distributed systems. IJDPS serves as a platform for engineers and researchers to present new ideas and system technology, with an interactive and friendly, but strongly professional atmosphere.

new ppt artificial intelligence historyyyPianoPianist

Oil-gas_Unconventional oil and gass_reseviours.pdfM7md3li2

"Boiler Feed Pump (BFP): Working, Applications, Advantages, and Limitations E...Infopitaara

A Boiler Feed Pump (BFP) is a critical component in thermal power plants. It supplies high-pressure water (feedwater) to the boiler, ensuring continuous steam generation. ⚙️ How a Boiler Feed Pump Works Water Collection: Feedwater is collected from the deaerator or feedwater tank. Pressurization: The pump increases water pressure using multiple impellers/stages in centrifugal types. Discharge to Boiler: Pressurized water is then supplied to the boiler drum or economizer section, depending on design. 🌀 Types of Boiler Feed Pumps Centrifugal Pumps (most common): Multistage for higher pressure. Used in large thermal power stations. Positive Displacement Pumps (less common): For smaller or specific applications. Precise flow control but less efficient for large volumes. 🛠️ Key Operations and Controls Recirculation Line: Protects the pump from overheating at low flow. Throttle Valve: Regulates flow based on boiler demand. Control System: Often automated via DCS/PLC for variable load conditions. Sealing & Cooling Systems: Prevent leakage and maintain pump health. ⚠️ Common BFP Issues Cavitation due to low NPSH (Net Positive Suction Head). Seal or bearing failure. Overheating from improper flow or recirculation.

Explainable-Artificial-Intelligence-XAI-A-Deep-Dive (1).pptxMahaveerVPandit

Metal alkyne complexes.pptx in chemistrymee23nu

"Feed Water Heaters in Thermal Power Plants: Types, Working, and Efficiency G...Infopitaara

Smart Storage Solutions.pptx for production engineeringrushikeshnavghare94

DSP and MV the Color image processing.pptHafizAhamed8

Introduction to FLUID MECHANICS & KINEMATICSnarayanaswamygdas

Raish Khanji GTU 8th sem Internship Report.pdfRaishKhanji

Mathematical foundation machine learning.pdfTalhaShahid49

IntroSlides-April-BuildWithAI-VertexAI.pdfLuiz Carneiro

Development of MLR, ANN and ANFIS Models for Estimation of PCUs at Different ...Journal of Soft Computing in Civil Engineering

QA/QC Manager (Quality management Expert)rccbatchplant

Smart_Storage_Systems_Production_Engineering.pptxrushikeshnavghare94

ELectronics Boards & Product Testing_Shiju.pdfShiju Jacob

ADVXAI IN MALWARE ANALYSIS FRAMEWORK: BALANCING EXPLAINABILITY WITH SECURITYijscai

introduction to machine learining for beginersJoydebSheet

Artificial Intelligence (AI) basics.pptxaditichinar

International Journal of Distributed and Parallel systems (IJDPS)samueljackson3773

new ppt artificial intelligence historyyyPianoPianist

Oil-gas_Unconventional oil and gass_reseviours.pdfM7md3li2

"Boiler Feed Pump (BFP): Working, Applications, Advantages, and Limitations E...Infopitaara