Image result for manual vs automated code review

Manual vs Automated Code Review

Manual vs Automated Code Review

 

An unending battle between human and machine! A fight between what should be trusted, the human intuition or the machine. Code review is a systematic process to verify and check the produced code. The process has two different approaches to itself, Manual Code Review (MCR) and Automated Code Review (ACR). This article brings forward some of the points of differences between the two approaches.

To start with the basics, the Manual Code Review (MCR) is the process of reading the source code line by line to look out for possible vulnerabilities. This process demands a lot of skills, experience, and patience. The issues or errors identified in this type of review will help enhance the efficiency of the company. On the other hand, the Automated code review (ACR), verifies source code to conform with a predefined set of rules or best practices. It is a common development practice to use analytical approaches to analyze and evaluate source code to find vulnerabilities or security concerns.

Choosing and picking out the most suitable option from the two can get tricky. So, to make things easier for you, we have done a small comparative study of the two that help you in making this decision.

 

Image result for manual vs automated code review

 

Differences between manual & automated code review

 

1) Time:

  • MCR- The basis of the manual code review process is that in this procedure the reading of the code is done manually, line by line. Even though, because of this process identifying and detecting errors becomes easy, it takes a lot of time to read these codes line by line. In the evaluation process, developers need to be qualified and must be ready to conduct reviews. Before a developer is able to conduct manual code reviews effectively, it will take a full year of practice. Manual code reviewing is a long, repetitive, and tiring operation.

  • ACROn the contrary, the automated code review process is efficient enough that it can travel through and read thousands of lines of code in a few seconds. An automated code review tool must be thorough, effective, and highly statistical while making it easier for all types of developers to use and understand. With this benefit, it comes bearing a drawback that it lacks the skills of reading codes deeply and identifying errors if any. Along with this, the automated system is unable to understand and comprehend human intentions and logic behind a particular code or system.

2) Examination:

  • MCR- Manual analysis is outstanding at unwinding business logic and recognizing a developer’s intentions. In these areas, automated systems fail, resulting in false positives and, worse, missed problems. In crossing the seldom visited code paths, this strategy is very useful. It is easier to recognize these paths that are ignored by automated tools via a thorough manual code review. Manual research also better identifies vulnerabilities relating to authentication, authorization, cryptography, and overall data validation.

  • ACR- Automation tools that are much more advanced can also easily explore these deliberately secret routes, but the automated code analysis can ignore the intentions behind them. One way to increase the efficiency of automation is to apply code review procedures in which your colleagues review automated tests. You may find problems with automation with code review activities that could hinder research.

3) Subtle mistakes:

  • MCR– Since the reviews are conducted on an individual basis by testers, it is very possible that a few vulnerabilities related to integration or other isolated issues can be overlooked by the human eye. If the primary objective is to uncover bugs, keeping the consistency high is the secondary objective of code reviews.
    This is more subjective, but it is one advantage that cannot be offered by any other method of quality assurance. And the long-term longevity of your codebase can be just as critical as that. Although reading through code will find problems, some of the most common forms of more subtle errors are often easy to miss and neglect.
    Often, while it is easy to see errors in the code, it is not as easy to find the missing code. It is also useful to make a checklist of different types of errors to look for, depending on your technology stack, domain, and other variables.

  • ACR- Automated systems quickly catch these mistakes and minor errors that are overlooked in manual reviews. This automation, however, does not go beyond a certain review cap that can be achieved by manual code review.
    The point of this is that there is no way to decide whether the making of your first project is a successful identity verification problem with some form of automated tool. This doesn’t mean that, though, humans are always better than machines.
    When we start looking at bugs or flaws at the implementation level that occurs from configuration errors, we begin to see a number of situations in which a scanning tool can beat a human reviewer

4) Costs:

  • MCR-Having skilled and certified engineers to handle an effective manual code review is related to its apparent costs. It takes years of experience before a reviewer is able to handle feedback adequately.
    Creating powerful manual safe code review teams has an expense associated with it. In the evaluation process, engineers need to be qualified and must be ready to conduct reviews. Before an engineer is able to conduct manual safe code reviews effectively, it will take a full year of practice.
  • ACR- Reviewers do not need to have all the expertise and skills to review. The software for automation is designed to issue warnings of possible errors. Inside their development teams, several companies now do gradual code reviews and improvements as the software is developed. In terms of spreading awareness, finding problems early, and motivating individuals to write better code, this is also highly beneficial. Time is the only cost of this and the savings normally much outweigh that. 

Conclusion

Both these analysis and reviewing approaches have their own pros and cons. We, therefore, accept the challenge of selecting which one to go ahead with. Generally, because of time, expense, and effort, the trend is now moving to automated code review, but still, many businesses prefer to have a human touch. Hence, a combination of human and machine would be ideal.

Using any one of these should not be an option. This is particularly because design-level problems such as weak identity-verification issues can be identified only by humans, whereas automated instruments can be used for brute-force situations such as fuzzing or directory enumeration where manual testing would be too cumbersome and costly. Hence, the best tool for reviewing codes is a combination of manual and automated code review

Using the services of Codegrip will help you choose the best practice for your business. 

Fun Fact: There are a total of 698 programming languages! Click To Tweet

 

Related Post : Automated Code Reviews: Some Processes You Can Automate

You can get started with automating your code review process.
Sign Up with Codegrip and get started for Free!

Liked what you read? Subscribe and get fresh updates.

 

Post a Comment

I hope you’re enjoying this blog post

If you want our team at Codegrip to help you automate your code review process just connect with us.