Top 5 Code Editors for the Software Programmers | Best Code Editor | scmGalaxy

top-5-code-editors
This is the age of programming and coding and in the last few years software industry changes a lot. We can see a lot of automation and different kind of tools used by programmers and developers to perform their tasks and projects, and it’s necessary too  because a right tool can simplify your work environment and same time it improves your productivity. So, today we are going to talk about “Code Editors” tools, which play a vital role in programmer’s workspace.
So first, Let’s see , What is code Editor?
The formal definition is: A code editor is a type of program used for editing plain text files.
In our language we can say: A code editor is a program in our systems or computer that allows us to write, create and edit a range of programming languages codes on them very easily and it’s also assist programmers to avoid some of the common mistakes in coding by providing them instant detailing of the code, which increase their efficiency.

So, this is very much important to use good code editors which comes with some common features which are necessary to make best use of it.

Let’s look on to the common features in Code Editor you should look for.
  • User-Friendly — It should be easy to use and navigate.
  • Search & Replace — This is one feature through which you can easily search words and replace them with few clicks.
  • Copy & Paste —This feature is no doubt one the most important feature because without cut,copy and paste we can not think to even write these days.
  • Syntax highlighting — Only a programmer knows, how it feels when a single “;” (semi-colon) missed in a code of thousand lines results in a failed program execution. So, Code editor should contain syntax highlighting feature, it helps to read and pick up code errors easily.
  • UTF-8 — Code editors should able to deal with UTF-8 encoded text.
  • Extensions — When choosing a text editor one should also check plugins availability to the editor. It allows you to use it with additional features.

Now, comes the real problem

 

There are so many Code editors available but to choose from them can be a challenging task. It requires time, experiment and research to find out the best code editors. To help you out we have done all these things for you and compile a list of top 10 code editors. So without wasting any time let’s start.


1. Notepad++

notepad++

Notepad ++ is an open source code editor which is one of the most popular editor which compatible with windows but can be use on Linux, Unix, Mac or OS with the help of Wine. This application supports large numbers of programming, scripting and markup languages but works best with HTML, CSS, JavaScript and PHP. It is very easy to use and very lightweight application which can manage huge files without any major lags or crashes.
It’s features:-
  • Supports syntax highlighting
  • Tabbed editing
  • External Plugins Support
  • Auto indentation
  • Auto-completion of words & functions.
  • Compiler Integration
  • File Transfer Protocol (FTP) support
  • Search and Replace
2.Sublime
sublime
Sublime is also one of the most popular editor tool. The sublime editor is not available for free but you can use free trial offer. This editor works on Mac, Windows, and Linux operating systems and they have an advanced interface which is really good for server side programming. It is also lightweight but powerful editor which provides IDE-like features along with Python Scripting. This editor can be an alernative for Integrated Development Environment (IDE). This editor also allows you to use it without any complications. Easy to use and navigate.
It’s features
  • Lightning fast project switching
  • Multiple line selection and editing
  • Syntax highlighting
  • Can be completely customized
  • Programmers friendly Plugins support
  • Side by side file comparisons
  • cross platform support
  • Distraction free mode (Black screen)

3. Vim

vim

Vim is an open source free to use editor which is one of the oldest code editor of the industry. This editor works on windows, Linux, Mac os, Android and in iOS platforms. This editor supports large number of plugins which makes it fully customizable. This is one of the most powerful editor you can use but it demands your mastery due to its overtly techie nature but once you get it, you can find no other better options than this editor.
It’s features
  • Work very well with large files
  • Supports complete keyboard operations
  • Supports large numbers of plugins
  • Useful in a remote development environment using a terminal over SSH
  • It can be customized to heart’s content using .vimrc dotfile & VimScript
  • Charityware (Donations go to charities)
4. Atom
atom
Atom is also amongst open source free to use editors which was invented by GitHub. Atom is a quite new in this industry which was introduced as “hackable text editor for the 21st century”. It’s designed very simple but can be easily customize with the help of packages. This one is resemblance of sublime text editor. It’s work on OSX 10.8 or later, Windows and Linux platforms.
It’s features
  • Very easy to use
  • Auto-completion
  • Highly customizable
  • Offers git control and package management features
  • Updates on regular basis with new functionalities and bug fixes
  • Supports Command Palette
  • Easy to Customise UI

