Regular Expression Tester

Regular Expression Tester

Regex is a useful string of characters that defines a search pattern. In the security world, regular expression plays a crucial role as a security measure. They are used across multiple infrastructure layers of a corporation to implement:

Malware Detection

Regex can customize malware detectors to identify and isolate dangerous file content. This is one of the most common uses for Regex, by searching for patterns in files and databases.

Validating user input

Accepting any user input opens an application to a wide array of vulnerabilities, such as an SQL injection. Regex filters and clears this input as a defense against possible attacks.


System firewalls can be given an added boost with Regex. It is used to create custom rules that can be implemented to block certain requests from specific IP addresses, for example, or even known malicious agents.

Regex Patterns 

Creating patterns to help match and locate text, many regex patterns are popular for their utility. Incorrect composition of Regex can lead to vulnerabilities that can allow attackers to siphon sensitive information. 

Regex tools

Some of the most basic tools Regex utilizes include:

  • sed: This allows you to find and replace a text. Providing a match and the text with which to replace will cause the action to occur
  • grep: This filter tool allows filtration of regular expressions. A large amount of text can be filtered to produce only the wanted results


Regex quantifiers indicate the numbers of characters or expressions that need to be matched. They match the number of instances of a character, group, or class in a string. They match the preceding elements between n and m times, where n and m are integers. 

Open redirect filter bypass

Vulnerabilities caused by a faulty Regex include open also include open redirect filter bypass. The app prevents open redirect by requiring specific criteria to be fulfilled:

  1. The URL must contain “”
  2. The extension at the end should be image-related, such as jpg or png

A Regex that is too permissive such as this:



Allows for too much room in user input, as the “.*” pattern will match any character. Such an open filter exposes the system to vulnerabilities. We can overcome it with:

Matching Email Addresses

Email address restrictions are generally quite extensive, making these Regex a little harder. While there are no valid email Regex, some that can get you on your way include:



This is where the expression starts, which can then be customized. The expression will have to be tested against a valid list of email addresses. 

Matching URLs

A general Regex code to match URLs may be:



As per URL requirements, a specific format helps generate the expression. It matches the:

  • Http
  • Https
  • Ftp
  • Mailto
  • File
  • Irc
  • Schemes
  • Query strings (preceded by ?)
  • Fragments (preceded by #)

This is not a foolproof expression by any means. It is meant to act as a starting point on which further modifications can be made as needed.

Matching Passwords

Password complexity and vulnerability testing a key use of Regex expressions. Javascript offers a simple way to test passwords in the user’s browser window. Given the variety of criteria, the expression may be altered. This expression tests for letters, numbers and length: 



Special characters can be included in the criteria as well:


Enforcing the presence of certain characters, such as a number, a positive lookahead is used (?=…). This can be exemplified in the following expression:


This expression ensures that the password contains:

  • At least one upper case letter [A-Z]
  • At least one lower case letter [a-z]
  • At least one number [0-9]
  • At least one special character 
  • At least 8 total characters 

SSRF blacklist protection 

The Server Side Request Forgery (SSRF) occurs when a malicious attacker can send requests acting as the server. The vulnerability allows attackers to fake or ‘forge’ the request signature of the actual server. This privileged position allows access to a secure network, bypassing any firewalls and gaining internet access. 

A legitimate image request, for example, looks something like this:

SSRFs are prevented by the website by rejecting img parameters which have certain URLs in a blacklist. The corresponding Regex looks like this:


This pattern is intended to check all user input against the blacklist of local IP addresses. Requests are denied if a match is found. However, this is not a foolproof method. Another possible IP address case is “”, which is used to refer to the local machine. This protection can then be bypassed using the expression:

Limitations of Regular Expression Testers

As with every other process, Regex has its limitations. Software security and testing to locate vulnerabilities and guard against them is an essential aspect of development, however; this should not be done with limitless expectations of the tools in use. 

Testing software for potential vulnerabilities focuses on identifying hidden errors. While this white-box testing lets you uncover many errors, it is limited to those that are known. The approach is never 100% foolproof, as it gives no information about uncovered errors.  

Cannot Guarantee Functionality

Additionally, while software testing is designed and intended to improve the final functionality of the product for the end user, it is never a guarantee. While it can identify improper functioning, it by no means should be taken to assume that all possible errors have been identified and resolved. Exhaustive, rigorous testing still cannot predict with absolute certainty the functioning of the product. 

