Turning carbon offset credits into crypto tokens is the latest trend in attempted techno-fixes for climate change. One high-profile effort is backed by Adam Neumann, but experts are skeptical.
Computing systems are becoming increasingly complex and sophisticated. Technologies such as artificial intelligence, big data, and autonomous vehicles are pushing the boundaries of system size, complexity, and comprehensibility beyond anything seen before. These advances, however, have left the associated software quality assurance (SQA) tools and processes behind. This is compounded by many training and education programs also not attempting to address this inadequacy in the preparation of future software engineering professionals. We face a situation of extensively-deployed advanced computing systems, many of which lack sufficient SQA support. Metamorphic Testing (MT) and Metamorphic Exploration (ME) are SQA approaches that have a record of being able to alleviate some of the challenges associated with the advanced computer systems. This paper reports on an MT/ME experience with the Baidu Apollo autonomous driving system (ADS). The experience included identifying an apparent problem
Advanced Driver-Assistance Systems (ADASs) have become increasingly popular. To ensure safety, simulation testing is essential. In this research, we conducted a case study to investigate the fault-detection effectiveness of existing ADAS testing standards: We tested the Lane Keeping Assist System (LKAS), which is a prebuilt ADAS module of MATLAB and Simulink. We first tested LKAS using the European New Car Assessment Programme (Euro NCAP), which contains 40 prebuilt driving scenarios in MATLAB. Our results show that none of the 40 scenarios detected any failure. We then continued the tests by applying a simple metamorphic relation equivalence under geometric transformation, and a previously unknown real-life bug in LKAS was immediately revealed. We reported this finding to the MATLAB team in the US, who then confirmed the bug and corrected the LKAS code. This research provides a strong case for incorporating metamorphic testing into ADAS testing standards and protocols.
Information is indispensable in modern society. People’s daily communication and work depend on information transmission. Unsafe storage or transmission of data may result in privacy and security problems. One way to attempt to prevent such issues is to use encryption algorithms to transform information into encrypted forms. Because the encryption steps of most encryption algorithms are complex, deciding the correctness of the encrypted output may take a long time in practice. This kind of problem is called the Test Oracle problem. In contrast to traditional software testing, Metamorphic Testing (MT) does not focus on the correctness of each individual output, but examines whether the inputs and outputs of multiple executions of a Program Under Test (PUT) satisfy necessary relations of the PUT, called metamorphic relations. This paper reports on an experience of applying MT to test three encryption algorithms Data Encryption Standard (DES), Triple Data Encryption Standard (3DES), a
This paper presents an automated, domain-independent, metamorphic testing platform called MTKeras. In this paper, we report on an investigation demonstrating the effectiveness and usability of MTKeras through five case studies in the four domains of image classification, sentiment analysis, search engines and database management systems. We also report on the effectiveness of combining metamorphic relation (input) patterns in individual metamorphic relations, enhancing the failure-finding abilities of the individual relations. The results of our experiments support combining patterns, and the use of MTKeras. The research reported in this paper shows the applicability of metamorphic relation patterns, and introduces a practical tool for the research community.