5. Komodo Edit

 

komodo edit
Komodo edit is also amongst one of the powerful editor which is available in open source and free to use that works on Windows, Mac OS X and Linux. Komodo edit supports few programming languages which are HTML5, TCL, XML, JavaScript, Ruby, Python, Perl, CSS3, and PHP. This editor is preferred by advanced programmers , so if you are just starting out than it will take some time to understand it’s interface and navigations.
It’s features
  • Syntax highlighting
  • Auto indentation
  • Code folding
  • Auto completion
  • Extension support and macros
  • Multiple selections
  • Code snippets
  • Komodo IDE for Teams (you can upgrade for advance features)
In the end I would just say, the best text editor is the one you work most effectively with. You simply need to discover the editor that gets you there the fastest.
So, this is our selection of top editors for software programmer, we have tried our best to make this list but, if you used or using any other editors and find it better than the above mentioned list then let us know in the comment box below with it’s key features.
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Top 5 Code Coverage Tools | Best Test Coverage Tools

Today we will talk about code coverage tools which are used by developers for measuring the quality of the software testing. There are so many different types of code coverage tools, some are basics and others that are exceptionally thorough.
But before going further on tools let’s first see what is Code Coverage?
Code Coverage is a methodology, which is performed to measure and describe how much the source code of a program is executed when a specific test suite runs. It gives a percentage score to a program which defines as a high code coverage and low code coverage. If it gets high percentage of code coverage during testings which means it has a minimal chance of containing undiscovered software bugs in the comparison of a program which scored low percentage of code coverage while testing. In simple words , code coverage is performed to check whether your tests are really analyzing your code or not. With code coverage, one can tell the amount of your code is being tested by running the test.
Where to use ?
Code coverage tools can be performed on .NET, Java, Visual C/C++ and Visual Basic applications.
Benefits of Code Coverage
Dead Code Identification – The first and the major benefits of code coverage is that after running this test you will get the outputs that shows those functions which are not called, after detecting that you can identify whether the code is untouched as no required use case exists or code is dead code (i.e. not required).
Missing test Identification – It can be beneficial in identifying the extra tests (exceptional cases), which are missed out earlier after running the test suites analysis report.
Quality Assurance – Quality of a product or application is one of the major concern in software world and this can be done by measuring the report after running the code coverage. Higher the amount of coverage better will be the quality of product or application and lesser is the chance to have defects.
Now the next question here is which code coverage tools to choose ?
This is the real challenge to choose which code coverage tools to use for application testing. I also thought about it and after few hours research on the internet and with the help of google trend I shortlisted my results and pick top 5 code coverage tools.
1. Cobertura –
code-coverage-tool-cobertura
Cobertura is one of the most used and best code coverage tools. This is a free Java tool that calculates the percentage of code accessed by tests. It can be used to identify which parts of your Java program are lacking test coverage. It is based on jcoverage. It is easy to use and can measure coverage without having the source code. It’s represents reports in HTML or XML format, It has capacity to test lines and branches of class and method.
2. JaCoCo –
code-coverage-tool-jacoco
JaCoCo is also an open source free code coverage tools for Java, which has been made by the EclEmma group in view of the lessons gained from utilizing and joining existing libraries for a long time. JaCoCo offers instructions, line and branch coverage. It can instrument off-line and on-the-fly and It fully supports Java 7 and Java 8. It also has capacity to test lines and branches of class and method. It also provide very nice and easy to navigate HTML or XML report.
3. Clover –
code-coverage-tool-clover
Clover is also a Java Code Coverage tools bought and further developed by Atlassian. It is also an open source tool. Clover provide very helpful configurable HTML reports demonstrating code scope as well as high level risks and so on, per-test code coverage and test enhancement, dispersed per-test coverage and many instrument integration; it is by and large effectively created and supported.
4. NCover-
code-coverage-tool-ncover
NCover is a code coverage tool for .Net programs and applications. It supports statement coverage and branch coverage. It is also very easy to use and fast tool which is available on open source and as well as on commercial license. This tool can perform manual as well as automated code coverage tests and it provides nice and attractive multiple testing environments.
5. Testwell CTC++ –
code-coverage-tool-testwell-ctc++
Testwell CTC++ is a code coverage tool for  C and C++ but it also can be used for Java and C#. The development of this tool is belongs to Testwell which lately acquired by Verifysoft Technology GmbH for C and C++. This tool can check Statement Coverage, Function Coverage, Decision Coverage, Multi Condition Coverage, Modified Condition/Decision Coverage (MC/DC), Condition Coverage. This is also in the category of user-friendly and fast tools. It finds missing test cases smoothly. It provide reports on XML format.
So, This is my list of top code coverage tools, I hope this list will help you in your testings. But, if you think this list should contain any other tools instead these than feel free to share with us in comment box below.
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Top 10 Static Code Analysis Tool | Best Static Code Analysis Tools List

