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8 Tips to Maximize Salesforce Code Analysis

Josh Rank
February 23, 2022

A combination of best practices and powerful tools is the best way to improve the quality of your code and consistently produce secure applications and updates.

Why It Matters: Even the best developers make the occasional mistake. So putting systems in place to perform a Salesforce code analysis supports numerous aspects of a successful Salesforce DevSecOps pipeline.

Producing consistently high-quality, secure applications and updates is impossible without reliable coding structures.
Selecting appropriate tools and processes enables team members to produce the best products.
Utilizing automation reduces manual touchpoints and avoidable errors.

Here are 8 best practices for Salesforce code analysis:

Utilize Automation
Incorporate with CI/CD
Evaluate Existing Technical Debt
Address Metadata
Define Expectations
High Level + Low Level Analysis
Integrate with Popular Plugins
Create Reusable Processes and Refine Them Over Time

1. Utilize Automation

Manual processes are time-consuming, costly, and vulnerable to human error. Even the most talented team members make mistakes, especially when performing a repetitive task such as analyzing large amounts of code. Introducing automation to Salesforce code analysis offers immediate benefits in quality and speed.

Automated code analysis increases team member productivity by taking repetitive, time-consuming tasks off their hands.

Static code analysis is an integral part of an optimized Salesforce DevOps strategy. Testing code is an essential step when releasing an update or application. But automating that process strengthens your products. And increasing those automated processes gives your team back the time they would otherwise have spent performing code reviews, all while boosting your productivity and release velocity.

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2. Incorporate with CI/CD

A synergistic approach to DevOps yields the greatest results. And the best way to accomplish this is to utilize as many specialized tools as possible to streamline the various stages of the development cycle. Every stage of testing feeds into the next and contributes to the overall quality of an application or update.

Implementing continuous integration and continuous delivery/deployment (CI/CD) expands the benefits of a Salesforce code analysis tool.

Multiple layers of automated testing ensure bugs and errors are found before they become larger issues. CI/CD adds another layer of security to the code review process.

These tools work together to provide a comprehensive approach to testing, ensuring that the eventual product is secure and stable. And since these processes are automated, they’re performed quickly and precisely without error.

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3. Evaluate Existing Technical Debt

Any outstanding errors or bugs can become data security vulnerabilities and pose a significant risk to your overall environment. Clearing up these issues not only works to secure your Salesforce instance, but also supports future development through the mitigation of overall risk.

Technical debt creates extra work for your development team, preventing them from writing new code and furthering outstanding projects.

Assessing and mitigating the technical debt that currently exists within production orgs paves the way for successful Salesforce code analysis. This process can even be addressed with a static code analysis tool.

But creating clean, new code won’t impact the bugs and errors that already exist within your Salesforce environment. So if your team was manually performing code reviews, it’s very likely your system contains legacy errors that must also be addressed.

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4. Address Metadata

Metadata exists in the background of every aspect of your Salesforce environment. Every process, customization, field, and more contributes to the ever-growing amount of metadata in your system. And this metadata needs to be addressed and protected just as much as other types of system data to ensure continued operations.

Lost, damaged, or corrupted metadata can lead to a breakdown in processes and improper functionality in your Salesforce code analysis.

Addressing metadata with a static code analysis tool ensures total visibility into the health of this important aspect of your environment.

Failing to address metadata can lead to errors in processing data, fields that don’t properly populate, and loss of other types of essential data. A holistic approach to Salesforce data is the best way to keep your operations running smoothly and your systems safe.

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5. Define Expectations

What do you hope to gain from your Salesforce code analysis efforts? Sure, everyone wants error-free code, but you can go even deeper than that. Perhaps you want to streamline your processes. Or maybe you want to increase your number of releases per year. Are you looking to locate and rectify a growing backlog of technical debt?

Knowing what you want to accomplish will direct your efforts and help allocate resources to appropriate areas.

A proper code analysis strategy must take a variety of factors into consideration. The very first consideration needs to illuminate what you hope to gain from your efforts. Setting a concrete strategy will help guide your decisions and give you a rubric to judge success moving forward.

