Mutation Analysis for Cyber-Physical Systems: Scalable Solutions and Results in the Space Domain

被引:8
作者
Cornejo, Oscar [1 ]
Pastore, Fabrizio [1 ]
Briand, Lionel C. [1 ,2 ]
机构
[1] Univ Luxembourg, SnT Ctr Secur Reliabil & Trust, L-4365 Esch Sur Alzette, Luxembourg
[2] Univ Ottawa, Chool EECS, Ottawa, ON K1N 6N5, Canada
基金
加拿大自然科学与工程研究理事会; 欧洲研究理事会;
关键词
Software; Embedded software; Optimization; Libraries; Scalability; Pipelines; Hardware; Mutation analysis; mutation testing; space software; embedded software; cyber-physical systems; CONFIDENCE-INTERVALS; SAMPLE-SIZE; BINOMIAL PROPORTION;
D O I
10.1109/TSE.2021.3107680
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
On-board embedded software developed for spaceflight systems (space software) must adhere to stringent software quality assurance procedures. For example, verification and validation activities are typically performed and assessed by third party organizations. To further minimize the risk of human mistakes, space agencies, such as the European Space Agency (ESA), are looking for automated solutions for the assessment of software testing activities, which play a crucial role in this context. Though space software is our focus here, it should be noted that such software shares the above considerations, to a large extent, with embedded software in many other types of cyber-physical systems. Over the years, mutation analysis has shown to be a promising solution for the automated assessment of test suites; it consists of measuring the quality of a test suite in terms of the percentage of injected faults leading to a test failure. A number of optimization techniques, addressing scalability and accuracy problems, have been proposed to facilitate the industrial adoption of mutation analysis. However, to date, two major problems prevent space agencies from enforcing mutation analysis in space software development. First, there is uncertainty regarding the feasibility of applying mutation analysis optimization techniques in their context. Second, most of the existing techniques either can break the real-time requirements common in embedded software or cannot be applied when the software is tested in Software Validation Facilities, including CPU emulators and sensor simulators. In this paper, we enhance mutation analysis optimization techniques to enable their applicability to embedded software and propose a pipeline that successfully integrates them to address scalability and accuracy issues in this context, as described above. Further, we report on the largest study involving embedded software systems in the mutation analysis literature. Our research is part of a research project funded by ESA ESTEC involving private companies (GomSpace Luxembourg and LuxSpace) in the space sector. These industry partners provided the case studies reported in this paper; they include an on-board software system managing a microsatellite currently on-orbit, a set of libraries used in deployed cubesats, and a mathematical library certified by ESA.
引用
收藏
页码:3913 / 3939
页数:27
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