top-10-static-code-analysis-tool
Software security is a very important concern for todays Software market and for that you need to do code analysis in the development lifecycle. Now we can not imagine ourselves to sit back and do manual reading each line of codes and find issues and bugs. Those days of manual review in the software development lifecycle to find the flaws in the codes are over now.
Now the mindsets has changed and developing quality & secure code from the beginning is on rise. This is the time of automation and developers & programmers are now shifting towards the adoption of tools which auto detects the flaws as soon as possible in the software development lifecycle.
As the process shifting towards the automation, static code analysis (SCA) has become an important part of creating quality code. Now the question here is, What is Static Code Analysis?

Static Code Analysis is a technique which quickly and automatically scan the code line by line to find security flaws and issues that might be missed in the development process before the software or application is released. It functions by reviewing the code without actually executing the code.

There are three main benefits of Static analysis tools
1. Automation —  Automation can save your time and energy which ultimately means you can invest your time and energy in some other aspects of development lifecycle, which will help you to release your software faster.
2. Security — Security is also one of the major concern and by adopting Static analysis you can cut the doubt of security vulnerabilities in your application, which will ensure that you are delivering a secure and reliable software.
3. Implementation — Static analysis can be implemented as early in the software development lifecycle (SDLC) as you have code to scan, it will give more time to fix the issues discovered by the tool. The best thing of static analysis is that it can detect the exact line of code that’s been found to be problematic.
There are so many Static code analysis tools are available to ease our work but to choose good tools among them is really a challenging task. I have done some research and providing you the list of top 10 static code analysis tools:-

1. VisualCodeGrepper

static-code-analysis-tool-visualcodegrepper
Visualcodegreeper is an open source automated code security review tool which works with C++, C#, VB, PHP, Java and PL/SQL to track the insecurities and different issues in the code. This tool rapidly review and depicts in detail the issues it discovers, offering a simple to use interface. It allows custom configurations of queries and it’s updated regularly since its creation (2012).
2. Coverity

static-code-analysis-tool-coverity

Coverity is also an open source static code analysis tool which supports C, C++, C#, Objective-C, Java, Javascript, node.JS, Ruby, PHP & Python. It is an excellent static analysis product with support of 100 compilers & detailed and clear description of the code issues you can use it in your desktop environment to quickly find and resolve the errors before checking in the code.

3. Veracode

static-code-analysis-tool-veracode

Veracode is also one of the best static code analysis tool which can find security flaws in application binary code – compiled or “byte” code even when the consideration of source code is not available. Veracode supports multi-languages which includes .NET (C#, ASP.NET, VB.NET), Java (Java SE, Java EE, JSP), C/C++, JavaScript (including AngularJS, Node.js, and jQuery), Python, PHP, Ruby on Rails, ColdFusion, Classic ASP, including mobile applications on the iOS and Android platforms and written in JavaScript cross platform frameworks.