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6. High Level + Low Level Analysis

Complete oversight of code health—and the processes a business utilizes to achieve high quality products—requires multiple levels of analysis.

First, and perhaps most apparent, are the line-by-line analyses of the lines of code themselves. This includes checking for proper structures, overwrites, and other potentially harmful interactions between lines of code.

Second, proper Salesforce code analysis should also include a high-level view of the review process as a whole. How long did the process take? How many lines of code were addressed? Was the deployment successful? Were errors found later in the project pipeline?

These types of insights will show how successful your code analysis efforts actually are and point to potential improvements.

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7. Integrate with Popular Plugins

Many development environments will inevitably include a series of customizations. Developers can take that a step further and integrate a new development environment through IDE plugins. The DevOps tools you use for code analysis, CI/CD, and anything else will need to work within these plugins just as well as they would in a standard Salesforce environment.

Sourcing quality tools with the flexibility to meet your team’s specific needs supports a successful code analysis and equips your DevOps team.

Editor plugins are a great way to properly test your applications and updates. And plugging a Salesforce code analysis tool into them makes them even more powerful. Specializing your development environment to suit your team’s individual needs creates a more comfortable working environment.

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8. Create Reusable Processes and Refine Them Over Time

The best DevOps processes are those that have been altered to meet evolving needs. Refining your approach requires sustained attention. Taking the time to investigate what worked and hone what didn’t in a singular project will inform future efforts and lead to more successes.

Templatizing your code analysis process reduces time spent planning each project.

Static code analysis tools simplify the process of ensuring proper stability of coding structures. However, the surrounding processes in the DevOps pipeline can—and should—continue to be tweaked over time.

Finding a rhythm and continually refining it lets your team know what to expect. And time saved avoiding needless adjustments contributes to streamlined efforts and better projects created more quickly.

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Next Step…

Did you know that static code analysis also helps support your Salesforce data security strategy?

Click here to learn more about how strong, error-free code keeps your Salesforce environment secure.

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FAQs

How does static code analysis work?

Static code analysis offers many benefits, but the most instantaneous are the immediate alerts in the development environment. If you’ve ever used a word processor with spellcheck, then static code analysis will feel very familiar. You know when spelling a word wrong, how the program puts that red, squiggly line beneath the word? That’s essentially it. The static code analysis tool highlights coding errors as soon as they’re entered so developers can quickly and easily rework them before they have a chance to corrupt other aspects of the project.

Does using a static code analysis tool balance out the cost of the tool itself?

The answer to this question is different for every environment. For instance, a company that produces several large releases each year will definitely see a positive ROI from their static code analysis tool. If your team only produces incremental updates with no urgency, it might be a wash. The smartest way to make an educated guess as to your potential benefit from utilizing a static code analysis tool is to look at the amount of time your team spends on code reviews, and how often bugs and errors make it to your live environment (taking into account that errors often go unnoticed until they are exploited by cybercriminals). In general, every Salesforce environment will benefit from reduced manual processes, strengthened code, and expedited production cycles. The degree to which you benefit depends on your scale of operations.

How does clean code support Salesforce data security?

The products produced by your Salesforce DevOps pipeline are supposed to increase functionality or offer new services. Any bugs or errors in the coding structure can lead to misfires, slow performance, or a total breakdown of operations. These scenarios become more likely with every mistake that moves through production. And while these errors create a poor experience for end users, they can simultaneously create opportunities for bad actors to exploit vulnerabilities and gain access to your system.

Tags: code quality, salesforce code analysis, salesforce DevOps, salesforce static code analysis tool

8 Tips to Maximize Salesforce Code Analysis

1. Utilize Automation

2. Incorporate with CI/CD

3. Evaluate Existing Technical Debt

4. Address Metadata

5. Define Expectations

6. High Level + Low Level Analysis

7. Integrate with Popular Plugins

8. Create Reusable Processes and Refine Them Over Time

Next Step…

FAQs

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