The document discusses code for a TODOs application that uses an SQLite database. It covers creating the database adapter and helper classes, writing methods to insert, update, and delete TODO items from the database, and retrieving data. It also discusses running the application and viewing TODO items, as well as the code for an activity to edit an individual TODO item.
Unilever - History, Evolution, Present and the FutureGreg Thain
A comprehensive background of Unilever containing its History and Origins, Early Evolution, Modern Business, Global Expansion, Company Structure, Recent Efforts and Company DNA. As one of the chapters of the book FMCG: The Power of Fast-Moving Consumer Goods by authors Greg Thain and John Bradley. For more details on their success story and that of other leading FMCG companies, check www.fmcgbook.com or Amazon http://amzn.to/1jRyd20.
Unilever - History, Evolution, Present and the FutureGreg Thain
A comprehensive background of Unilever containing its History and Origins, Early Evolution, Modern Business, Global Expansion, Company Structure, Recent Efforts and Company DNA. As one of the chapters of the book FMCG: The Power of Fast-Moving Consumer Goods by authors Greg Thain and John Bradley. For more details on their success story and that of other leading FMCG companies, check www.fmcgbook.com or Amazon http://amzn.to/1jRyd20.
Log Data Analysis Platform by Valentin KropovSoftServe
Log Data Analysis Platform is a completely automated system to ingest, process and store huge amount of log data based on Flume, Spark, Hadoop, Impala, Hive, ElasticSearch and Kibana.
Log Data Analysis Platform is a completely automated system to ingest, process and store huge amount of log data based on Flume, Spark, Hadoop, Impala, Hive, ElasticSearch and Kibana.
About us
BISP is an IT Training and Consulting Company. We are Subject Matter Experts for DHW and BI technologies. We provide Live virtual Online global IT support and services like online software training, live virtual online lab services, virtual online job support with highly intellectual professional trainers and skilled resources , predominantly In Oracle BI, Oracle Data Integrator, Hyperion Product stack, Oracle Middleware solution, Oracle SoA, AIA Informatica, IBM Datastage and IBM Cognos .
BISP has footprints virtually across USA, CANADA, UK, SINGAPORE, SAUDI ARABIA, AUSTRALIA and more by providing live virtual support services from India for fresh graduates, opt students, working professionals etc. Being a live virtual online training the support , training and service methodology is just click away considerably reducing your TIME,INFRASTRUCTURE and Cost effective.
About us
BISP is an IT Training and Consulting Company. We are Subject Matter Experts for DHW and BI technologies. We provide Live virtual Online global IT support and services like online software training, live virtual online lab services, virtual online job support with highly intellectual professional trainers and skilled resources , predominantly In Oracle BI, Oracle Data Integrator, Hyperion Product stack, Oracle Middleware solution, Oracle SoA, AIA Informatica, IBM Datastage and IBM Cognos .
BISP has footprints virtually across USA, CANADA, UK, SINGAPORE, SAUDI ARABIA, AUSTRALIA and more by providing live virtual support services from India for fresh graduates, opt students, working professionals etc. Being a live virtual online training the support , training and service methodology is just click away considerably reducing your TIME,INFRASTRUCTURE and Cost effective.
About us
BISP is an IT Training and Consulting Company. We are Subject Matter Experts for DHW and BI technologies. We provide Live virtual Online global IT support and services like online software training, live virtual online lab services, virtual online job support with highly intellectual professional trainers and skilled resources , predominantly In Oracle BI, Oracle Data Integrator, Hyperion Product stack, Oracle Middleware solution, Oracle SoA, AIA Informatica, IBM Datastage and IBM Cognos .
BISP has footprints virtually across USA, CANADA, UK, SINGAPORE, SAUDI ARABIA, AUSTRALIA and more by providing live virtual support services from India for fresh graduates, opt students, working professionals etc. Being a live virtual online training the support , training and service methodology is just click away considerably reducing your TIME,INFRASTRUCTURE and Cost effective.
All developers understand the theoretical value of unit testing, but with data driven applications, figuring out how to create tests can be hard. In this session, you will learn how to design and build a data layer that can be tested. We will introduce data layer architecture practices and methodologies that make testing possible, and cover the basics of unit test mocking. You will also be guided through various types of testing, including unit, integration, and functional testing. Leave this session with the basics needed to start creating tests for application data layers, including those powered by LinqToSQL and Entity Framework.