4. YASCA

static-code-analysis-tool-yasca

“Yet Another Source Code Analyzer (YASCA)” is an open source stactic code analysis tool which supports HTML, Java, JavaScript, .NET, COBOL, PHP, ColdFusion, ASP, C/C++ and some other languages. It is an easy to extend and a flexible tool which can integrate with variety of other tools which includes CppCheck, Pixy, RATS, PHPLint, JavaScript Lint, JLint, FindBugs and various others.
5. Cppcheck

static-code-analysis-tool-cppcheck

Cppcheck is an open source static code analysis tool for C/C++. Cppcheck basically identifies the sorts of bugs that the compilers regularly don’t recognize. The objective is to identify just genuine mistakes in the code. It provides both interface command line mode and graphical user interface (GUI) mode and has possiblitites for environment integration. Some of them are Eclipse, Hudson, Jenkins, Visual Studio.

6. Clang

 

static-code-analysis-tool-clang
Clang is also one of the best static code analysis tool for C, C++ and objective-C. This analyzer can be run either as standalone tool or within Xcode. It is an open source tool and a part of the clang project. It utilizes the clank library, hence forming a reusable component and can be utilized by multiple clients.

7. RIPS

 

static-code-analysis-tool-rips
RIPS is a static code analyzer tool to detect different types for security vulnerabilities in PHP codes. RIPS also provide integrated code audit framework for manual analysis. It is an open source tool too and can be controlled via web interface.
8. Flawfinder
static-code-analysis-tool-flawfinder
Flawfinder is also one of the best static analysis tool for C/C++. This tool is easy to use and wel designed. It reports possible security vulnerabilities sorted by risk level. It is an open source tool written in python and use command line interface.
9. DevBug
static-code-analysis-tool-devbug
DevBug is an online PHP static code analyser which is very easy to use and written on Javascript. It was intended to make essential PHP Static Code Analysis accessible on the web, to raise security mindfulness and to incorporate SCA into the development procedure. This analyser tool is also available in open source.

10. SonarQube

 

static-code-analysis-tool-devbug
SonarQube is one of the best and well known open source web based static code analysis tool, it can scan projects written in many different programming languages including  ABAP, Android (Java), C, C++, CSS, Objective-C, COBOL, C#, Flex, Forms, Groovy, Java, JavaScript, Natural, PHP, PL/SQL, Swift, Visual Basic 6, Web, XML, Python and also allows a number of plug ins. What makes SonarQube really stand out is that It provides metrics about your code which will to help you to take the right decision and translates these non-descript values to real business values such as risk and technical debt.
So, above we mentioned top selective static code analysis tools which can be helpful, but if you think this lists should contain some other tools than feel free to share in comment box.
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Chef Code Analysis using Foodcritic | Foodcritic Tutorial

chef-code-analysis-using-foodcritic

What is Foodcritic? Foodcritic is a static linting tool that analyzes all of the Ruby code that is authored in a cookbook against a number of rules, and then returns a list of violations. In another word, Foodcritic is a helpful lint tool you can use to check your Chef cookbooks for common problems.

We use Foodcritic to check cookbooks for common problems:
Style
Correctness
Syntax
Best practices
Common mistakes
Deprecations

Foodcritic does not
Foodcritic does not validate the intention of a recipe, rather it evaluates the structure of the code, and helps enforce specific behavior, detect portability of recipes, identify potential run-time failures, and spot common anti-patterns.

When Foodcritic returns a violation, this does not automatically mean the code needs to be changed. It is important to first understand the intention of the rule before making the changes it suggests.

Foodcritic has two goals:

To make it easier to flag problems in your Chef cookbooks that will cause Chef to blow up when you attempt to converge. This is about faster feedback. If you automate checks for common problems you can save a lot of time.

To encourage discussion within the Chef community on the more subjective stuff – what does a good cookbook look like? Opscode have avoided being overly prescriptive which by and large I think is a good thing. Having a set of rules to base discussion on helps drive out what we as a community think is good style.