Clash of Resources

The clash of resources in software testing adds another major limitation to its role and effectiveness. Thorough testing requires an adequate time frame and attentive planning to be effective in its goal. Budget priorities however make this difficult, and the compromise is usually a more hurried testing plan to stay within budget limits. Any quality goals which would considerably improve functionality require time and effort that such constraints are unable to provide. 

Incomplete Testing Protocol

As testing cannot be conducted within system requirements and only against them, it leads to an incomplete testing protocol. Errors also cannot be detected, and levying unrealistic expectations of tools to conduct such tests wastes both time and effort. Meanwhile, the testing process remains inadequate to fulfill security demands of the project. 

Miscalculated Resources

In the same vein, time, budget and effort requirements are often miscalculated in accordance with what the project and the testing protocols require. This ends up costing the project, as the tool cannot be used to its full potential, nor can rigorous testing be carried out. That said, projects often incorporate too much dependence on testing tools, thereby using them as guarantee of secure and sufficient testing. This leaves potential vulnerabilities in the system that are overlooked and never tested for. 

Impossible to Test Every Aspect

The greatest limitation of any test protocol is that it can never be exhaustive enough. Every last cent of budget and time limit could be used up without ever running out of testing scenarios. It is not possible to test every path, or every valid or invalid testing input. This leaves the system always open to vulnerabilities. Even if the very last bug is found and resolved, there is no possible way to know or confirm this, leaving further progress dependent on assumptions and incomplete testing. 

The lack of absolute proof means no claims of the correctness of the product can be made. It is not possible to test every formal specification and ensure it is correct, based on which this claim can be made of the product. As a result, testing remains inhibited to the constraints of the testing tools and the testers’ ability to implement sufficient testing scenarios. 


A regular expression is a string of characters that defines a search pattern. It’s extremely helpful in terms of security, because it can be used across multiple infrastructure layers of a company. Here, we’ve explained how they work, what they do, and what their limitations are. For more guidance, be sure to check out our other articles on secure software development.

Code Analysis Tools

Code Analysis Tools

When developing an application or any other software, the security of the finalized product is one of the major concerns faced by developers. Security testing offers improved risk management for the individuals or businesses that are ultimately going to use the software. Many forms of security testing solutions work to identify and remove vulnerabilities before the software is deployed, as any flaws in it can be easily exploited by malicious third parties.

Using Dynamic Testing to Find Security Issues Early

Security testing of a program can be done in a number of ways. This can be done after a program is completed by a process called Dynamic Testing, while it is still under development of Static Testing, an integration of both through Interactive Security Testing or by Composition Analysis when testing security issues caused as a result of third-party dependencies.

Security Testing is a great way to identify the threats in the system and also helps developers in detecting all possible security risks in their program so that they can be solved. Many tools are available today to help developers with the time-consuming and elaborate process of manual testing, and using these tools can help developers in finding security issues along the SDLC.

How do Code Analysis Tools Work?

Using code tools to examine the code provides the developer with warnings that may be potential vulnerabilities. Each of these warnings is divided into many types and have different levels of severity assigned to them. 

But due to the complexity of the task and the security risks associated with it, these tools can not automate the process completely. The task of verifying the detected risks and identifying what can be a threat is left to the developer. These non-threatening errors raised by these analysis tools are called False Positives and require human actions to be identified and corrected.

These tools offer various uses, and some can be deployed along all phases of the program’s development, given that the tool supports the IDE and language that the developer is using. The analysis is performed based on predefined rules, which the developer can edit if they have the in-depth security knowledge required for the personalization. There is a wide variety of these tools available, each with distinctive features that you can utilize depending upon your program and work preference.

