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In Theory: Automatic Unit Testing with Plang

This post dives into Plang, an intent-based programming language that interprets natural language. For more, visit plang.is or get started here. In Plang, you can bind events to goals and steps, which opens up a fascinating possibility…

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This post dives into Plang, an intent-based programming language that interprets natural language. For more, visit plang.is or get started here.




In Plang, you can bind events to goals and steps, which opens up a fascinating possibility for automatic testing. Let's walk through an example, starting with something simple: adding two numbers.






A Simple Example: Adding Two Numbers



Here’s a basic code snippet in Plang:




AddTwoNumbers
- %num1% + %num2%, write to %sum%
- write out %sum%






To build automatic unit tests, let's first think about the usual process of testing logic manually. Without automation, you’d run something like this:




plang num1=1 num2=2






This would output:




3









Automating the Process



Because Plang lets us bind events to steps, we can automate this process. For example:




Events
- before each step, call PrepareUnitTest
- after each step, call MakeUnitTest






Here’s how it works:




  • The PrepareUnitTest goal stores the variables in the current step.

  • The MakeUnitTest goal captures the output, like the value of %sum%.



Once that’s in place, we can even ask the LLM to generate unit tests for us. This results in a JSON file with the relevant test values.






A Developer’s Interface



At this point, a developer would likely need a simple interface—a GUI—to tweak those values, add new tests, or remove unnecessary ones. Each module would define its own rules for unit testing, especially for handling I/O operations like HTTP requests, which would require special considerations.



With this setup, automatic testing becomes a streamlined part of the development process, enhancing efficiency and reliability in Plang projects.






In Theory



This post is titled In Theory because, at this point, automatic unit testing with Plang is just that—a theory. It hasn’t been implemented or tested yet, but there’s no reason it couldn’t be. The concept is sound; it’s just a matter of engineering time.






More Information



Interested in learning more about Plang? Here are some useful resources to get started:



1. Sofort-Triage & Abwehrmaßnahmen

SOC Incident Playbook: Remote Code Execution (RCE) Defense
Syntax validiert (0 Fehler)
title: Detect Exploitation - In Theory: Automatic Unit Testing with Plang
id: 8b43f737-e787-49ae-988c-79aa4c0345ac
status: experimental
description: Automatisch generierte SIEM-Erkennungsregel basierend auf CTI Intelligence
references:
  - https://tsecurity.de/
author: iShareStuff CTI Automated Detection Engine
date: 2026-09-25
logsource:
  category: network_connection
  product: any
detection:
  selection:
      CommandLine|contains:
        - 'exploit'
  condition: selection
falsepositives:
  - Legitime administrative Zugriffe oder Penetrationstests
level: high
tags:
  - attack.initial_access
Syntax validiert (0 Fehler)
rule CTI_Threat_Indicator {
    meta:
        author = "iShareStuff CTI Automated Detection Engine"
        date = "2026-09-25"
        description = "YARA Signature for "
    strings:
        $str = "In Theory: Automatic Unit Test" ascii wide
    condition:
        any of them
}
Syntax validiert (0 Fehler)
index=security sourcetype IN ("cisco:asa", "pan:traffic", "zeek_conn", "suricata", "WinEventLog:Security")
("In Theory Automatic Unit Testing with Pl")
| stats count earliest(_time) as first_seen latest(_time) as last_seen by src_ip, dest_ip, dest_host, signature
| eval first_seen=strftime(first_seen, "%Y-%m-%d %H:%M:%S"), last_seen=strftime(last_seen, "%Y-%m-%d %H:%M:%S")
| sort - count
Syntax validiert (0 Fehler)
message: "*In Theory Automatic Unit Testing with Pl*"
Syntax validiert (0 Fehler)
CommonSecurityLog
| where Message has "In Theory Automatic Unit Testing with Pl"
| summarize EventCount = count(), FirstSeen = min(TimeGenerated), LastSeen = max(TimeGenerated) by SourceIP, DestinationIP, DestinationPort, Activity
| extend DetectionRule = "iShareStuff-CTI-Compiled"
| sort by EventCount desc

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Impact
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Fokus-Vektor:

Kognitive Analyse für identifizierte Bedrohung: Erhöhte Bedrohungslage im Bereich In Theory: Automatic Unit Testing with P.... Basierend auf 368k Vektor-Korrelationen werden sofortige Isolationsmaßnahmen für betroffene Endpunkte empfohlen.

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