Foodcritic built-in Rules
It comes with 47 built-in rules that identify problems ranging from simple style inconsistencies to difficult to diagnose issues that will hurt in production. If you want to see the list of rules, please navigate the url as below;
http://www.foodcritic.io/

Prerequisites
Foodcritic runs on Ruby (MRI) 1.9.2+ which depending on your workstation setup may be a more recent version of Ruby than you have installed. The Ruby Version Manager (RVM) is a popular choice for running multiple versions of ruby on the same workstation, so you can try foodcritic out without running the risk of damaging your main install

Foodcritic installation

Method 1
Install RVM as non-root user

$ sudo /etc/init.d/iptables stop OR sudo start ufw

$ curl -s raw.github.com/wayneeseguin/rvm/master/binscripts/rvm-installer | bash -s stable
OR
$ sudo bash -s stable < <(curl -s https://raw.github.com/wayneeseguin/rvm/master/binscripts/rvm-installer )
OR
$ curl -s raw.github.com/wayneeseguin/rvm/master/binscripts/rvm-installer | sudo bash -s stable
OR
$ gpg –keyserver hkp://keys.gnupg.net –recv-keys 409B6B1796C275462A1703113804BB82D39DC0E3
OR
$ command curl -sSL https://rvm.io/mpapis.asc | gpg –import –

$ rvm get stable
$ rvm install ruby-2.2.3
$ gem install foodcritic

Method 2
Install ruby

$ sudo apt-get install ruby-2.2.3 (Ubantu)
$ sudo yum install ruby-2.2.3 (rhel)

Install foodcritic
> gem install foodcritic

Method 3
Alternatively install ChefDK which already includes foodcritic: https://downloads.getchef.com/chef-dk/

How to run Foodcritic?
You should now find you have a foodcritic command on your PATH. Run foodcritic to see what arguments it supports:

foodcritic [cookbook_path]
-r, –[no-]repl Drop into a REPL for interactive rule editing.
-t, –tags TAGS Only check against rules with the specified tags.
-f, –epic-fail TAGS Fail the build if any of the specified tags are matched.
-C, –[no-]context Show lines matched against rather than the default summary.
-I, –include PATH Additional rule file path(s) to load.
-S, –search-grammar PATH Specify grammar to use when validating search syntax.
-V, –version Display version.

How to setup Foodcritic with Jenkins

Configuring Jenkins to run foodcritic
To manually add a new job to Jenkins to check your cookbooks with foodcritic do the following:

  1. Ensure you have Ruby 1.9.2+ and the foodcritic gem installed on the box running Jenkins.
  2. You’ll probably need to install the Git plugin. In Jenkins select “Manage Jenkins” -> “Manage Plugins”. Select the “Available” tab. Check the checkbox next to the Git Plugin and click the “Install without restart” button.
  3. In Jenkins select “New Job”. Enter a name for the job “my-cookbook”, select “Build a free-style software project” and click “OK”.
  4. On the resulting page select “Git” under “Source Code Management” and enter the URL for your repo.
  5. Check the checkbox “Poll SCM” under “Build Triggers”.
  6. Click “Add Build Step” -> “Execute shell” under “Build”. This is where we will call foodcritic.
  7. Assuming you are using rvm enter the following as the command:
  8. #!/usr/bin/env rvm-shell 1.9.3
    foodcritic .
  9. Click “Save”.
  10. Cool, we’ve created your new job. Now lets see if it works. Click “Build Now” on the left-hand side.
  11. You can click the build progress bar to be taken directly to the console output.
  12. After a moment you should see that the build has been successful and foodcritic warnings (if any) are shown in your console output.
  13. Yes, for maximum goodness you should be automating all this with Chef. 🙂
  14. For more information refer to the instructions for building a “free-style software project” here:
    https://wiki.jenkins-ci.org/display/JENKINS/Building+a+software+project
  15. See also this blog post about rvm-shell which ensures you have the right version of Ruby loaded when trying to build with foodcritic:
    http://blog.ninjahideout.com/posts/rvm-improved-support-for-hudson

Failing the build
The above is a start, but we’d also like to fail the build if there are any warnings that might stop the cookbook from working.

CI is only useful if people will act on it. Lets start by only failing the build when there is a correctness problem that would likely break our Chef run. We’ll continue to have the other warnings available for reference in the console log but only correctness issues will fail the build.

Select the “my-cookbook” job in Jenkins and click “Configure”.

