New York, Feb 12 (SocialNews.XYZ) If you ever felt frustrated because the software updates that are intended to make our applications run faster inadvertently ended up doing just the opposite, there could be help at hand. Scientists have now developed a complete automated way of identifying the source of errors caused by software updates.
These bugs, dubbed in the computer science field as performance regressions, are time-consuming to fix since locating software errors normally requires substantial human intervention.
The new algorithm, based on a specialised form of machine learning called deep learning, is not only turnkey, but also quick, finding performance bugs in a matter of a few hours instead of days, said the study published in the journal Advances in Neural Information Processing Systems.
"Updating software can sometimes turn on you when errors creep in and cause slowdowns. This problem is even more exaggerated for companies that use large-scale software systems that are continuously evolving," said Abdullah Muzahid, Assistant Professor in the Department of Computer Science and Engineering, Texas A&M University in the US.
"We have designed a convenient tool for diagnosing performance regressions that is compatible with a whole range of software and programming languages, expanding its usefulness tremendously," Muzahid said.
The tool has been developed by researchers at Texas A&M University, in collaboration with computer scientists at Intel Labs.
When their algorithm was ready, the researchers tested if it could find and diagnose a performance bug in a commercially available data management software used by companies to keep track of their numbers and figures.
They found that their algorithm located and diagnosed the bug within a few hours. Muzahid said this type of analysis could take a considerable amount of time if done manually.
Source: IANS
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