Subversion user and administration training | SVN Course | SVN Training | India

subversion-svn-training-course

Our Subversion training courses are designed to provide the necessary hands-on experience to enable attendees to become productive immediately. We offer public classes at our training centers, private classes that can be held on-site at the customer’s location, as well as web based training.

Subversion user and administration training agenda as below;
Fundamental Concepts

    • The Repository
    • The Problem of File Sharing
    • The Lock-Modify-Unlock Solution
    • The Copy-Modify-Merge Solution

Subversion in Action

    • Subversion Repository URLs
    • Working Copies
    • Revisions
    • How Working Copies Track the Repository
    • Mixed Revision Working Copies

Basic Usage

    • Help!
    • svn import
    • Recommended Repository Layout
    • Disabling Password Caching
    • Authenticating As a Different User

Basic Work Cycle

    • Update Your Working Copy
    • Make Changes to Your Working Copy
    • Examine Your Changes
    • Undoing Working Changes
    • Resolve Conflicts (Merging Others’ Changes)
    • Commit Your Changes

Examining History

    • Generating a List of Historical Changes
    • Examining the Details of Historical Changes
    • Browsing the Repository
    • Fetching Older Repository Snapshots
    • Disposing of a Working Copy
    • Recovering from an Interruption

Advanced Topics

    • Revision Specifies
    • Properties
    • File Portability
    • Locking
    • Changelists
    • Network Model

Branching and Merging

    • Using Branches
    • Basic Merging
    • Advanced Merging
    • Tags
    • Branch Maintenance
    • Common Branching Patterns
    • Vendor Branches

Repository Administration

    • Strategies for Repository Deployment
    • Creating and Configuring Your Repository
    • Repository Maintenance
    • Server Configuration
    • Customizing Your Subversion Experience

About us:
scmGalaxy online platform is a community initiatives based on Software configuration management and DevOps that helps members and organizations to optimize their software development process, advocating agile methodologies and improve productivity across all aspects of Application lifecycle management. We provide consulting, training and mentoring services in agile development practices such as Source Code Management, Continuous Integration, Build management, Test-Driven development, Acceptance-Test driven development, Build automation, code quality practices and automated testing and continuous delivery.

We provide job oriented training in the area of Software Configuration management, Build and Release Engineering and DevOps domain . Candidates with engineering or software background and looking to either start or change their career to Build and Release Engineering, would benefit most from this training. This course offered online around the globe which include India, USA, Europe, Australia, Bangalore, Delhi, Pune, Mumbai, Chennai and Hydrabad. Instructor is an expert in Software configuration management, Build and release engineering and DevOps with more than 10 years industry experience in India.

Course Objectives
To bring your team up to speed with agile development, We can also run the from Continuous Integration to Continuous Delivery with automated course within your premises.
Course Schedule
This course is an intensive 1-day & 2-day workshop with a mixture of teaching and lab exercises. Currently, this course is offered exclusively as an on-line course. Please contact us for more details.
Audience
This is a hands-on, practical course designed to teach specialized skills for real-world development situations. It is thus primarily aimed at a SCM Engineer, Build/Release Engineer, DevOps engineer and developer and QA audience.
Approach
The course is modular and flexible – depending on specific student needs and requests. Through our trainings, you benefit from the wide experience and architectural expertise of our team. We bring that experience to you in an highly interactive, intensely hands-on setting.
Assumptions
We assume participants have a reasonable understanding of Development in any language as well as a basic understanding of the Software Development Life Cycle.
Lab Work
All our courses are above all practical in nature. We believe that the best way to learn is by doing. So the course contains approximately 80% lab work.
Learning Resources
Each registrant will receive a copy of the student notes and lab solutions, a certificate of completion, and a CD containing all the tools covered in the course and CD containing all the tools covered in the course.
Contact Us
This course is provided on-site, and can be tailored to your particular requirements. If you would like our trainings delivered at your premises, or for any additional information please contact us. Please email us at info@scmGalaxy.com

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Static vs dynamic code analysis: Advantages and Disadvantages

static-vs-dynamic-code-analysis-advantages-and-disadvantages

What are the advantages and limitations of static and dynamic software code analysis? Maj. Michael Kleffman of the Air Force’s Application Software Assurance Center of Excellence spelled it out.

