What we offer

 

3 Types of Software to Test

 

Our performance testing expertise commonly includes three major software solution types:

 

• Internet-facing solutions — Web portals, e-commerce applications, social media, SaaS, etc.

• Enterprise software such as ERP, CRM and ECM solutions, including extranets, customer portals and other online services

• Mobile applications and mobile distributed solutions

 

6 Areas to Cover

 

Load testing

 

Code Q uncovers application behavior under a set of load variations based on use cases and business context. Relying on pre-defined metrics, Code Q estimates relevant indicator values, such as the maximum allowed number of concurrent connections or the response time limit for normal software system functioning.

 

Performance Testing

 

Code Q can help you measure the speed of your web app.

 

Stress testing

 

During stress testing, Code Q evaluates how the software behaves under stress loads, where its load resistance limit is, and how fast the software is able to restore after the load returns to normal.

 

Volume testing

 

We help evaluated software productivity in regard to the volumes of data stored and processed by the application. Our team transforms raw calculations into easily understandable metrics (e.g., number of users, required computing resources, etc.)

 

Scalability testing

 

Code Q reveals software solution capability to quickly increase productivity by adding new computing resources, amending architecture and making configuration changes.

 

Stability testing

 

Code Q checks application stability by testing under continuous loads (including 24/7 operation) to evaluate the risk of downtime and help schedule maintenance tasks.

 

3 Project Activities to Get Work Done

 

Analysis: Objectives, Research, Methodology

 

Code Q helps define clear business objectives for the performance testing project as well as formalize and prioritize detailed requirements for software performance within an appropriate business context. Research is based on application use cases, relevant business processes, the operational domain, the production environment, technology specifics, etc. As a result, Code Q recommends the best-match methodology for any performance testing project, as well as transparent testing metrics.

 

Testing: Planning, Executing, Interpreting Results

 

Based on preliminary research, we plan our testing activities and carefully align them with the customer’s milestones, processes and workflows. To execute a developed testing plan, Code Q runs a set of manual and automated tests revealing software performance metrics and the correlation with a number of factors such as concurrent connections and processed data volume. The Code Q team aggregates all test results into a comprehensive performance report for further interpretation.

 

Tuning: Optimal Hardware, Optimal Configuration, Eliminating Bottlenecks

 

Code Q develops recommendations to eliminate detected performance bottlenecks, and to plan optimal hardware and software configuration. The recommendations aim at reducing software downtime by increasing system scalability, improving productivity and avoiding efforts spent on system restoration.