Some Famous Tools


Offensive 360 offers deep static code analysis. Provides SCA, malware, and deep source code analysis. The languages supported by this tool are:

  • C#
  • Java
  • Ruby
  • Javascript
  • XML

Some of the features offered by the tool are:

  • Quick and wide range of integrations
  • Works 100% without the internet
  • Provides an all-in-one solution: Malware, SCA, source code, and License analysis.
  • Automated Report Generation
  • Supports virtual compilers to attack the code from all angles.
  • AI verification of the obtained results 


PVS studio can perform static code analysis to help developers find vulnerabilities and problems in their code via reports. The languages supported by this tool are:

  • C, C++, C#
  • Java

Some features offered by the tool include:

  • Integration with Visual Studio
  • Error and bug tracking
  • Report generation
  • Automated recompilation file analysis


Saas-based analysis tool to help in the identification of vulnerabilities. The languages supported by this tool are:

  • Java
  • Java Script

Features offered by this tool are:

  • Prediction of false positives through machine learning
  • Vulnerability detection with fewer false positives
  • Pull request


This static code analysis tool is built on the Software as a Service (SaaS) model. It performs source code analysis from a security standpoint. Languages supported by this tool include:

  • C, C++, C#
  • Java
  • JavaScript
  • PHP
  • Python
  • Rub
  • TypeScript

The features offered by this robust tool are:

  • Dynamic and Static Security Scanning
  • Dynamic integration 
  • Wide range of languages


This tool offers real-time end-to-end source code analysis. It has an added benefit of a trial scan to analyze the range and integration of the tool before investing. The languages supported by the tool are:

  • C#
  • C
  • C++
  • Java
  • JavaScript
  • PHP
  • XML
  • Python

Features offered by the tool include:

  • Variety and ease of integration
  • Free Trial analysis
  • Automated analysis and result scanning to highlight critical errors first.

What to Look for in A Code Analysis Tool?

When choosing a specific Code Analysis tool, you must put a few factors into consideration:

User Friendliness

The tool must be easy to set up, use, and configure to provide the best user experience. A low false-positive is also a must as these can make testing unnecessarily complex and time extensive. 

Does it Work for You?

IDE Integration, language support, understanding of libraries and frameworks, and the extent of your knowledge of code security are the main factors in determining this. It is best to research a wide range of tools and find out which works best for your project, work style, and budget. 


The tool’s range of automation can affect the testing process’s time requirement. A wide range of detection and problem-solving automation is a great benefit to look out for when choosing a source code analysis tool. 

Detailed Detection and Reporting

As for the main feature, the tool must be able to perform a detailed detection analysis and report it in an easy-to-understand format to make it possible for even a developer inexperienced in code security methods to take corrective action. 

What are the Benefits of Using Code Analysis Tools?

Code analysis tools can simplify and secure the development process by giving developers feedback as they code, also helping them fix the issues before moving to the next stage of developing their application. These tools also provide a variety of benefits:

  • Remove the resource-extensive process of code reviews, which humans do.
  • Provide faster results than manual secure code testing.
  • Automatically identify most of the major vulnerabilities.
  • Improve the quality of the developed code.
  • Catch errors in real-time and early in development.
  • Provide an automated solution to security testing.
  • Give an in-depth test result report and display problematic code. 
  • Do not require code execution.


To ensure security of your final software product, code analysis tools — whether through static or dynamic analysis — identify vulnerabilities in the system so they can be resolved. This is an essential process, so we’ve helped you by explaining how they work, compiling some famous tools, and discussing how you can decide which code analysis tool is best for you. For more help on securing your software development process, check out our other articles on the subject.

Bad Coding Practices

Bad Coding Practices

Sometimes the development teams employ unconventional practices to fix bugs or add new features without realizing the importance of design principles. This choice makes it difficult to maintain the code and creates new challenges like:

  • Fixing one feature to break the functionality of another one.
  • Adding new code that does not support existing or future enhancements. 
  • Introducing complexities while understanding or maintaining the code.
  • Making feature testing difficult in isolation. 
  • Making it difficult to include new features.

