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Applications used in the field of Big Data process huge amounts of information, and this often happens in real time. Naturally, such applications must be highly reliable so that no error in the code can interfere with data processing. To achieve high reliability, one needs to keep a wary eye on the code quality of projects developed for this area. The PVS-Studio static analyzer is one of the solutions to this problem. Today, the Apache Flink project developed by the Apache Software Foundation, one of the leaders in the Big Data software market, was chosen as a test subject for the analyzer.

So, what is Apache Flink? It is an open-source framework for distributed processing of large amounts of data. It was developed as an alternative to Hadoop MapReduce in 2010 at the Technical University of Berlin. The framework is based on the distributed execution engine for batch and streaming data processing applications. This engine is written in Java and Scala. Today, Apache Flink can be used in projects written using Java, Scala, Python, and even SQL.

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An analysis of Huawei’s source code.

Many companies have broken into the cloud market segment and created their own cloud services of various purposes. Recently our team has also been interested in integrating the PVS-Studio code analyzer into our own cloud infrastructure. Chances are, our regular readers have already guessed what type of project we will check this time. The choice fell on the code of Huawei cloud services.

You may also enjoy:  Using PVS-Studio to Get Beginners Familiar With Code Analysis Tools 

Introduction

If you’re following PVS-Studio team posts, you’ve probably noticed that we had been digging deep in cloud technologies lately. We have already published several articles covering this topic:

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Posting of projects sources by Microsoft is a good reason to perform their analysis. This time is no exception, and today, we will look at suspicious places found in Infer.NET code.

Briefly About the Project and the Analyzer

Infer.NET is a Machine Learning system developed by Microsoft specialists. Project source code has become recently available on GitHub, which gave rise to its check. More details about the project can be found here.


Source de l’article sur DZONE (AI)