Self sustained regression testing framework

A system comprising:

• a non-transitory memory storing instructions;
• and
• one or more hardware processors coupled to the non-transitory memory and configured to read the instructions from the non-transitory memory to cause the system to perform operations comprising:
• identifying a plurality of payloads that correspond to scenarios in a production computing environment, wherein each payload includes a request and a response for a transaction that passes through a distribute computing system;
• determining hashes for the plurality of payloads by:
• identifying multiple attributes in a plurality of attributes in each payload in the plurality of payloads, wherein the multiple attributes include data from the transaction;
• and
• determining a hash of the identified multiple attributes in the each payload;
• aggregating payloads in the plurality of payloads that have a same first hash in the hashes into a first set of payloads;
• aggregating payloads in the plurality of payloads that have a same second hash in the hashes into a second set of payloads;
• selecting a first payload from the first set of payloads aggregated according to the first hash and a second payload from the second set of payloads aggregated according to the second hash into a set of unique payloads, wherein the first payload includes values of the multiple attributes different from values of the multiple attributes in the second payload;
• creating user data, wherein the user data is associated with the set of unique payloads;
• testing the set of unique payloads with the user data in a first testing environment to generate expected results, wherein the first testing environment includes software components in the production computing environment;
• testing the set of unique payloads with the user data in a second testing environment to generate actual results, wherein the second testing environment includes the software components in the production computing environment and new software;
• comparing the expected results with the actual results;
• and
• identifying an error in the new software based on the comparing.

A non-transitory machine-readable medium having stored thereon machine-readable instructions executable to cause a machine to perform operations comprising:

• identifying a plurality of payloads that correspond to scenarios in a production computing environment;
• determining hashes for the plurality of payloads by:
• identifying a subset of attributes in each payload in the plurality of payloads, wherein the subset of attributes include data from the production computing environment;
• and
• determining a hash of the identified subset of attributes in the each payload;
• aggregating payloads in the plurality of payloads that have a same first hash in the hashes into a first set of payloads;
• aggregating payloads in the plurality of payloads that have a same second hash in the hashes into a second set of payloads;
• selecting a first payload from the first set of payloads aggregated according to the first hash and a second payload from the second set of payloads aggregated according to the second hash into a set of unique payloads, wherein the first payload includes values of the subset of attributes different from values of the subset of attributes included in the second payload;
• creating user data, wherein the user data is associated with the set of unique payloads;
• testing the set of unique payloads with the user data in a first testing environment to generate expected results, wherein the first testing environment includes software components in the production computing environment;
• testing the set of unique payloads with the user data in a second testing environment to generate actual results, wherein the second testing environment includes the software components in the production computing environment and new software that modifies at least one software component in the software components in the production environment;
• comparing the expected results with the actual results;
• and
• identifying an error in the new software based on the comparing.