Research Papers

Analysis of the Characteristics and Causes of Underestimated Bug Reports

The bug-fixing process requires software maintenance resources. Usually, defects are submitted, fixed and closed, but sometimes they have to be reopened because of a change of resolution. It happens when a defect was evaluated incorrectly at the beginning. This problem can increase maintenance costs and software quality in general. In this paper, we investigate the characteristics of such defects and their bug reports and call them “underestimated”. Our research is based on general statistical indicators and text descriptions of defect reports. We propose using different methods of feature selection and ranking in order to reveal the significant terms of such defects. The top of significant terms of the underestimated bug reports can help to find the root causes of such life cycles.

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Towards a Formal Modelling of Order-driven Trading Systems using Petri Nets: A Multi-Agent Approach

Electronic trading systems provide the computational support for stock exchanges. Liquid markets use order-driven systems, i.e., where client requests, for trading financial instruments, are served through individual orders. This paper presents Petri net models assembling some crucial processes executed within order-driven systems such as orders submission, application of precedence rules, and the order matching mechanism. Such processes were modelled as types of agents running in a multi-agent system (MAS) using nested Petri nets (NP-nets) - a convenient formalism for modelling MAS. With NP-nets, we focus on the control-flow perspective (causal dependence between activities executed by agents) and in the synchronization between agents. Conversely, we have used coloured Petri nets to extend the model including orders as objects with attributes. Thus, this work with Petri nets represents an experimental & initial research phase to validate trading systems using related methods such as process mining, simulations and model checking.

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ClearTH Test Automation Framework: A Running Example of a DLT-Based Post-Trade System

The paper presents an overview of a test automation framework aimed at end-to-end functional and non-functional testing of DLT-based hybrid financial software for post-trade. The proposed solution comprises the components designed for testing user-facing parts of the SUT as well as business logic specific for different DLT-based architectures. This combined approach is seen as a viable solution of the problem of the SUT complexity as well the variety of possible DLT architectural decisions.

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User-Assisted Log Analysis for Quality Control of Distributed Fintech Applications

Testing of distributed systems is a complex task, which is hampered by the impossibility of guaranteed reproduction of errors associated with race conditions. Even minor instrumentation of the system significantly changes its characteristics, which becomes critical, especially for load testing. All of that increases the importance of quality control methods based on the system log analysis. In this paper, we present our experience of semi-automated analysis of the behavior of clearing and settlement system by utilizing its logs for the purpose of identifying and classifying errors.

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Creating Test Data for Market Surveillance Systems with Embedded Machine Learning Algorithms

Market surveillance systems, used for monitoring and analysis of all transactions in the financial market, have gained importance since the latest financial crisis. Such systems are designed to detect market abuse behavior and prevent it. The latest approach to the development of such systems is to use machine learning methods. The approach presents a challenge from the standpoint of quality assurance and the standard testing methods. We propose several types of test cases which are based on the equivalence classes methodology. The division into equivalence classes is performed after the analysis of the real data used by real surveillance systems. This paper describes our findings from using this method to test a market surveillance system that is based on machine learning techniques.

Olga Moskaleva, Researcher, Exactpro, London Stock Exchange Group
Anna Gromova, Researcher, Exactpro, London Stock Exchange Group

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Reconciliation Testing Aspects of Trading Systems Software Failures

This paper describes the concept of reconciliation testing - a process of using data reconciliation tools to validate the system in parallel with other activities. The authors studied information about two major software failures in electronic trading area: Facebook IPO on NASDAQ and Knight Capital runaway algorithms. This paper contributes to the subject matter by identifying aspects related to data reconciliation during these two events. The authors discuss the balance between automated and manual reactions to discrepancies reported by reconciliation tools and analyze the necessity of introducing reconciliation testing as part of system development life cycle for complex transactional processing systems.

Anna-Maria Kriger, Kostroma State Technological University
Alyona Pochukalina, Obninsk Institute for Nuclear Power Engineering
Vladislav Isaev, Yuri Gagarin State Technical University of Saratov

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