Bad Coding Practices 

The easiest method to avoid mistakes and save costs is by understanding and identifying bad programming habits while adapting the better ones. Here are five bad practices that you should avoid while developing software:

  1. Leaving typos in the code: Typos are common in coding, even when it has nothing to do with the software developer’s programming abilities. A misspelled variable or function could induce vulnerabilities in the software, making it difficult to review. Developers can easily eliminate typos using an integrated development environment for a programming-focused text editor. Additionally, the developer can choose functions and variables that are easy to spell and spot.
  2. Failing to modularise the cryptogram: Most developers have a habit of writing long lines of code that become Complex and Tangle the control structure, making them unreadable during the review. Therefore, developers should write short code responsible for performing a single function. This approach allows the developer to keep the code easy to comprehend and maintain.
  3. Using hard-coded passwords: Secure software development is all about teamwork; every team member has different responsibilities to ensure data integrity and availability. However, some developers may find attempting to use hard code passwords so that no one could access the system without their express approval. Everyone working on the same project should have convenient access to the source code. If someone decides to leave the password in the source code, it could pose a big security risk, as data should not be embedded directly into the source code.  
  4. Writing code without the proper formatting for indenting: Following a proper format makes it easy to understand the code from a glance and identify errors. proper indenting makes it easier for other team members to maintain the source code as a consistent presentation. some developers might prefer using an IDE  that does not format the code automatically as it has less bloatware.
  5. Relying on the IDE for security: Developers prefer using an ID because they improve their productivity, but they also suggest variables and other elements without requiring the necessary effort. Even when the IDE can write the code itself, it does not mean that the code follows the necessary security protocols. Therefore, developers should only use the IDE to eliminate errors and improve productivity.


No matter how good a development team is, it can make mistakes. We wrote this article to discuss some common mistakes that you should avoid when developing your software, such as leaving typos or using hard-coded passwords. When it comes to software, it’s always better to be safe than sorry. That’s why we have written dozens of articles on secure software development and related processes like safe functions or design reviews. Check them out to develop the safest and most efficient software for your needs.

What is Data Security?

What is Data Security?

Data security implies keeping digital information safe from corruption, damage, and malicious parties. Data security procedures, tools, and policies focus on enhancing data protection, privacy, and safety. A robust data security management enables digital data protection against cyberattacks while also reducing the risk of insider threats and human error, which are major causes of data breaches and other similar threats.

Handling Data Safely

Whether it be protecting data due to legal regulations, personal information protections, or organizational resource requirements, handling data safely is a great practice to ensure privacy, confidentiality, and accessibility. Data security is crucial to preventing the reputational risk that accompanies a data breach. A cyberattack or loss of data can result in the loss of an organization’s reputation, an individual’s personal identity, or sensitive research data. 

Unauthorized access, cyber-attacks, and corruption and modification of data are among the major threats to consider when handling data, as these can be difficult to defend against without proper measures. Causing catastrophic damage to the data.

Neglecting safe data handling measures can also have major financial impacts in loss of personal credentials, user data, and lawsuits and fines that result from poor data handling. When handling data safely, there are many factors that come into play that must actively be considered to improve data security posture.


When handling data of any kind, whether it is corporate or personal, many threats must be considered to devise proper protective actions against them. Some threats that put digital data at risk are:

Accidental Data Exposure

Negligence in data handling can be a major threat to data security. Personal negligence, such as sharing devices that contain your sensitive data, accidentally exposing the data to third parties, losing data devices to theft, or due to mishandling, can all result in data corruption, loss, or theft. In a corporate or research environment, team members and employees who have access to the data can be the major source of causing this exposure and compromising sensitive information. 

Phishing Attacks

These manipulative attacks are caused by malicious third parties to trick authorized individuals with access to the data into providing the security or access details to them. These cybercriminals contact the victim as a trusted source to prevent raising any suspicion and deceiving them into sharing their private information or allowing them access to protected resources via malicious links or files sent to their inbox. 

Insider Threats

Insider threats result from people that have authorized access to the data, which intentionally or intentionally make it accessible to malicious third parties. Such authorized users may be unaware that their credentials have been compromised and are being used by malicious attackers to access sensitive data. On the other hand, these users may be intentionally trying to damage or steal the data for personal gain, just causing threats to the data due to negligence of proper security measures.

Cyber Threats

Cyber threats are focused attacks performed by malicious third parties on databases to gain access to the stored data. These utilize vulnerabilities in networks, codes, or applications found in the system to infiltrate the database. Some of the major cyber threats include:

  • Malware: Malicious software attackers use it to infect computers and corporate networks to cause data security threats like theft, damage, and extortion.
  • Ransomware: Ransomware attackers use variabilities to infiltrate systems and encrypt the data on them. These are caused to demand ransom for data safety.
  • SQLi: SQL injection attackers gain access to databases by injecting malicious code into the system to get third parties administrative access and steal or damage the data.