Data lineage has gained popularity in the Machine Learning community as a way to make models and datasets easier to interpret and to help developers debug their ML pipelines by enabling them to go from a model to the dataset/user who trained it. Data provenance and lineage is the process of building up the history of how a data artifact came to be. This history of derivations and interactions can provide a better context for data discovery, debugging, as well as auditing. In this area, others, such as Google and Databricks, have made small steps.
The Hopsworks approach presented provenance information is collected implicitly through the unobtrusive instrumentation of jupyter notebooks and python code - What we call 'implicit provenance'.
Hybrid Transactional & Analytical Processing are a new breed of database queries offered by NewSQL engines. This talk features key engine capabilities required to offer HTAP and state of the art of PostgreSQL 11 that aligns with an HTAP vision in terms of sharding, fault tolerance, high availability, and replication
Log Data Analysis Platform by Valentin KropovSoftServe
Log Data Analysis Platform is a completely automated system to ingest, process and store huge amount of log data based on Flume, Spark, Hadoop, Impala, Hive, ElasticSearch and Kibana.
Log Data Analysis Platform is a completely automated system to ingest, process and store huge amount of log data based on Flume, Spark, Hadoop, Impala, Hive, ElasticSearch and Kibana.
About us
BISP is an IT Training and Consulting Company. We are Subject Matter Experts for DHW and BI technologies. We provide Live virtual Online global IT support and services like online software training, live virtual online lab services, virtual online job support with highly intellectual professional trainers and skilled resources , predominantly In Oracle BI, Oracle Data Integrator, Hyperion Product stack, Oracle Middleware solution, Oracle SoA, AIA Informatica, IBM Datastage and IBM Cognos .
BISP has footprints virtually across USA, CANADA, UK, SINGAPORE, SAUDI ARABIA, AUSTRALIA and more by providing live virtual support services from India for fresh graduates, opt students, working professionals etc. Being a live virtual online training the support , training and service methodology is just click away considerably reducing your TIME,INFRASTRUCTURE and Cost effective.
About us
BISP is an IT Training and Consulting Company. We are Subject Matter Experts for DHW and BI technologies. We provide Live virtual Online global IT support and services like online software training, live virtual online lab services, virtual online job support with highly intellectual professional trainers and skilled resources , predominantly In Oracle BI, Oracle Data Integrator, Hyperion Product stack, Oracle Middleware solution, Oracle SoA, AIA Informatica, IBM Datastage and IBM Cognos .
BISP has footprints virtually across USA, CANADA, UK, SINGAPORE, SAUDI ARABIA, AUSTRALIA and more by providing live virtual support services from India for fresh graduates, opt students, working professionals etc. Being a live virtual online training the support , training and service methodology is just click away considerably reducing your TIME,INFRASTRUCTURE and Cost effective.
About us
BISP is an IT Training and Consulting Company. We are Subject Matter Experts for DHW and BI technologies. We provide Live virtual Online global IT support and services like online software training, live virtual online lab services, virtual online job support with highly intellectual professional trainers and skilled resources , predominantly In Oracle BI, Oracle Data Integrator, Hyperion Product stack, Oracle Middleware solution, Oracle SoA, AIA Informatica, IBM Datastage and IBM Cognos .
BISP has footprints virtually across USA, CANADA, UK, SINGAPORE, SAUDI ARABIA, AUSTRALIA and more by providing live virtual support services from India for fresh graduates, opt students, working professionals etc. Being a live virtual online training the support , training and service methodology is just click away considerably reducing your TIME,INFRASTRUCTURE and Cost effective.
All developers understand the theoretical value of unit testing, but with data driven applications, figuring out how to create tests can be hard. In this session, you will learn how to design and build a data layer that can be tested. We will introduce data layer architecture practices and methodologies that make testing possible, and cover the basics of unit test mocking. You will also be guided through various types of testing, including unit, integration, and functional testing. Leave this session with the basics needed to start creating tests for application data layers, including those powered by LinqToSQL and Entity Framework.
