Top White Papers

A fast, scalable solution for solving the transportation problem

While the family of transportation problems can be solved by hand, at least for relatively small problems, the IMSL Library includes an algorithm that is fast and scalable.

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7 questions to select, deploy, and maintain open source software effectively

A question that often comes up in enterprise software organizations is: What happens when open source software doesn’t work?

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Prioritize defects faster with Klocwork SmartRank

The faster a bug is identified in code, the easier it is to fix. Klocwork SmartRank helps identify which issues to fix first.

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Enterprise API management defined

Defining API management and the best path to quickly capitalize on new revenue channels without assuming risk along the way.

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White Papers

Memory error analysis in distributed applications

Memory bugs can have a disastrous effect on an applications usability. They are hard to track down because a variety of different situations cause them including overwriting the stack, not freeing the heap, or freeing it at the wrong time. It's difficult to trace back to a specific line of code because it can take a long time to manifest. And having to boot everyone off servers periodically and restart doesn't suffice when people rely on these servers. Read this paper to understand the root cause and how to resolve memory bugs.

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Lessons learned: Using a static analysis tool within a continuous integration system

Static analysis tools are used for improving software quality and reliability. Since these tools can be time consuming when used for analysis of big codebases, they are normally run during scheduled (e.g. nightly) builds. However, the sooner a defect is found, the easier it is to fix efficiently.

In order to detect defects faster, some analysis tools offer an integration with the integrated development environment of the developers at the cost of not always detecting all the issues. To detect defects earlier and still provide a reliable solution, one could think of running an analysis tool at every build of a continuous integration system.

In this IEEE paper, we share the lessons learned during the integration of the static analysis tool Klocwork (that we are developing) with our continuous integration system. We think that the lessons learned will be beneficial for most companies developing safety-critical software (or less critical systems) that wish to run their analysis tool more often in their build system. We report these lessons learned along with examples of our successes and failures.

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API essentials for every stakeholder

APIs, by virtue of their openness and utility, tend to touch many areas of an IT organization. As a result, API success usually means devising an API strategy that will serve the diverse needs of people in various roles who rely on them. The right tooling for API design and management are essential to ensure that all roles feel served by the API strategy. This can be as much an organizational issue as a technical one.

This paper reviews some of the key players who have a stake in API strategy, including API designers, integration developers, API product managers, operations leads, security architects, and enterprise architects. It looks at how an API platform (or platforms) can address the distinctive needs of each role as they come to devise and implement an API strategy.

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Use support vector machines in JMSL

Support vector machines were implemented as part of the latest release of JMSL, along with expanded data mining functionality, including areas such as decision trees and bootstrap aggregation. The documentation of the IMSL Libraries is detailed and robust, but the algorithm discussion and examples can only cover a finite set of use cases.

This white paper will walk you through examples not covered in the documentation, with a focus on classification. We start with the textbook examples that are part of most SVM resources, providing notes and key points throughout.

Download this complimentary resource now, and receive access to a full code example which follows the examples outlined.

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Using IMSL C on relational data with SourcePro DB

SourcePro DB supports a wide variety of databases and can be used to retrieve, manipulate, and analyze data, including very large data, using the statistical analysis functions provided by the IMSL C Numerical Library.

This paper provides a code example that uses SourcePro DB to harvest data from a database, analyzes that data using IMSL C, and then updates the database with the processed data.

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