The Right FIX to Improve Testing Efficiency in Financial Exchange Systems

The financial services market could expectedly reach nearly $37.5 Trillion in 2027 at a CAGR of 7.5%. The Financial Information eXchange (FIX) protocol is rapidly gaining popularity among buyers and sellers in financial markets. Stock exchanges worldwide have adopted this protocol, enabling brokerage and trading firms to share orders and trade information electronically between systems. Testing these complex systems involves verifying syntax, transmission of FIX messages, and testing system logic, such as tag defaulting, order routing, message enrichment, and algorithmic behavior. Testing these systems effectively requires predictable simulation of all possible response types in different sequences.

Roadblocks to the Seamless Test Journey

Test engineers encounter numerous challenges when ensuring accurate testing of such systems. The limited working hours of exchanges, including holidays, session times, and paid bookings, shrink the test window. Continuous integration – continuous testing (CI/CT) failures result from unpredictable downstream responses, making it tough to replicate complex scenarios in manual and automated testing. Test engineers require different simulators per system for each exchange connection and specific custom tags using FIX rules of engagement. Thus, test planning and strategies involve endless time-consuming cycles of rework and waiting times.

Overcoming Exchange Simulation Limitations

Teams can overcome the limitations of Exchange provided test environments by leveraging a simulator. By simulating responses to each message, the test can yield accurate results. To achieve this, the team must test their software by writing stubs that represent the systems. While this methodology works mainly for unit and system tests, it helps teams gain initial confidence with the systems. End to end testing, manual exploratory testing and user acceptance must still rely on external test exchanges, which does not eliminate failures from random downstream responses, such as unexpected fills.

Considering Options for Downstream Response Control

In manual testing, achieving control of the downstream response relies on a trial-and-error approach. However, this unpredictability poses challenges for test automation and continuous integration. Simulators developed as part of the application under test are often highly specific and cannot be reused for other systems or overall tests.

Another preferred approach uses the automation framework to simulate replies, effectively encompassing the system under test. However, the pathways that an order message follows through a system, or a set of systems, are often complicated. This makes it challenging for the automation framework to track messages and send replies accurately. Additionally, this solution lacks reusability across systems and requires it to be built from scratch for each application.

Introducing the FIX Exchange Simulator

The ideal solution entails an independent, high-performance exchange simulator supporting the following key features:

  • Enable concurrent manual and automated tests
  • Seamless integration with different automation frameworks
  • Concurrent connection with multiple applications/environments
  • Real-time precise electronic control over responses, along with pre-configured response options
  • Support multiple versions of FIX protocol and custom tags
  • Allow easy simulation of complex negative scenarios
  • Single user interface (UI) to efficiently service multiple users
  • Support high load/volume to deliver optimal performance

Enterprises can unlock several benefits by implementing such systems, including increased exchange availability, shorter test cycles, improved manual testing processes, enhanced automation scripts and frameworks, higher accuracy, and improved overall performance. Additionally, they can leverage a single solution across multiple systems and seamlessly integrate it with multiple automation frameworks.


Adopting agile and DevOps has turned the focus on continuous testing and frequent, smaller releases. However, many firms are now retrofitting existing solutions to fit this new model, unintentionally compromising product quality due to inadequate testing. Individual teams often struggle to contribute to a large solution as they remain focused on their own priorities. This necessitates a comprehensive review of practices traditionally considered niche but with significant impact on quality engineering. The design of a multi-scenario exchange simulator can effectively address various time-consuming issues faced by testers and developers, leading to enhanced long-term productivity. It can enable uncompromised quality, ease of adoption, and maintenance. As a result, the time to market for changes will substantially improve, with shortened development and testing phases of the software development lifecycle (SDLC).


Author Details

Arun Shanmugam S.

Arun Shanmugam, a project manager with Infosys, has eighteen years of global experience in software engineering, testing, test-automation, business analysis, and project management. In his career, he has worked in the investment banking domain, ensuring critical applications are bug-free and compliant with regulatory and industry standards across front and middle-office functions. Arun holds a bachelor’s degree in production engineering from Anna University, Chennai. Beyond his professional pursuits, he enjoys reading and travelling.


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