Data lineage has gained popularity in the Machine Learning community as a way to make models and datasets easier to interpret and to help developers debug their ML pipelines by enabling them to go from a model to the dataset/user who trained it. Data provenance and lineage is the process of building up the history of how a data artifact came to be. This history of derivations and interactions can provide a better context for data discovery, debugging, as well as auditing. In this area, others, such as Google and Databricks, have made small steps.
The Hopsworks approach presented provenance information is collected implicitly through the unobtrusive instrumentation of jupyter notebooks and python code - What we call 'implicit provenance'.
Hybrid Transactional & Analytical Processing are a new breed of database queries offered by NewSQL engines. This talk features key engine capabilities required to offer HTAP and state of the art of PostgreSQL 11 that aligns with an HTAP vision in terms of sharding, fault tolerance, high availability, and replication
Similar to Creating and working with databases in Android (20)
Common Java problems when developing with AndroidStephen Gilmore
For some, developing for the Android platform might provide their first experience of working with a complex, modern Java API. This may test your knowledge of the Java programming language, especially with regard to features such as generics. The Android APIs make use of generics throughout and so you will have to know how to create and handle generic classes.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
Climate Impact of Software Testing at Nordic Testing DaysKari Kakkonen
My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
GridMate - End to end testing is a critical piece to ensure quality and avoid...ThomasParaiso2
End to end testing is a critical piece to ensure quality and avoid regressions. In this session, we share our journey building an E2E testing pipeline for GridMate components (LWC and Aura) using Cypress, JSForce, FakerJS…
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
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.
1. A database example Running the application TODOs application code Inspecting the database Using LogCat
CS/SE Individual Practical
Stephen Gilmore
October 28, 2011
School of Informatics, University of Edinburgh
CS/SE Individual Practical
1 / 40
2. A database example Running the application TODOs application code Inspecting the database Using LogCat
A database example
Lars Vogel example: TODOs
CS/SE Individual Practical
2 / 40
3. A database example Running the application TODOs application code Inspecting the database Using LogCat
A database example
A database example
CS/SE Individual Practical
3 / 40
4. A database example Running the application TODOs application code Inspecting the database Using LogCat
A database example
TodoDatabaseAdapter
CS/SE Individual Practical
4 / 40
5. A database example Running the application TODOs application code Inspecting the database Using LogCat
A database example
TodoDatabaseHelper (onCreate())
CS/SE Individual Practical
5 / 40
6. A database example Running the application TODOs application code Inspecting the database Using LogCat
A database example
TodoDatabaseHelper (onUpgrade())
CS/SE Individual Practical
6 / 40
7. A database example Running the application TODOs application code Inspecting the database Using LogCat
A database example
TodoDatabaseAdapter (open(), close())
CS/SE Individual Practical
7 / 40
8. A database example Running the application TODOs application code Inspecting the database Using LogCat
A database example
The create, update, and delete methods
CS/SE Individual Practical
8 / 40
9. A database example Running the application TODOs application code Inspecting the database Using LogCat
A database example
The insert() method
CS/SE Individual Practical
9 / 40
10. A database example Running the application TODOs application code Inspecting the database Using LogCat
A database example
The update() method
CS/SE Individual Practical
10 / 40
11. A database example Running the application TODOs application code Inspecting the database Using LogCat
A database example
The delete() method
CS/SE Individual Practical
11 / 40
12. A database example Running the application TODOs application code Inspecting the database Using LogCat
A database example
Fetch data
CS/SE Individual Practical
12 / 40
13. A database example Running the application TODOs application code Inspecting the database Using LogCat
A database example
Create content values
CS/SE Individual Practical
13 / 40
14. A database example Running the application TODOs application code Inspecting the database Using LogCat
A database example
Resources
CS/SE Individual Practical
14 / 40
15. A database example Running the application TODOs application code Inspecting the database Using LogCat
Running the application
Running the TODOs application
CS/SE Individual Practical