Scroll down to our “Execute shell” command and change it to look like the following:

#!/usr/bin/env rvm-shell 1.9.3
foodcritic -f correctness .
Click “Save” and then “Build Now”.

More complex expressions
Foodcritic supports more complex expressions with the standard Cucumber tag syntax. For example:

#!/usr/bin/env rvm-shell 1.9.3
foodcritic -f any -f ~FC014 .
Here we use any to fail the build on any warning, but then use the tilde ~ to exclude FC014. The build will fail on any warning raised, except FC014.

You can find more detail on Cucumber tag expressions at the Cucumber wiki:

https://github.com/cucumber/cucumber/wiki/Tags

Tracking warnings over time
The Jenkins Warnings plugin can be configured to understand foodcritic output and track your cookbook warnings over time.

You’ll need to install the Warnings plugin. In Jenkins select “Manage Jenkins” -> “Manage Plugins”. Select the “Available” tab. Check the checkbox next to the Warnings Plugin and click the “Install without restart” button.

From “Manage Jenkins” select “Configure System”. Scroll down to the “Compiler Warnings” section and click the “Add” button next to “Parsers”.

Enter “Foodcritic” in the Name field.

Enter the following regex in the “Regular Expression” field:

^(FC[0-9]+): (.*): ([^:]+):([0-9]+)$

Enter the following Groovy script into the “Mapping Script” field:

import hudson.plugins.warnings.parser.Warning

String fileName = matcher.group(3)
String lineNumber = matcher.group(4)
String category = matcher.group(1)
String message = matcher.group(2)

return new Warning(fileName, Integer.parseInt(lineNumber), “Chef Lint Warning”, category, message);

To test the match, enter the following example message in the “Example Log Message” field:

FC001: Use strings in preference to symbols to access node attributes: ./recipes/innostore.rb:30
Click in the “Mapping Script” field and you should see the following appear below the Example Log Message:

One warning found
file name: ./recipes/innostore.rb
line number: 30
priority: Normal Priority
category: FC001
type: Chef Lint Warning
message: Use strings in prefe[…]ols to access node attributes
Cool, it’s parsed our example message successfully. Click “Save” to save the parser.

Select the “my-cookbook” job in Jenkins and click “Configure”.

Check the checkbox next to “Scan for compiler warnings” underneath “Post-build Actions”.

Click the “Add” button next to “Scan console log” and select our “Foodcritic” parser from the drop-down list.

Click the “Advanced…” button and check the “Run always” checkbox.

Click “Save” and then “Build Now”.

Add the bottom of the console log you should see something similar to this:

[WARNINGS] Parsing warnings in console log with parsers [Foodcritic]
[WARNINGS] Foodcritic : Found 48 warnings.
Click “Back to Project”. Once you have built the project a couple of times the warnings trend will appear here.

Reference:
http://acrmp.github.io/foodcritic/
https://docs.chef.io/foodcritic.html
http://www.foodcritic.io/
https://atom.io/packages/linter-foodcritic
http://www.slideshare.net/harthoover/rapid-chef-development-with-berkshelf-testkitchen-and-foodcritic

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Source code analysis tools: Evaluation criteria

code-analysis-tools-evaluation-criteria

Source code analysis tools: Evaluation criteria

Support for the programming languages you use. Some companies support mobile devices, while others concentrate on enterprise languages like Java, .Net, C, C++ and even Cobol.

Good bug-finding performance, using a proof of concept assessment. Hint: Use an older build of code you had issues with and see how well the product catches bugs you had to find manually. Look for both thoroughness and accuracy. Fewer false positives means less manual work.

Internal knowledge bases that provide descriptions of vulnerabilities and remediation information. Test for easy access and cross-referencing to discovered findings.

Tight integration with your development platforms. Long-term, you’ll likely want developers to incorporate security analysis into their daily routines.

A robust finding-suppression mechanism to prevent false positives from reoccurring once you’ve verified them as a non-issue.

Ability to easily define additional rules so the tool can enforce internal coding policies.

A centralized reporting component if you have a large team of developers and managers who want access to findings, trending and overview reporting

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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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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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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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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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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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