Static code analysis advantages:

  1. It can find weaknesses in the code at the exact location.
  2. It can be conducted by trained software assurance developers who fully understand the code.
  3. It allows a quicker turn around for fixes.
  4. It is relatively fast if automated tools are used.
  5. Automated tools can scan the entire code base.
  6. Automated tools can provide mitigation recommendations, reducing the research time.
  7. It permits weaknesses to be found earlier in the development life cycle, reducing the cost to fix.

Static code analysis limitations:

  1. It is time consuming if conducted manually.
  2. Automated tools do not support all programming languages.
  3. Automated tools produce false positives and false negatives.
  4. There are not enough trained personnel to thoroughly conduct static code analysis.
  5. Automated tools can provide a false sense of security that everything is being addressed.
  6. Automated tools only as good as the rules they are using to scan with.
  7. It does not find vulnerabilities introduced in the runtime environment.

Dynamic code analysis advantages:

  1. It identifies vulnerabilities in a runtime environment.
  2. Automated tools provide flexibility on what to scan for.
  3. It allows for analysis of applications in which you do not have access to the actual code.
  4. It identifies vulnerabilities that might have been false negatives in the static code analysis.
  5. It permits you to validate static code analysis findings.
  6. It can be conducted against any application.

Dynamic code analysis limitations:

  1. Automated tools provide a false sense of security that everything is being addressed.
  2. Automated tools produce false positives and false negatives.
  3. Automated tools are only as good as the rules they are using to scan with.
  4. There are not enough trained personnel to thoroughly conduct dynamic code analysis [as with static analysis].
  5. It is more difficult to trace the vulnerability back to the exact location in the code, taking longer to fix the problem.
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Difference between dynamic code analysis and static code analysis

difference-dynamic-code-analysis-and-static-code-analysis

Difference between dynamic code analysis and static code analysis

Static analysis is the testing and evaluation of an application by examining the code without executing the application whereas Dynamic analysis is the testing and evaluation of an application during runtime.

Many software defects that cause memory and threading errors can be detected both dynamically and statically. The two approaches are complementary because no single approach can find every error.

The primary advantage of dynamic analysis: It reveals subtle defects or vulnerabilities whose cause is too complex to be discovered by static analysis. Dynamic analysis can play a role in security assurance, but its primary goal is finding and debugging errors.

Level of in-depth review

The key difference between a static and dynamic code analyser is the how in-depth the code review

process is. By default, static code analysis combs through every single line of source code to find flaws and errors. For dynamic analysis, the lines of code that get reviewed depend upon which lines of source code are activated during the testing process. Unless a line of code is interacted with, the dynamic analysis tool will ignore it and continue checking active codes for flaws. As a result, dynamic analysis is a lot quicker since it is able to review code on the fly and generates real-time data. However, static code analysis provides peace of mind that each and every line of source code has been thoroughly inspected. It may take longer, but static code analysis runs in the background and is crucial for creating a flawless web application.

 

Catching errors early and making recommendations

The primary advantage of static analysis: It examines all possible execution paths and variable values, not just those invoked during execution. Thus static analysis can reveal errors that may not manifest themselves until weeks, months or years after release. This aspect of static analysis is especially valuable in security assurance, because security attacks often exercise an application in unforeseen and untested ways.

As mentioned before, dynamic analysis reviews codes during the testing process and generates real-time results. While it is great for fine-tuning the user experience, it has one major drawback: any errors highlighted by dynamic code analysis tools requires developers to go all the way back to the source code, make changes to the code itself and then make changes to everything that has been modified as a result of changing the source code. This is a very time consuming and expensive process; one that companies and developers like to avoid at all costs. Static code analysis tools highlight any errors immediately and allow developers to makes changes before proceeding any further. Moreover, static code analysis tools are more feature-packed than their dynamic counterparts. One important feature is the number of errors it can detect and the recommendations it can make to fix that error. If configured, static code analysers can automatically make the required changes and let developers know what changes have been made.

 

Cost of code analysis tools

Just like any other business, software application companies have to find a fine balance between application costs and profit margins. With respect to price, static code analysis tools are always cheaper than dynamic analysers. Moreover, having a dynamic code analyser requires a company to hire professionals trained in the use of dynamic analysis tools. A static code analysis tool can be used by any web developer with ease, thus guaranteeing that it won’t turn out to be a long-term expenditure.

Static code analysers are absolutely essential for application developers, whereas dynamic code analysers can only be used in conjunction with static analysis tools.

