This document outlines a project to automate the continuous integration of a software project using CruiseControl. It describes configuring CruiseControl to monitor the project's source code repository for changes, automatically build and test the project on each change, and publish the results. The key steps are to define a CruiseControl configuration file to specify the project details, build schedule, and publishers for notifications and artifacts. The build process is also automated using Ant build scripts. This allows validating and testing the project on each code change to catch issues early and monitor code quality over time.
Unit V
STAFFING IN SOFTWARE PROJECTS
Managing people – Organizational behavior – Best methods of staff selection – Motivation – The Oldham-Hackman job characteristic model – Ethical and Programmed concerns – Working in teams – Decision making – Team structures – Virtual teams – Communications genres – Communication plans.
Phing - A PHP Build Tool (An Introduction)Michiel Rook
PHing Is Not GNU make; it's a PHP project build system or build tool based on Apache Ant.
These are slides from my talk during the Unconference at the Dutch PHP 2011 Conference (Amsterdam). During this talk I gave an overview of the features and how to use, adapt and extend Phing.
Unit V
STAFFING IN SOFTWARE PROJECTS
Managing people – Organizational behavior – Best methods of staff selection – Motivation – The Oldham-Hackman job characteristic model – Ethical and Programmed concerns – Working in teams – Decision making – Team structures – Virtual teams – Communications genres – Communication plans.
Phing - A PHP Build Tool (An Introduction)Michiel Rook
PHing Is Not GNU make; it's a PHP project build system or build tool based on Apache Ant.
These are slides from my talk during the Unconference at the Dutch PHP 2011 Conference (Amsterdam). During this talk I gave an overview of the features and how to use, adapt and extend Phing.
scmGalaxy.com is dedicated to software configuration, build and Release management. This covers CVS, VSS (Visual Source Safe),Perforce, SVN(Subversion) MKS Integrity, ClearCase,TFS,CM Synergy, Best Practices ,AnthillPro, Apache Ant, Maven, Bamboo, Cruise Control and many more tools.
File Can be downloaded from:
http://community.scmgalaxy.com/
Presentation held in the seminar on "Development Processes in Open Source Projects." Features the documentation tool Sphinx and its internationalization component sphinx-i18n, along with general insights to Open Source communities and technical details about gettext, Docutils, ReStructuredText, and Google's Summer of Code. Also fixed lotsa bugs in sphinx-i18n. :-)
This workshop introduced the power of XML and XSLT to delegates. It used an innovative solution of Apache Cocoon on a single server and form-based file upload to allow delegates to quickly and simply see the effect of applying XSL transformations on their markup.
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
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Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
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.
Enchancing adoption of Open Source Libraries. A case study on Albumentations.AIVladimir Iglovikov, Ph.D.
Presented by Vladimir Iglovikov:
- https://www.linkedin.com/in/iglovikov/
- https://x.com/viglovikov
- https://www.instagram.com/ternaus/
This presentation delves into the journey of Albumentations.ai, a highly successful open-source library for data augmentation.
Created out of a necessity for superior performance in Kaggle competitions, Albumentations has grown to become a widely used tool among data scientists and machine learning practitioners.
This case study covers various aspects, including:
People: The contributors and community that have supported Albumentations.
Metrics: The success indicators such as downloads, daily active users, GitHub stars, and financial contributions.
Challenges: The hurdles in monetizing open-source projects and measuring user engagement.
Development Practices: Best practices for creating, maintaining, and scaling open-source libraries, including code hygiene, CI/CD, and fast iteration.
Community Building: Strategies for making adoption easy, iterating quickly, and fostering a vibrant, engaged community.
Marketing: Both online and offline marketing tactics, focusing on real, impactful interactions and collaborations.
Mental Health: Maintaining balance and not feeling pressured by user demands.
Key insights include the importance of automation, making the adoption process seamless, and leveraging offline interactions for marketing. The presentation also emphasizes the need for continuous small improvements and building a friendly, inclusive community that contributes to the project's growth.
Vladimir Iglovikov brings his extensive experience as a Kaggle Grandmaster, ex-Staff ML Engineer at Lyft, sharing valuable lessons and practical advice for anyone looking to enhance the adoption of their open-source projects.
Explore more about Albumentations and join the community at:
GitHub: https://github.com/albumentations-team/albumentations
Website: https://albumentations.ai/
LinkedIn: https://www.linkedin.com/company/100504475
Twitter: https://x.com/albumentations
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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:
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!SOFTTECHHUB
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Paper: https://eprint.iacr.org/2023/1886
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
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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
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...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.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...
Project Automation
1. Project Automation
Christian Plessl & Stefan Bleuler
Software Engineering Workshop,
December 5-6, 2005
ETH Zürich, Institut TIK December 5, 2005
2. Project Automation: Outline
reasons methods
tools continuous
integration
Project
Automation
reproducible principles
research and pitfalls
2
3. Why should we automate…
…when doing the same thing multiple times?
