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Fairness Testing: Testing Software for Discrimination [PDF]

Proceedings of the 2017 11th Joint Meeting on Foundations of Software Engineering, 2017
This paper defines software fairness and discrimination and develops a testing-based method for measuring if and how much software discriminates, focusing on causality in discriminatory behavior.
Angwin Julia, Brun Yuriy, Ferral Katelyn, Gonzalez Jesus A., Guglielmo Luigi Di, Ingold David, Letzter Rafi, Mattioli Dana, Meliou Alexandra, Meliou Alexandra, Nadella Satya, Olson Parmy, Shahani Aarti, Soper Spencer, Soper Spencer, von Rhein Alexander, Zafar Muhammad Bilal, Zemel Richard   +17 more
core   +2 more sources

Field Testing of Software Applications [PDF]

2017 IEEE/ACM 39th International Conference on Software Engineering Companion (ICSE-C), 2017
When interacting with their software systems, users may have to deal with problems like crashes, failures, and program instability. Faulty software running in the field is not only the consequence of ineffective in-house verification and validation ...
Gazzola, Luca
core   +4 more sources

Testing ocean software with metamorphic testing

Proceedings of the 7th International Workshop on Metamorphic Testing, 2022
7 pages, 3 ...
Quang-Hung Luu, Huai Liu, Tsong Yueh Chen, Hai L. Vu   +3 more
openaire   +2 more sources

Vigour testing for the rice seed with computer vision-based techniques

Frontiers in Plant Science, 2023
Rice is the staple food for approximately half of the world’s population. Seed vigour has a crucial impact on the yield, which can be evaluated by germination rate, vigor index and etc.
Juxiang Qiao, Yun Liao, Changsheng Yin, Xiaohong Yang, Hoàng Minh Tú, Wei Wang, Yanfang Liu   +6 more
doaj   +1 more source

A Deep Learning Approach for State-of-Health Estimation of Lithium-Ion Batteries Based on a Multi-Feature and Attention Mechanism Collaboration

Batteries, 2023
Safety issues are one of the main limitations for further application of lithium-ion batteries, and battery degradation is an important causative factor.
Bosong Zou, Mengyu Xiong, Huijie Wang, Wenlong Ding, Pengchang Jiang, Wei Hua, Yong Zhang, Lisheng Zhang, Wentao Wang, Rui Tan   +9 more
doaj   +1 more source

An Introduction to Software Testing

Electronic Notes in Theoretical Computer Science, 2006
AbstractThe development of large software systems is a complex and error prone process. Faults might occur at any development stage and they must be identified and removed as early as possible to stop their propagation and reduce verification costs. Quality engineers must be involved in the development process since the very early phases to identify ...
Luciano Baresi, Mauro Pezzè
openaire   +4 more sources

Enhanced Location K-anonymity Privacy Protection Scheme Based on Geohash [PDF]

Jisuanji kexue
With the wide application of LBS,location privacy protection is imperative.In recent years,location k-anonymity solution has become a research hotpot which is widely used.However,k-anonymity schemes are vulnerable to background knowledge attacks.Although
LI Yongjun, ZHU Yuefei, BAI Lifang
doaj   +1 more source

Graph-Based Node Finding in Big Complex Contextual Social Graphs

Complexity, 2020
Graph pattern matching is to find the subgraphs matching the given pattern graphs. In complex contextual social networks, considering the constraints of social contexts like the social relationships, the social trust, and the social positions, users are ...
Keshou Wu, Guanfeng Liu, Junwen Lu
doaj   +1 more source

Multi-factor Dummy Location Selection Algorithm in Location-based Service [PDF]

Jisuanji kexue
In view of the existing dummy location selection methods in LBS snapshot location privacy protection,the background knowledge attack caused by the time factor of the location itself is ignored,and the sensitive locations are treated equally.Based on this,
LI Yongjun, ZHU Yuefei, WU Wei, BAI Lifang
doaj   +1 more source

Learning-Based Testing Using SAL (Symbolic Analysis Laboratory) Model Checker

NUML International Journal of Engineering and Computing, 2023
This paper studies learning-based testing (LBT) for reactive systems with different learning algorithms and model checkers. LBT is a technique that requires a learning algorithm to learn the models to generate test cases automatically.
Anjum Ara Shah, Muddassar Azam Sindhu
doaj   +1 more source