 

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Dynamic code analysis VS Static code analysis

dynamic-code-analysis-vs-static-code-analysis

Difference between dynamic code analysis and static code analysis

Static analysis is the testing and evaluation of an application by examining the code without executing the application whereas Dynamic analysis is the testing and evaluation of an application during runtime.

Many software defects that cause memory and threading errors can be detected both dynamically and statically. The two approaches are complementary because no single approach can find every error.

The primary advantage of dynamic analysis: It reveals subtle defects or vulnerabilities whose cause is too complex to be discovered by static analysis. Dynamic analysis can play a role in security assurance, but its primary goal is finding and debugging errors.

Level of in-depth review

The key difference between a static and dynamic code analyser is the how in-depth the code review

process is. By default, static code analysis combs through every single line of source code to find flaws and errors. For dynamic analysis, the lines of code that get reviewed depend upon which lines of source code are activated during the testing process. Unless a line of code is interacted with, the dynamic analysis tool will ignore it and continue checking active codes for flaws. As a result, dynamic analysis is a lot quicker since it is able to review code on the fly and generates real-time data. However, static code analysis provides peace of mind that each and every line of source code has been thoroughly inspected. It may take longer, but static code analysis runs in the background and is crucial for creating a flawless web application.

 

Catching errors early and making recommendations

The primary advantage of static analysis: It examines all possible execution paths and variable values, not just those invoked during execution. Thus static analysis can reveal errors that may not manifest themselves until weeks, months or years after release. This aspect of static analysis is especially valuable in security assurance, because security attacks often exercise an application in unforeseen and untested ways.

As mentioned before, dynamic analysis reviews codes during the testing process and generates real-time results. While it is great for fine-tuning the user experience, it has one major drawback: any errors highlighted by dynamic code analysis tools requires developers to go all the way back to the source code, make changes to the code itself and then make changes to everything that has been modified as a result of changing the source code. This is a very time consuming and expensive process; one that companies and developers like to avoid at all costs. Static code analysis tools highlight any errors immediately and allow developers to makes changes before proceeding any further. Moreover, static code analysis tools are more feature-packed than their dynamic counterparts. One important feature is the number of errors it can detect and the recommendations it can make to fix that error. If configured, static code analysers can automatically make the required changes and let developers know what changes have been made.

 

Cost of code analysis tools

Just like any other business, software application companies have to find a fine balance between application costs and profit margins. With respect to price, static code analysis tools are always cheaper than dynamic analysers. Moreover, having a dynamic code analyser requires a company to hire professionals trained in the use of dynamic analysis tools. A static code analysis tool can be used by any web developer with ease, thus guaranteeing that it won’t turn out to be a long-term expenditure.

Static code analysers are absolutely essential for application developers, whereas dynamic code analysers can only be used in conjunction with static analysis tools.

 

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How to Differentiate Dynamic code analysis and Static code analysis?

static-dynamic-code-analysis-difference

Difference between dynamic code analysis and static code analysis

Static analysis is the testing and evaluation of an application by examining the code without executing the application whereas Dynamic analysis is the testing and evaluation of an application during runtime.

Many software defects that cause memory and threading errors can be detected both dynamically and statically. The two approaches are complementary because no single approach can find every error.

The primary advantage of dynamic analysis: It reveals subtle defects or vulnerabilities whose cause is too complex to be discovered by static analysis. Dynamic analysis can play a role in security assurance, but its primary goal is finding and debugging errors.

Level of in-depth review

The key difference between a static and dynamic code analyser is the how in-depth the code review

process is. By default, static code analysis combs through every single line of source code to find flaws and errors. For dynamic analysis, the lines of code that get reviewed depend upon which lines of source code are activated during the testing process. Unless a line of code is interacted with, the dynamic analysis tool will ignore it and continue checking active codes for flaws. As a result, dynamic analysis is a lot quicker since it is able to review code on the fly and generates real-time data. However, static code analysis provides peace of mind that each and every line of source code has been thoroughly inspected. It may take longer, but static code analysis runs in the background and is crucial for creating a flawless web application.

 

Catching errors early and making recommendations

The primary advantage of static analysis: It examines all possible execution paths and variable values, not just those invoked during execution. Thus static analysis can reveal errors that may not manifest themselves until weeks, months or years after release. This aspect of static analysis is especially valuable in security assurance, because security attacks often exercise an application in unforeseen and untested ways.

