Top White Papers

Software security begins with flaw-free, standards-compliant code

Research shows that improving code security starts with developers.

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Security in practice: Creating bulletproof software

The ramifications of a security lapse are well known to business executives. Many of the largest brands in the world have paid a heavy price for failing to protect customer information.

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The business case for earlier software defect detection and compliance

Regardless of the industry your business operates in, software is likely all around it. Software powers our cars, airplanes, and even the medical devices we rely on to diagnose and treat illness...

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Four strategies to reduce your open source risk

Try to think of a single system in the world that hasn’t been touched by open source software...

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White Papers

Prototype to production with IMSL Numerical Libraries

In the development of software that requires advanced math, statistics, or analytics, there is often a disconnect early in the development process. This occurs at the transition from algorithm selection and testing to the beginning of coding in the actual compiled language. We refer to this as the prototype to production transition.

To address the disconnect during prototype to production, we are presenting a method to run IMSL Numerical Libraries routines in R or Matlab. The goal is not to replace the algorithm developer’s tool of choice but to run a compiled version of the code in parallel. Pitfalls can be caught early, and data discrepancies can be resolved quickly by running the script version and compiled version side by side.

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Deterministically troubleshooting network distributed applications

Debugging is all about understanding what your software is really doing. Computers are unforgiving readers; they never pay attention to what you mean, and always insist on doing what the code says.

Debugging happens naturally when actively developing code and troubleshooting a problem. The same kind of investigation is also a great way to learn about programs that are working just fine. It pays to look closely at what programs are really doing when you re-introduce yourself to code that you wrote a long time ago, or when you try to understand a new bit of code that you encounter for the first time.

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Car cybersecurity: What do the automakers really think?

The Ponemon Institute recently conducted a cybersecurity survey sponsored by Rogue Wave Software and Security Innovation of over 500 automotive developers, engineers, and executives, primarily from automotive OEMs and tier one suppliers.

This paper analyzes the survey results, and provided new insights to help automotive software suppliers understand the current mindset of their developers and build security and safety into their software.

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Increase system availability by leveraging Apache Tomcat clustering

Open source is the dominant force in software development today, with over 80 percent of developers now using open source in their software. With an increase in use of open source software (OSS), support and knowledge of these packages becomes critical to companies. Apache Tomcat is one of the most popular open source software implementations in the industry, and one of the most requested support packages to Rogue Wave OSS support experts. Support requests related to Apache Tomcat cover many aspects of the software, but a popular topic is always high-reliability and clustering.

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Tech tutorial: Embedding analytics into a database using JMSL

Responding to the many challenges of Big Data means coming up with specific tactics and tools for specific problems, such as using Hadoop and the MapReduce framework for storing and processing very large data sets. Hadoop embodies one of the fundamental changes in Big Data, bringing the algorithms to the data instead of separating the analysis from the storage.

One specific tactic to bring the algorithms to the data is to embed analytics into the database. This paper presents a walkthrough, with code samples, of how to embed JMSL predictive analytics into an Oracle 12c database, using the Naive Bayes classifier algorithm and an example test data set. The complete Java code for this exercise is presented in the appendix.

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See it for yourself: Analytics in IMSL C# vs. R

Statistical analysis and desktop modeling are often performed with software such as the well-known R Project yet sometimes a more robust and fully-featured framework is required. It's also common for statisticians and programmers to spend time re-implementing functions and not realize that they already exist elsewhere.

Using this MSDN article as a starting point, this paper offers up an alternative way of deploying statistical analysis: the IMSL.NET Numerical Library (C#). By walking through the examples presented in the article, you will see how the same numerical results are achieved in less time and with less complexity than trying to do it in R.

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Using JMSL in Hadoop MapReduce applications

The excitement around big data is the expectation of better results and new insights as we take more accurate measurements of our world. Among the many important considerations to help reach this potential is deciding how to perform efficient mathematical and statistical analysis on the data when traditional storage methods are no longer feasible, reasonable, or possible. The answer is to combine Hadoop MapReduce with JMSL Numerical Libraries.

Learn more by walking through a few technical examples and code of how to use JMSL Numerical Libraries in Hadoop MapReduce applications.

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Top 3 strategies to reduce risk in automotive / in-vehicle software development

Developing in-vehicle embedded applications is a safety, security, and quality challenge. Given that cars and trucks are increasingly connected to each other and to the devices around them, it’s becoming harder and harder to ensure that software is functional and free from risk. Development teams, especially the managers who are ultimately responsible, face incredible challenges when building such applications, and are learning that team members need to do more than just catch code defects during verification and validation testing. The new imperative: Identify and address security and compliance concerns earlier in the lifecycle, all while delivering innovative and differentiating features.

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