The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
임베디드 소프트웨어는 종속성이 복잡하거나 개발자에게 부분적으로 알려진 다양한 센서의 여러 입력과 상호 작용하는 경우가 많습니다. 종속성에 대한 정보가 불완전하면 테스트만으로는 오류를 감지하는 데 충분하지 않을 수 있습니다. 우리는 사용 로그에 포함된 정보를 사용하여 미묘하고 종종 무시되는 종속성을 식별함으로써 임베디드 소프트웨어의 테스트 범위를 향상시키는 방법을 제안합니다. 전통적으로 주로 사고 발생 후 조사 목적으로 사용되는 사용 로그는 임베디드 소프트웨어를 테스트하는 동안에도 유용한 기여를 할 수 있습니다. 우리의 접근 방식은 먼저 각 환경 입력에 대한 동작 모델을 개별적으로 개발하고, 사용 로그에서 실행 가능하지만 테스트되지 않은 종속성을 식별하는 동시에 구성 분석을 수행하고, 테스트되지 않았거나 충분히 테스트되지 않은 종속성에 해당하는 추가 테스트 케이스를 생성하는 것에 의존합니다. 실험 평가는 Gravity Screen이라는 Android 애플리케이션과 Arduino 기반 웨어러블 장갑 앱에서 수행되었습니다. 기존 CTM 기반 테스트 기법은 이들 애플리케이션에서 각각 26%와 68%의 평균 분기 커버리지를 달성한 반면, 제안된 기법은 두 애플리케이션 모두에서 100% 커버리지를 달성했습니다.
Sooyong JEONG
Kyungpook National University
Sungdeok CHA
Korea University
Woo Jin LEE
Kyungpook National University
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Sooyong JEONG, Sungdeok CHA, Woo Jin LEE, "Usage Log-Based Testing of Embedded Software and Identification of Dependencies among Environmental Components" in IEICE TRANSACTIONS on Information,
vol. E104-D, no. 11, pp. 2011-2014, November 2021, doi: 10.1587/transinf.2021EDL8042.
Abstract: Embedded software often interacts with multiple inputs from various sensors whose dependency is often complex or partially known to developers. With incomplete information on dependency, testing is likely to be insufficient in detecting errors. We propose a method to enhance testing coverage of embedded software by identifying subtle and often neglected dependencies using information contained in usage log. Usage log, traditionally used primarily for investigative purpose following accidents, can also make useful contribution during testing of embedded software. Our approach relies on first individually developing behavioral model for each environmental input, performing compositional analysis while identifying feasible but untested dependencies from usage log, and generating additional test cases that correspond to untested or insufficiently tested dependencies. Experimental evaluation was performed on an Android application named Gravity Screen as well as an Arduino-based wearable glove app. Whereas conventional CTM-based testing technique achieved average branch coverage of 26% and 68% on these applications, respectively, proposed technique achieved 100% coverage in both.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2021EDL8042/_p
부
@ARTICLE{e104-d_11_2011,
author={Sooyong JEONG, Sungdeok CHA, Woo Jin LEE, },
journal={IEICE TRANSACTIONS on Information},
title={Usage Log-Based Testing of Embedded Software and Identification of Dependencies among Environmental Components},
year={2021},
volume={E104-D},
number={11},
pages={2011-2014},
abstract={Embedded software often interacts with multiple inputs from various sensors whose dependency is often complex or partially known to developers. With incomplete information on dependency, testing is likely to be insufficient in detecting errors. We propose a method to enhance testing coverage of embedded software by identifying subtle and often neglected dependencies using information contained in usage log. Usage log, traditionally used primarily for investigative purpose following accidents, can also make useful contribution during testing of embedded software. Our approach relies on first individually developing behavioral model for each environmental input, performing compositional analysis while identifying feasible but untested dependencies from usage log, and generating additional test cases that correspond to untested or insufficiently tested dependencies. Experimental evaluation was performed on an Android application named Gravity Screen as well as an Arduino-based wearable glove app. Whereas conventional CTM-based testing technique achieved average branch coverage of 26% and 68% on these applications, respectively, proposed technique achieved 100% coverage in both.},
keywords={},
doi={10.1587/transinf.2021EDL8042},
ISSN={1745-1361},
month={November},}
부
TY - JOUR
TI - Usage Log-Based Testing of Embedded Software and Identification of Dependencies among Environmental Components
T2 - IEICE TRANSACTIONS on Information
SP - 2011
EP - 2014
AU - Sooyong JEONG
AU - Sungdeok CHA
AU - Woo Jin LEE
PY - 2021
DO - 10.1587/transinf.2021EDL8042
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E104-D
IS - 11
JA - IEICE TRANSACTIONS on Information
Y1 - November 2021
AB - Embedded software often interacts with multiple inputs from various sensors whose dependency is often complex or partially known to developers. With incomplete information on dependency, testing is likely to be insufficient in detecting errors. We propose a method to enhance testing coverage of embedded software by identifying subtle and often neglected dependencies using information contained in usage log. Usage log, traditionally used primarily for investigative purpose following accidents, can also make useful contribution during testing of embedded software. Our approach relies on first individually developing behavioral model for each environmental input, performing compositional analysis while identifying feasible but untested dependencies from usage log, and generating additional test cases that correspond to untested or insufficiently tested dependencies. Experimental evaluation was performed on an Android application named Gravity Screen as well as an Arduino-based wearable glove app. Whereas conventional CTM-based testing technique achieved average branch coverage of 26% and 68% on these applications, respectively, proposed technique achieved 100% coverage in both.
ER -