As mentioned before, dynamic analysis reviews codes during the testing process and generates real-time results. While it is great for fine-tuning the user experience, it has one major drawback: any errors highlighted by dynamic code analysis tools requires developers to go all the way back to the source code, make changes to the code itself and then make changes to everything that has been modified as a result of changing the source code. This is a very time consuming and expensive process; one that companies and developers like to avoid at all costs. Static code analysis tools highlight any errors immediately and allow developers to makes changes before proceeding any further. Moreover, static code analysis tools are more feature-packed than their dynamic counterparts. One important feature is the number of errors it can detect and the recommendations it can make to fix that error. If configured, static code analysers can automatically make the required changes and let developers know what changes have been made.

 

Cost of code analysis tools

Just like any other business, software application companies have to find a fine balance between application costs and profit margins. With respect to price, static code analysis tools are always cheaper than dynamic analysers. Moreover, having a dynamic code analyser requires a company to hire professionals trained in the use of dynamic analysis tools. A static code analysis tool can be used by any web developer with ease, thus guaranteeing that it won’t turn out to be a long-term expenditure.

Static code analysers are absolutely essential for application developers, whereas dynamic code analysers can only be used in conjunction with static analysis tools.

 

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Difference between Code Coverage and Test Coverage | Code Coverage VS Test Coverage

code-coverage-and-test-coverage-difference

There is not any official distinguished between code Coverage and Test Coverage. Some practitioner has expressed their difference opinion in terms of defining Code Coverage and Test Coverage.
Code coverage and test coverage metrics are both measurements that can be seful to assess the quality of your application code. Code coverage is a term to describe which application code is exercised when the application is running.

Whereas Test coverage refers to metrics in an overall test-plan. In this expert  response, you’ll learn how quality assurance professionals use both of these metrics effectively.

Another definition found over the google search as below;
Code coverage is a measure of how much code is executed during testing &
Test coverage is a measure of how many test cases have been executed during testing.

Lets know about  Code Coverage by definition more in details.
In computer science, code coverage is a measure used to describe the degree to which the source code of a program is tested by a particular test suite. A program with high code coverage has been more thoroughly tested and has a lower chance of containing software bugs than a program with low code coverage. Many different metrics can be used to calculate code coverage; some of the most basic are the percent of program subroutines and the percent of program statements called during execution of the test suite.

Basic coverage criteria

There are a number of coverage criteria, the main ones being:

  • Function coverage – Has each function (or subroutine) in the program been called?
  • Statement coverage – Has each statement in the program been executed?
  • Branch coverage – Has each branch (also called DD-path) of each control structure (such as in if and case statements) been executed? For example, given an if statement, have both the true and false branches been
  • executed? Another way of saying this is, has every edge in the program been executed?
  • Condition coverage (or predicate coverage) – Has each Boolean sub-expression evaluated both to true and false?

[Taken from Wikipedia]

Simply put, code coverage is a way of ensuring that your tests are actually testing your code. When you run your tests you are presumably checking that you are getting the expected results. Code coverage will tell you how much of your code you exercised by running the test. Your tests may all pass with flying colours, but if you’ve only tested 50% of your code, how much confidence can you have in it?

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Build and Release Engineer Training | Build and Release Engineer Course | Online | Classroom

build-and-release-engineer-training

Training Duration – 30 Days (90 mins each day)

Mode – Online (Webex | Skype | Gotomeeting)

Email – info@scmgalaxy.com

Call – +91 700 483 5930

Course Fees: INR 25,000 / Candidate

Registration is based on First Come basis and only confirmed registration would be considered.

scmGalaxy Advantage – If you enroll for scmGalaxy courses once, this is life time enrollment. You can attend this training as many times in future without any cost.

FAQ | Training Calendar | Why scmGalaxy Online Training

Course Outline :

Concept and Process

Operating Systems

  • Introduction of Linux Operating System
  • Linux User Commands
  • Linux Admin Commands
  • Windows Administrator fundamental

Source Code Management

Build Tools

Scripting

Package Management in Linux and Windows

  • Yum
  • apt-get
  • Nuget
  • RPM

Artifact Repository Tools

Configuration Management Tools

Incident Management tools

Continuous Integration Tools

CI/CD Concept and Implementation

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