Security Measures

When handling data safely, proper measures must be taken to ensure safety from a wide range of threats posed to the sensitive information at hand. These measures include:

Data Access Controls and Management

Applying proper access controls and management frameworks enables proper authorization and authentication of all users that access data. Each user is allowed to access specific parts of the data while restricted from other unauthorized parts. Proper management of identities using techniques like multi-factor authentication and access privileges allow control over sensitive information within the database.

Data Encryption

Data encryption codes the data before storing it to make it unreadable even if a malicious user tries to access it. 

Data Loss Prevention

Data loss prevention enforces data protection policies to detect and notify if a potential data breach is taking place. It detects exfiltration and unauthorized sharing of information outside the organization.

Cloud Security

Data handling through the cloud means using cloud services to protect and store all sensitive data giving access to only authorized users who can access the data from anywhere via a network connection. 

Email Security

Email security prevents malicious attacks such as phishing attacks caused by malicious attachments or links. These ensure end-to-end email encryption and inbox controls to ensure secure data handling,

Handling Data Safely for Programmers

Using secure programming practices to ensure that the source code of an application is clear of any vulnerabilities is crucial to ensure that these are not exploited by malicious third parties to gain access to the system. Some of these practices are:

Authenticate Input

Authentication of user input is a great safety measure to secure data. Validate all inputs from untrusted data sources to remove software vulnerabilities.

Utilize Safety and Analysis Tools

Using the best compilers to compile the source code is also a great way to highlight loopholes or errors in the program. Furthermore, static analysis or dynamic analysis tools can also help in finding code errors and safety vulnerabilities. 

Security Policies and Access Control 

Dividing the system into subsystems based on privileges, access controls, and restrictions can help in keeping unauthorized users from accessing sensitive data. Denying access until conditions are met and providing users with the least amount of privilege necessary to undertake their tasks are great security policies to implement into your system. 

Server-side input validation is a good security measure and can be implemented in Microsoft ASP.NET using C#:

namespace ServerValidation.Models


    public class User  


        public string Name { get; set; }  

        public string Email { get; set; }          




Validating Name and Email, and displaying error message:

using System.Text.RegularExpressions;  

using System.Web.Mvc;   

namespace ServerValidation.Controllers  


    public class UserController : Controller  


        public ActionResult Index()  


            return View();  



        public ActionResult Index(ServerValidation.Models.User model)  


            if (string.IsNullOrEmpty(model.Name))  


                ModelState.AddModelError("Name", "Name is required");  


            if (!string.IsNullOrEmpty(model.Email))  


                string emailRegex = @"^([a-zA-Z0-9_\-\.]+)@((\[[0-9]{1,3}" +  

                                         @"\.[0-9]{1,3}\.[0-9]{1,3}\.)|(([a-zA-Z0-9\-]+\" +  


                Regex re = new Regex(emailRegex);  

                if (!re.IsMatch(model.Email))  


                    ModelState.AddModelError("Email", "Email is not valid");  





                ModelState.AddModelError("Email", "Email is required");  


            if (ModelState.IsValid)  


                ViewBag.Name = model.Name;  

                ViewBag.Email = model.Email;  


            return View(model);  





Using “index.cshtml” to support user input:


@model ServerValidation.Models.User  


    ViewBag.Title = "Index";  


@using (Html.BeginForm()) {   

    if (@ViewData.ModelState.IsValid)  


        if(@ViewBag.Name != null)  



                Name : @ViewBag.Name<br />  

                Email : @ViewBag.Email  






        <div class="editor-label">  

            @Html.LabelFor(model => model.Name)  


        <div class="editor-field">  

            @Html.EditorFor(model => model.Name)    



                <span class="field-validation-error">@ViewData.ModelState["Name"].Errors[0].ErrorMessage</span>   



        <div class="editor-label">  

            @Html.LabelFor(model => model.Email)  


        <div class="editor-field">  

            @Html.EditorFor(model => model.Email)   

            @if (!ViewData.ModelState.IsValid)   


                 <span class="field-validation-error">@ViewData.ModelState["Email"].Errors[0].ErrorMessage</span>   




            <input type="submit" value="Create" />  




Analyze Data Sent and Received From Other Systems

SQL injection and other such attacks utilize this data exchange aspect to make the system process malicious code that creates vulnerabilities. Creating a subsystem to analyze the context under which data is requested or received to ensure system and data safety.

