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Building the foundation for a successful AI deployment

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Building the foundation for a successful AI deployment
Artificial intelligence, like any traditional business system or application, needs a solid foundation. Before embarking on complex applications, engineers must first resolve software reliability issues. Almost all software comes with undetected errors that can turn into serious production incidents, which will lead to an outflow of customers and burning hours of engineering resources in the future. It would be foolish to ignore the promise and threats proclaimed by AI; it is equally foolish to ignore the problems and risks associated with the unreliability of modern “conventional” software.

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Commercial pressure means that software development managers and their teams are forced to find a compromise between code quality and pressure to implement new product features. The Economist writes that some of the best programs ever written by NASA's Software Assurance Technology Center contained 0.1 errors per 1000 lines of source code. The reliability of most programs is many orders of magnitude lower than theirs. Tricentis, a testing platform provider, highlighted this issue in its 2018 Fail Watch report. He analyzed 606 software failures and found that more than 3.6 billion people were affected by these software problems, resulting in $ 1.7 trillion in lost revenue to software vendors.

Database vendors are particularly vulnerable due to high market competition, system complexity, and the high cost of insecurity. As a result, errors should be fixed as early as possible during testing. Unfortunately, many of them are difficult to identify, since they only slightly affect the program, so they do not seem to appear at the testing stage at all. Once in production, these errors can lead to serious crashes and software crashes.

Software reliability

To ensure that companies do not abandon the above scenario, engineering departments are encouraged to consider their software reliability strategy and take preventative measures to diagnose serious software defects before they cause chaos at the customer site. So what can software development teams do to make their software more reliable? The revolution in testing (continuous integration, development through testing, fuzzy testing, etc.) means that today you can run thousands of automated tests. A typical software project of a given size will perform thousands of times more tests than a similar project ten or twenty years ago. For the industry, this is a big leap forward. But all of these tests are a sorting nightmare if even a tiny fraction fails, especially if they fail periodically.

One possible solution to this trillion-dollar software reliability problem is to register flight software. By recording the execution of a program in the event of its failure, engineering teams receive a reliable reproducible test case, which gives them a complete picture of all the factors that led to the failure or incorrect behavior of the program. This approach is especially effective against intermittent test failures, which by their nature are very difficult to reproduce - a common problem in software development. Software crashes can then be captured, reproduced in a reversible debugger, and diagnosed orders of magnitude faster than using traditional methods. Such a solution as recording and playing back a program allows teams of software developers to accurately observe what their program was doing at any given time and why. This helps to speed up resolution times and minimize client disruptions.

Recording and playing a program is a revolution in the development and testing of software. Enterprises should worry less about fanfare orbiting artificial intelligence systems, and instead think about how to improve the foundation on which their business applications and products are built.

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