RPA Code Insight

When it comes to quality check and delivery methodology, Robotic Process Automation (RPA) Technology is no different than that of conventional IT implementation. While most of the critical RPA product players are busy selling over-simplification of the Technology leveraging visual programming approach, it makes sense to evaluate the outcome holistically on usage of common IT principles.

Due to lack of any automated code review approach, most of the enterprises are dependent either on manual reviews or sometimes even skipping this important aspect of the Implementation. This situation often poses enterprise level risks, longer stabilization time, impact on support cost, expected efficiency gains and finally impact on customer satisfaction.

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Readability

Ease of understanding the code by having elements like naming convention standards & compliance, zero usage of junk code, adequate componentization and simplified logic.

Configurability

Ease of managing changes and BOT calibration by having inclusion of configurable parameters like performance parameters, URLs, Files & folder paths, email Ids, credentials, business rule threshold parameters, log messages, email formats, etc. and generic design.

Reliability

Degree of accuracy with minimal exception rate by having elements like robust exception handling, usage of best possible interaction technique, memory leakage avoidance, and appropriately designed auto-recovery and auto-healing mechanisms.

Performance

Minimal average handling time by having elements like efficient delay management, parallel execution, usage of optimal interaction technique, efficient memory management and efficient business logic configuration.

Security

Degree of freedom from known and unknown threats by having policies and approach towards authorization & authentication, credential management, business data storage and sharing.

Sample output from Code Insight

Score

Score represents the compliance level of the code against each rule on a scale of 0 to 10, where 10 being the best score. While it provides us the quantitative measure of the code, it also help us to define the severity of the observation on any rule.

Observation

For each rule having score lesser than 10, observation is provided with the following set of data,

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