It is necessary to ensure that all valid data is accepted and does not include dangerous code. A whitelisting approach can help in achieving this: 

Instead of a direct approach such as:

sprintf(buffer, "/bin/mail %s < /tmp/email", addr);



It is better to validate the data:


static char ok_chars[] = "abcdefghijklmnopqrstuvwxyz"



char user_data[] = "Bad char 1:} Bad char 2:{";

char *cp = user_data; /* Cursor into string */

const char *end = user_data + strlen( user_data);

for (cp += strspn(cp, ok_chars); cp != end; cp += strspn(cp, ok_chars)) {

  *cp = '_';



In order to help in developing threat mitigation strategies and ensuring that data is handled securely, adding multiple layers of security to your code to prevent security flaws and vulnerabilities, combining secure coding practices with secure runtime environments, performing penetration testing, source code audits and threat modeling practices are steps that need to be taken. Visit our other articles on safe programming and software development to help you go above and beyond to secure your digital design processes.

What is Error Handling?

What is Error Handling?

Error handling is the process of identifying errors and taking proper actions to ensure that any error relating to the code or execution is handled in a way that the program can continue to process uninterrupted. Error handling constitutes a major portion of any program’s code, dedicated to handling exceptions and error conditions. 

Error Handling

Catching and handling certain errors in various steps of software development is essential to ensure you don’t have to revise the whole code after writing or damage the user experience if the program does not function as intended or crashes without any warning. A major part of writing codes for developing applications is writing logic to handle possible errors that may arise during the software development and execution cycles.

An error exists if;  the code does not perform as it is intended to, the code damages the user (such as damage to the hardware, data, or progress), and if a code-facing error does not inform the user that an error has resulted.

Consequences of Bad Error Handling

When writing a program, it is best to understand that not all logic will work out as expected. A program often may not follow the normal path of execution either because of an error in the main execution path resulting in the program’s misbehavior or an error related to the logic used in the code. Not handling these errors by terminating the program after informing the user or completing the execution by passing it to another section of the code can result in misbehaving, crashing or corrupting user data.

Such a situation can lead to the termination of the program’s normal operations, and if those operations are critical such as a medical x-ray machine result display, driving automated cars, or guiding airplanes and ships, any deviation from the normal working of the program can be disastrous. 

What Good Error Handling Does

As error handling can be critical in defining a user’s experience with the program, good error handling can boost a program’s functionality and reviews. If you anticipate the possibility of errors occurring during the execution of your program, then it is best to take proper measures to handle them.

The first step of error handling is informing the user that an error has occurred. The program should let the user know about the error and possible steps that they can take to avoid it or possible reasons that might have resulted in that error without getting into technicalities.

After the user has been informed, the next step is to help the programmer debug the issue by providing information on how it resulted. It is mostly done through an email sent to the developer or a log file creation with event logs pertaining to the error. Such messages give developers all the information they need to find out the cause of the issue.

Types of Errors

Understanding the different types of errors is necessary and can help in finding various ways to handle them. Following are the types of errors:

Logical errors

A logical error is related to erroneous behavior resulting in an unexpected or wrong output. These are not recognized until the program is executed and does not produce the intended behavior.

Syntax (Compile-time) Errors

A syntax error is an error related to the coding language itself. These errors are also called compile-time errors because they are caught by the compiler and must be removed before the program can be executed. Syntax errors pertain to the clarity and usability of code, wrong placement of one letter character creates critical problems and makes the code incomprehensible to the compiler.

Runtime errors

Runtime error refers to an error that takes place during a program’s execution, as compared to the compilation errors that are identified during compilation. These may be bugs in the program or unsolved issues relating to the program, such as insufficient memory allocation.

Ways to Catch Errors 

Before handling an error, it must be identified. Three events can be used to catch and throw errors these are: 

Error Intermediate Event

These events can be connected to any activity from which an error is expected and then connected to the error handling measure. Such a process is called an error boundary event, in which if an error is found in an activity attached to the error intermediate event, the process flows along the sequence line to error handling measures associated with the event, and then normal processing of the program continues.

