Opaque Service Virtualisation: A Practical Tool for Emulating Endpoint Systems

Large enterprise software systems make many complex interactions with other services in their environment. Developing and testing for production-like conditions is therefore a very challenging task. Current approaches include emulation of dependent services using either explicit modelling or record-and-replay approaches. Models require deep knowledge of the target services while record-and-replay is limited in accuracy. Both face developmental and scaling issues. We present a new technique that improves the accuracy of record-and-replay approaches, without requiring prior knowledge of the service protocols. The approach uses Multiple Sequence Alignment to derive message prototypes from recorded system interactions and a scheme to match incoming request messages against prototypes to generate response messages. We use a modified Needleman-Wunsch algorithm for distance calculation during message matching. Our approach has shown greater than 99% accuracy for four evaluated enterprise system messaging protocols. The approach has been successfully integrated into the CA Service Virtualization commercial product to complement its existing techniques.Comment: In Proceedings of the 38th International Conference on Software Engineering Companion (pp. 202-211). arXiv admin note: text overlap with arXiv:1510.0142

Improving Software Quality and Productivity Leveraging Mining Techniques: [Summary of the Second Workshop on Software Mining, at ASE 2013]

The second International Workshop on Software Mining (Soft-mine) was held on the 11th of November 2013. The workshop was held in conjunction with the 28th IEEE/ACM International Conference on Automated Software Engineering (ASE) in Silicon Valley, California, USA. The workshop has facilitated researchers who are interested in mining various types of software-related data and in applying data mining techniques to support software engineering tasks. During the workshop, seven papers on software mining and behavior models, execution trace mining, and bug localization and fixing were presented. One of the papers received the best paper award. Furthermore, there were two invited talk sessions presented by two active researchers from software engineering and data mining community.</jats:p

Interaction traces mining for efficient system responses generation

Software service emulation is an emerging technique for creating realistic executable models of server-side behaviour. It is particularly useful in quality assurance and DevOps, replicating production-like conditions for large-scale enterprise software systems. Existing approaches can automatically build client-server and server-server interaction models of complex software systems directly from analysis of service interaction trace data. However, when these interaction traces become large, searching an entire trace library to generate a run-time responses can become very slow. In this paper we describe a new technique that utilises data mining, specifically clustering algorithms, to pre-process large amounts of recorded interaction trace data. With the obtained clusters we facilitate efficient yet well-formed runtime response generation in our Enterprise System emulation environment. We evaluate our approach using two common application-layer protocols: LDAP and SOAP. Our experimental results show that by utilising clustering techniques in the pre-processing step, the response generation time can be reduced by 99% on average compared with existing approaches