15 / 40
16. A database example Running the application TODOs application code Inspecting the database Using LogCat
Running the application
Editing a TODO item
CS/SE Individual Practical
16 / 40
17. A database example Running the application TODOs application code Inspecting the database Using LogCat
Running the application
Setting category to “Urgent”
CS/SE Individual Practical
17 / 40
18. A database example Running the application TODOs application code Inspecting the database Using LogCat
TODOs application code
TodoDetails (imports)
.14.20.png
CS/SE Individual Practical
18 / 40
19. A database example Running the application TODOs application code Inspecting the database Using LogCat
TODOs application code
TodoDetails (onCreate)
.14.31.png
CS/SE Individual Practical
19 / 40
20. A database example Running the application TODOs application code Inspecting the database Using LogCat
TODOs application code
Graphical layout of todo edit.xml
.32.52.png CS/SE Individual Practical
20 / 40
21. A database example Running the application TODOs application code Inspecting the database Using LogCat
TODOs application code
Text of todo edit.xml
.32.48.png CS/SE Individual Practical
21 / 40
22. A database example Running the application TODOs application code Inspecting the database Using LogCat
TODOs application code
Outline of todo edit.xml
.32.48.png CS/SE Individual Practical
22 / 40
23. A database example Running the application TODOs application code Inspecting the database Using LogCat
TODOs application code
TodoDetails (populateFields)
.14.38.png
CS/SE Individual Practical
23 / 40
24. A database example Running the application TODOs application code Inspecting the database Using LogCat
TODOs application code
Save state, onPause, onResume
.14.48.png
CS/SE Individual Practical
24 / 40
25. A database example Running the application TODOs application code Inspecting the database Using LogCat
TODOs application code
Save state
.14.56.png
CS/SE Individual Practical
25 / 40
26. A database example Running the application TODOs application code Inspecting the database Using LogCat
TODOs application code
TodosOverview (onCreate)
.15.04.png
CS/SE Individual Practical
26 / 40
27. A database example Running the application TODOs application code Inspecting the database Using LogCat
TODOs application code
Options menu, item selected
.15.10.png
CS/SE Individual Practical
27 / 40
28. A database example Running the application TODOs application code Inspecting the database Using LogCat
TODOs application code
Options item selected
.15.22.png
CS/SE Individual Practical
28 / 40
29. A database example Running the application TODOs application code Inspecting the database Using LogCat
TODOs application code
Accessing the insert menu
CS/SE Individual Practical
29 / 40
30. A database example Running the application TODOs application code Inspecting the database Using LogCat
Inspecting the database
Dalvik Debug Monitor Server (DDMS)
.21.38.png
CS/SE Individual Practical
30 / 40
31. A database example Running the application TODOs application code Inspecting the database Using LogCat
Inspecting the database
File explorer in DDMS
CS/SE Individual Practical
31 / 40
32. A database example Running the application TODOs application code Inspecting the database Using LogCat
Inspecting the database
/data/data/de.vogella.android.todos/...
CS/SE Individual Practical
32 / 40
33. A database example Running the application TODOs application code Inspecting the database Using LogCat
Inspecting the database
Pulling a file from the device
CS/SE Individual Practical
33 / 40
34. A database example Running the application TODOs application code Inspecting the database Using LogCat
Inspecting the database
Pulling a file from the device
CS/SE Individual Practical
34 / 40
35. A database example Running the application TODOs application code Inspecting the database Using LogCat
Inspecting the database
Get the device file
CS/SE Individual Practical
35 / 40
36. A database example Running the application TODOs application code Inspecting the database Using LogCat
Inspecting the database
Inspecting the file with sqlite3
CS/SE Individual Practical
36 / 40
37. A database example Running the application TODOs application code Inspecting the database Using LogCat
Inspecting the database
Inspecting the file with sqlite3 on DiCE
CS/SE Individual Practical
37 / 40
38. A database example Running the application TODOs application code Inspecting the database Using LogCat
Using LogCat
Debugs and errors displayed in LogCat
.22.45.png
CS/SE Individual Practical
38 / 40
39. A database example Running the application TODOs application code Inspecting the database Using LogCat
Using LogCat
Can filter messages displayed in LogCat
.34.51.png
CS/SE Individual Practical
39 / 40
40. A database example Running the application TODOs application code Inspecting the database Using LogCat
Using LogCat
Can use view menu to export messages
.40.30.png
CS/SE Individual Practical
40 / 40