Error Event Subprocess

These events are not a part of the normal program sequence but are only used when the error start event associated with them is triggered in the main program. You can use error event subprocesses to handle errors in your process by defining a readable process and defining the error start event of the error event subprocess in the normal process of the program.

Error End Event

Error end events specify an error code and map to an error type, which is thrown from the process to the error-catching event that focuses on measures against these errors. Linking these processes and events can make the program sort so that errors can be captured and proper measures can be taken.

Ways to Handle Errors

After an error has been identified, proper measures are taken to handle the error depending on whether it can be resolved, the process can resume functioning, or if the program needs to be terminated. 

Returning error codes

Runtime error refers to an error that occurs during a program’s execution, compared to the compilation errors identified during compilation. These numerics signify the severity of the failure, information about the responsible subsystem, and an error code. In Windows, a 32-bit value based on the HRESULT data type is used for returning error codes. In Python, this error handling is displayed as a tuple using boost::tuple, or in C++, it is “std::tuple”:

boost::tuple FindName();

boost::tuple result ¼ FindName(); 

if (result.get<0>() ¼¼ OKAY) { std::cout << "Name: " << result.get<1>() << std::endl; }

Throwing exceptions

Throwing exceptions allows the error handling code to be separated from the normal functional flow, making the code easier to understand and edit. These are not limited to returning error codes to every error encountered and can handle multiple errors in a sequence. Errors can also be thrown to a later part of the process instead of handling them as they are encountered. In C++, exceptions can be accessible via a “what()” statement.

Aborting the program

Finally, if an error is too extreme to be safely handled or thrown, the program must be aborted. Many libraries have statements designed for this purpose, such as “abort()” or “exit()”.

Errors and Exceptions

In much smaller programs, error handling is incorporated into the program to ensure that no fatal errors are caused. But when concerned with larger projects, this process can be very time-consuming. For them, error handling gets converted into exception handling, in which instead of jumping to an error state after encountering an issue, the program jumps to an exception state which contains a predefined result or output which is displayed to the user or performed by the program.

Importance of Exception Handling in Programming your Software

Exceptions and error handling go hand in hand, working to improve the user experience and functionality of the program. If a program is unexpectedly terminated, freezes, or delivers an incorrect output, it can reduce the program’s dependability. 

Managing Errors and Exceptions

Managing errors and exceptions properly can result in a clean and easily editable code, improving its maintainability. Errors result from an abnormal or anomalous response from the program’s execution flow, and exceptions are used to streamline these events.

Mishandling or overflowing of exceptions can lead to even more errors and harm to the code by making it brittle, but properly managing exceptions has become a crucial element of modern programming. 

In Ruby, a general pattern of handling exceptions is as follows:



rescue SpecificError => e


  retry if some_condition_met?





Controlling exceptions rather than handling them immediately is a good practice. A good exception syntax with the use of “ if/else” conditions is given as:

try {

    line = console.readLine();

    if (line.length() == 0) {

        throw new EmptyLineException("The line read from console was empty!");


    console.printLine("Hello %s!" % line);


catch (EmptyLineException e) {



catch (Exception e) {

    console.printLine("Error: " + e.message());


else {

    console.printLine("The program ran successfully.");


finally {

    console.printLine("The program is now terminating.");


Best Practices to Utilize Exceptions

Following are some recommended practices to make sure that the exceptions implemented in your program are manageable and keep the code maintainable:

  • Use exceptions where solving the error makes the code complex and unmanageable.
  • Create a small separate code after analyzing the type of exception.
  • Create specific exceptions where possible and avoid using all general exceptions as they can complicate the process of error finding.
  • Create your own application-specific hierarchy of exceptions.
  • If creating a hierarchy is not possible, many languages have built-in exceptions.
  • Never rescue all exceptions simultaneously in the same general handler.
  • Handle the exceptions which are necessary, and expose the ones that are not.


Catching and managing errors is key to ensure you don’t have to revise your whole code if the program doesn’t work as it was meant to. Here, we’ve discussed how you can go about identifiying erros and exceptions before mitigating them to ensure a seamless user experience. There are many consequences to bad error handling, so it’s important to understand what good error handling does. I.e., understand what the different errors are and what you can do about them. If you would like further guidance on securing your software, take a look at our other articles on secure software development.