Fujitsu and SMBC Conduct Joint Field Trial of AI Technology to Automatically Recommend Software Repairs
Reduces the time required to repair latent software bugs by up to 30%, shortening development and maintenance work.
TOKYO, Oct 24, 2019 - (JCN Newswire) - Sumitomo Mitsui Financial Group (SMFG), The Japan Research Institute, Limited (JRI), and Fujitsu Limited today announced that they have conducted a joint field trial to determine the effectiveness of an AI technology that automatically recommends software repairs(1).
| Summary of the technology to automatically recommend software repairs |
This technology leverages AI to automatically generate recommended repairs for latent bugs in software detected by static analysis tools(2), offering insights to the software's developers. In the trial, the technology was applied to software for the system that handles financial transactions for Sumitomo Mitsui Banking Corporation (SMBC), developed by JRI. The evaluation results showed that the technology could recommend appropriate repairs for over half of the latent bugs detected. Using these proposed repairs, it would have been possible to reduce the time required to repair the latent bugs by up to 30% compared with performing the task manually. Therefore, it is anticipated that the technology will contribute to significant reductions in software development and maintenance time.
Background
In the finance industry, providing service innovation using digital transformation and fintech, has become indispensable to improving competitiveness. While demand exists for financial institutions to provide their customers with the latest digital services as fast as possible, financial services require a particularly high degree of trustworthiness, so development methods for improving software quality in a short time frame have become a pressing issue. In light of these circumstances, Fujitsu Laboratories of America, Inc., and SMFG Silicon Valley Digital Innovation Laboratory collaborated to conduct a joint field trial to evaluate the effectiveness of this technology when applied to SMBC's financial transaction processing system. The technology was initially developed by Fujitsu Laboratories of America and Fujitsu Laboratories Ltd.
About the Technology
Given a set of latent bugs in software, identified by static analysis tools, this technology synthesizes repairs based on a set of repair strategies and recommends them to developers. The repair strategies are learned from repair examples of previous latent bugs using AI. Latent bugs may cause a wide variety of software problems, including performance degradation, incorrect behavior, and poor maintainability. In order to repair latent bugs, software developers must begin by analyzing how to repair each one individually, so the process requires significant amounts of time. With this technology, an AI model is trained on examples of repairing latent bugs extracted from the development history of a wide variety of software projects, deriving repair strategies for different bug types. When applied to latent bugs in software under development, this technology uses these learned repair strategies to automatically synthesize and recommend repairs for the bugs, to the developer. It is expected that the use of this technology could shorten software development and maintenance times compared to having developers repair each identified latent bug manually. Summary of the Field Trial
1. Time Period
August 1 - September 30, 2019
2. Details
In this field trial, this technology was applied to SMBC's financial transaction processing system, developed by JRI. In the trial, the number of latent bugs in the selected software was tabulated using a static analysis tool, as well as the number of valid repair recommendations synthesized by this technology, verified through a manual examination of each recommended repair. The results show that this technology was able to generate repair recommendations for 52.7% of the latent bugs in the selected software and that, of those repair recommendations, 95.3% were valid. This means that this technology was able to recommend valid repairs for 50.2% of all latent bugs. Further, we estimated that the time required to fix these latent bugs could be reduced by up to 30%, compared with having developers manually repair each bug individually.
Future Developments
SMFG and JRI are considering a full-scale deployment of this technology in order to improve the quality and efficiency of software development. In addition, Fujitsu aims to use the results of this field trial to further enhance the analytical capacity of the technology and improve the accuracy of the proposed solutions, while also aiming to make this technology available as a development support service during fiscal 2020.
Notes: (1) Technology to automatically recommend software repairs using AI -- Presented by Fujitsu Laboratories of America, Inc. at the 27th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE 2019), an international conference held in Tallinn, Estonia, on August 26-30, 2019. (2) Static analysis tools -- Tools for detecting latent software problems solely by analyzing the software's source code, without executing the software.
Contact:Fujitsu Limited
Public and Investor Relations
Tel: +81-3-3215-5259
URL: www.fujitsu.com/global/news/contacts/
Source: Fujitsu Ltd Sectors: Artificial Intel [AI]
Copyright ©2024 JCN Newswire. All rights reserved. A division of Japan Corporate News Network.
|
Latest Release
First-ever Mazda CX-80 Crossover SUV Unveiled in Europe Apr 19, 2024 13:50 JST
| Fujitsu develops technology to convert corporate digital identity credentials, enabling participation of non-European companies in European data spaces Apr 19, 2024 10:17 JST
| Mitsubishi Heavy Industries and NGK to Jointly Develop Hydrogen Purification System from Ammonia Cracking Gas Apr 18, 2024 17:01 JST
| Toyota Launches All-New Land Cruiser "250" Series in Japan Apr 18, 2024 13:39 JST
| Fujitsu and Oracle collaborate to deliver sovereign cloud and AI capabilities in Japan Apr 18, 2024 11:14 JST
| Eisai: Research on Treatments for Alzheimer's Disease Based on Its Pathological Mechanisms Recieves Award for Science and Technology (Research Category) Apr 18, 2024 10:53 JST
| All-New Triton Confirmed as First Double-Cab Pickup Truck to Achieve 2024 Five-Star ANCAP Safety Rating Apr 18, 2024 09:22 JST
| Eisai's Antiepileptic Drug Fycompa Injection Formulation Launched In Japan Apr 17, 2024 16:17 JST
| Honda Unveils Next-generation EV Series for China Apr 17, 2024 12:15 JST
| Lexus presents Time at the 2024 Milan Design Week Apr 16, 2024 18:49 JST
| Mitsubishi Corporation Announces Participation in a DAC Project in Louisiana, USA Apr 16, 2024 14:36 JST
| New circuit challenge for TOYOTA GAZOO Racing Apr 15, 2024 17:21 JST
| TOYOTA GAZOO Racing back on asphalt for Croatian challenge Apr 12, 2024 19:36 JST
| Heidelberg Materials North America Announces Latest Milestone in Edmonton CCUS Project Apr 12, 2024 14:39 JST
| MHIAEL Completes Expansion of the its Nagasaki Plant for Manufacture of Aero Engine Combustors Apr 11, 2024 18:08 JST
| Mitsubishi Shipbuilding Acquires Approval in Principle (AiP) from Classification Society ClassNK for Ammonia Fuel Supply System (AFSS) Apr 11, 2024 17:50 JST
| DOCOMO, NTT, NEC and Fujitsu Develop Top-level Sub-terahertz 6G Device Capable of Ultra-high-speed 100 Gbps Transmission Apr 11, 2024 15:10 JST
| Mitsubishi Corporation Announces Completion of Capital Raise by Nexamp Apr 11, 2024 13:07 JST
| Mitsubishi Shipbuilding Receives Order for Ammonia Fuel Supply System for Ammonia-Powered Marine Engine Apr 10, 2024 16:55 JST
| Transgene and NEC Present First Clinical Benefits of Neoantigen Cancer Vaccine, TG4050, in Head & Neck Cancer at AACR 2024 Apr 10, 2024 13:36 JST
|
More Latest Release >>
|