Example: in all html files: /home/ftp /home/tikftp
save time
repetition is boring, no learning
do the same thing: make the same mistake in all cases
do it more frequently, e.g., update software
do it on a schedule, e.g., backup
…when doing the same thing once?
Example: plot a figure in matlab
reproducibility: “Do it again but change the labels!”
documentation: “Which results did go into the figure?”
Can you reproduce your results?
3
4. What should we automate?
do not automate things you…
…won’t do again.
…don’t want to remember how you did them.
…like doing multiple times.
typical targets for automation
repetitive shell tasks
building and testing of software
simulation runs and analysis of results
4
5. Automation Languages
plenty of languages
general purpose “scripting” languages (Sh, Perl, Ruby)
general purpose languages (C, Java)
domain specific languages (Make, ant, XSLT, Matlab)
you can do anything with any language, but…
there is no “one size fits all” language
use the right language for each task
use the domain knowledge provided by domain specific
languages
make your job as easy as possible
glue the best tools together, be creative
5
6. Automation of Shell Tasks
examples
rename all welcome.html files to index.html
change all links pointing to /proj/* to point to /home/*
benefits
reduce errors
make functionality available to others
strategies
1. level: use the power of the shell (oneliners)
2. level: use scripts
6
7. The Power of the Shell
example: create a zip file of my source files:
command line: zip archive *.h *.c
GUI:
- run WinZip of similar
- create new archive
- select source directory, add *.c filter, add *.h filter
- close archive and quit WinZip
example: mass replace text in files
find . -name “*.html” -exec perl -spi -e 's/string1/string2/g' {} ;
concise and precise
which options have be be set in GUI?
likely to be valid for a long time (GUIs change a lot)
room for further automation
calling a sequence of scripts from a super-script
create wrappers for frequently used commands
7
8. Scripting Languages
shell scripts (sh, tcsh, ksh)
cumbersome syntax
few libraries, rely on external tools (incompatibilities)
manipulation of results difficult
don’t use them, or only for simple sequences of commands
general purpose script languages (Ruby, Perl, Python)
real programming languages (procedural / object oriented)
extensive libraries
strong text manipulation capabilities
very portable if built-in commands are used
can do anything a shell script can do
glue-logic between tools
can use built-in commands and libraries and external commands
8
9. Scripting Shell Tasks
example
generate PDFs from all ASCII handouts for this workshop
benefits
don’t forget anything
do it triggered by changes
method
Trigger perl make
ASCII
for all subdirectories
if filename ends in .txt redcloth
if filename contains searchstring HTML
make file.pdf
move file.pdf to public_html html2ps
end PS
end distill
end
PDF
9
11. Example: Shell Task Scripting
use strict;
use File::Find;
use File::Basename;
use File::Spec;
my $path_to_scripts = dirname(__FILE__);
my $makefile = quot;$path_to_scripts/handout_makefilequot;;
my $searchstr = $ARGV[0];
my $outdir = $ARGV[1];
my $abs_outdir = File::Spec->rel2abs($outdir);
my @dir_list = '.'; # we start in the current directory
# find all files and for each call ’wanted’
find({wanted => &wanted, no_chdir => 1}, @dir_list);
sub wanted {
my $name = $File::Find::name;
if (-f $_ && $name =~ m/^(.+).txt$/) { # is a file and name ends in .txt
my $prefix = $1;
if($name =~ m/$searchstr/) {
system(quot;make -f $makefile REDCLOTH=$path_to_scripts/redcloth $prefix.pdfquot;);
system(quot;cp $prefix.pdf $abs_outdirquot;);
}
}
} 11
12. More Power: Domain Specific Languages
general purpose scripting languages can do
everything
domain specific languages can do some things
more efficiently
they incorporate domain knowledge
code is shorter, more expressive
programs more efficient
examples: XSLT, matlab, SQL, …
12
13. Example: Domain Specific Languages
XSLT
XML to XML transformations
declarative, template based
<card type=quot;simplequot;>
<name>John Doe</name>
<email>doe@widget.com</email>
<phone>(202) 456-1414</phone>
</card>
<?xml version=quot;1.0quot;?>
<html xmlns=quot;http://www.w3.org/1999/xhtmlquot;>
<head>
<title>business card</title>
</head>
<body>
<h1>John Doe</h1>
<p>email: <a href=quot;mailto:doe@widget.comquot;>
doe@widget.com</a></p>
<p>phone:(202) 456-1414</p>
</body>
</html>
13
15. Code Generation
basic ideas
DRY principle: keep information in one place only
translate between representations of the same information
simple to change
active vs. passive code generators
passive: generate code once (then modify manually)
active: run each time the input data changes
examples
XML to XML transformations
database and access functions: SQL tables and Java Code
methods
scripts
domain specific languages …
15
17. Building and Testing Software
basic steps
compile link test
build
strategy
only do what is necessary (modification time)
write down recipe in one place
build tools (make, ant, ...)
