What We Do

Parallocity provides automated runtime analysis tools that find high-impact errors in complex software applications. Customers in industries from networking to storage, security, cloud infrastructure, telecommunications, consumer electronics, and more benefit from:

  • Automating the detection of data races, deadlocks, memory errors, and memory leaks.
  • Slashing development time and cost while improving code quality.
  • Tracking test coverage and quality improvements with detailed code analytics.
  • Reducing the risk that costly, brand-damaging errors will surface in their production code.

How We Do It

Parallocity’s  Zeus Virtual Machine® (ZVM) Dynamic Analysis Framework represents a breakthrough in runtime software defect detection. ZVM analyzes the software’s source code, identifying and adding instrumentation only to key data structures prior to compilation of an instrumented binary image. This makes ZVM exceptionally fast, memory-efficient, and scalable. Traditional dynamic analysis tools work on the application’s binary image. Because they have no way of identifying key data structures they capture and analyze more data than is necessary. This leads to huge memory bloat and significant degradation of application performance. Both factors make these tools impractical for regression testing or for the analysis of large-scale or complex applications – use cases for which ZVM shines!

Our Products

Parallocity’s products are based on the Zeus Virtual Machine® (ZVM) Dynamic Analysis Framework. Customers use ZVM-U to automate error detection in user space applications and ZVM-K for loadable kernel modules and device drivers. Parallocity’s patent pending technology saves time and reduces cost by enabling single-pass detection of elusive data races, deadlocks, memory errors and memory leaks.  Best of all, ZVM tools report errors with deterministic precision and zero false positives, so you don’t waste time analyzing errors that don’t exist. Detailed error reports help bridge the gap between developers and QA engineers by providing contextual information and back traces for each defect as well as code analytics that highlight gaps in test coverage and offer insight for performance optimization.

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