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Università della Svizzera italiana

MeMo : automatically identifying metamorphic relations in Javadoc comments for test automation

Blasi, Arianna ; Gorla, Alessandra ; Ernst, Michael D. ; Pezzè, Mauro ; Carzaniga, Antonio

In: Journal of systems and software, 2021, vol. 181, p. 13

Software testing depends on effective oracles. Implicit oracles, such as checks for program crashes, are widely applicable but narrow in scope. Oracles based on formal specifications can reveal applicationspecific failures, but specifications are expensive to obtain and maintain. Metamorphic oracles are somewhere in-between. They test equivalence among different procedures to detect semantic...

Università della Svizzera italiana

Mining code change patterns to aid software development

Fengcai, Wen ; Bavota, Gabriele (Dir.) ; Lanza, Michele (Codir.)

Thèse de doctorat : Università della Svizzera italiana, 2021 ; 2021INFO012.

Mining Software Repositories (MSR) has become a complete and mature research field, also due to the increasing number of open source projects publicly available. Repository hosting services such as GitHub provide unprecedented access to millions of events generated during development activities (e.g., code commits, pull requests), that can be mined and analyzed to extract new pieces of...

Consortium of Swiss Academic Libraries

Long-term Relationships: Static Gains and Dynamic Inefficiencies

Hémous, David ; Olsen, Morten

In: Journal of the European Economic Association, 2018, vol. 16, no. 2, p. 383-435

Consortium of Swiss Academic Libraries

An introduction to the problem of bridging quantum and classical dynamics

Bonella, S. ; Ciccotti, G.

In: The European Physical Journal Special Topics, 2015, vol. 224, no. 12, p. 2305-2320

Université de Fribourg

Mind the Gap : An Experimental Evaluation of Imputation of Missing Values Techniques in Time Series

Khayati, Mourad ; Lerner, Alberto ; Tymchenko, Zakhar ; Cudré-Mauroux, Philippe

In: Proceedings of the VLDB Endowment, 2020, vol. 13, no. 5, p. 768-782

Recording sensor data is seldom a perfect process. Failures in power, communication or storage can leave occasional blocks of data missing, affecting not only real-time monitoring but also compromising the quality of near- and off-line data analysis. Several recovery (imputation) algorithms have been proposed to replace missing blocks. Unfortunately, little is known about their relative...