benefits
incremental builds
can be triggered by changes => continuous integration
what about IDEs?
can do the same with one click
information distributed, not portable
some IDEs can export build procedure as makefile
17
18. Build Languages
make, ant, cmake, imake, rake
domain knowledge
hierarchy of build targets
build rules (templates e.g. File.java File.class)
dependencies
minimal incremental rebuilds
general purpose or language specific
example ant:
knows about javac, jar, rmic, javah, javadoc, etc.
tasks: archive, coverage, compile, deployment,
execution, logging, scm, test, etc
use for: automate build, test, packaging, deployment
18
20. Continuous Integration
core idea: run build and test loop continuously
watch repository for changes
run build and tests
publish status of the build and tests to developers
build is successful if:
- uses latest sources from version control
- is built automatically
- passes all unit tests and functional tests
benefits
detect errors early
monitor code quality over time
prevent integration problems
20
21. Contiuous Integration 2
requires: automated building and testing
use a single repository where anyone can get the current version of
all sources (and all previous versions)
automate the build process so that anyone can use a single
command to build the system from the sources
automate the testing so that you can run a good suite of tests on the
system at any time with a single command
tools
CruiseControl
CruiseControl.NET
Tinderbox
damagecontrol
use established version-control, build and testing
frameworks
21
23. CruiseControl Case Study
idea: automate validation and publishing of the
workshop webpage
basic steps
validate XHTML
validate CSS
convert ASCII handouts to PDF
publish on webserver
main tool: CruiseControl
ideal for java
also other languages possible (as you will see)
23
29. Publishing Process
all build and test results are
log_buildno.xml stored in a single XML file
UnitTest Commit log Build Coding style HTML valid. XSL stylesheets
XSL XSL XSL XSL XSL generate
reports
reports format
UnitTest Commit log Build Coding style HTML valid. the build and
report report report report report
test results
nicely
HTML Email SMS
various
publisher publisher publisher publishers send
results to
developers
29
30. Failed Build (HTML publisher)
build information
summary
build errors and
warnings
test reports
Subversion revision
logfile comments
HTML and CSS vali-
dation report
We have added this
information for our
case study
30
32. A Bug has been fixed (Email publisher)
email to all who committed since last successful build
32
33. Simulation Runs and Analysis – An Example
revision for a paper
study comparing algorithms
given
algorithms in binaries and source
synthetic data
some scripts for converting output files (a few broken)
multiple results directories per algorithm
one parameter file per algorithm
figures in the paper
task: do exactly the same for another kind of
synthetic data
problems:
what were the parameter settings for the different runs?
which scripts were used for processing which results?
which results did make it into the final figures?
33
34. Simulation Runs and Analysis II
conclusions
“normal” project
“everything” was there
it was mostly useless
Too many things had been performed manually.
advice
do not underestimate the amount of information in a few
commands entered by hand
automation is the most accurate form of documentation
34
35. Reproducible Research - A Vision
scientific experiments should be reproducible
in computer science they really could be
project.tar.gz
results
README
figures
data/
./do_it_all.pl tables
code/
do_it_all.pl
Can I reproduce your results?
35
36. Wrap up: Principles and Pitfalls of Project
automation
don’t repeat yourself DRY
single source principle
prefer convention over configuration
+ prefer modularity over generalization
choose right granularity (rule of thumb: isolate long running
tasks)
you will always have to adapt small things: reduce barrier for
change
use domain specific tools
trying to solve all possible problems
don’t know when to stop
! re-invent the wheel
36
37. Advice
do not try to automate everything
be familiar with the automation possibilities and judge
yourself
everyone should be intimate with
a scripting language
a build tool (make, ant, etc.)
the most important shell commands
one editor
define a good project layout
remove burden from developer of deciding what files to put where
defined directory layout enable automation, e.g. self-testing
stick to the layout!
exchange code and solutions
37
38. Literature
A. Hunt and D. Thomas, The Pragmatic Programmer, Addison Wesley, 2000
D. Thomas et al., Programming Ruby, Pragmatic Bookshelf,
L. Wall et al., Programming Perl, O’Reilly, 2000
T. Christiansen and N. Torkington, Perl Cookbook, O’Reilly, 1998
M. Clark, Pragmatic Project Automation, Pragmatic Bookshelf, 2004
http://cruisecontrol.sourceforge.net
extensive list of code generators: http://www.codegeneration.net
38