809 research outputs found
International conference on software engineering and knowledge engineering: Session chair
The Thirtieth International Conference on Software Engineering and Knowledge Engineering (SEKE 2018) will be held at the Hotel Pullman, San Francisco Bay, USA, from July 1 to July 3, 2018. SEKE2018 will also be dedicated in memory of Professor Lofti Zadeh, a great scholar, pioneer and leader in fuzzy sets theory and soft computing.
The conference aims at bringing together experts in software engineering and knowledge engineering to discuss on relevant results in either software engineering or knowledge engineering or both. Special emphasis will be put on the transference of methods between both domains. The theme this year is soft computing in software engineering & knowledge engineering. Submission of papers and demos are both welcome
Are Multi-language Design Smells Fault-prone? An Empirical Study
Nowadays, modern applications are developed using components written in
different programming languages. These systems introduce several advantages.
However, as the number of languages increases, so does the challenges related
to the development and maintenance of these systems. In such situations,
developers may introduce design smells (i.e., anti-patterns and code smells)
which are symptoms of poor design and implementation choices. Design smells are
defined as poor design and coding choices that can negatively impact the
quality of a software program despite satisfying functional requirements.
Studies on mono-language systems suggest that the presence of design smells
affects code comprehension, thus making systems harder to maintain. However,
these studies target only mono-language systems and do not consider the
interaction between different programming languages. In this paper, we present
an approach to detect multi-language design smells in the context of JNI
systems. We then investigate the prevalence of those design smells.
Specifically, we detect 15 design smells in 98 releases of nine open-source JNI
projects. Our results show that the design smells are prevalent in the selected
projects and persist throughout the releases of the systems. We observe that in
the analyzed systems, 33.95% of the files involving communications between Java
and C/C++ contains occurrences of multi-language design smells. Some kinds of
smells are more prevalent than others, e.g., Unused Parameters, Too Much
Scattering, Unused Method Declaration. Our results suggest that files with
multi-language design smells can often be more associated with bugs than files
without these smells, and that specific smells are more correlated to
fault-proneness than others
E-Debitum: managing software energy debt
35th IEEE/ACM International Conference on Automated Software Engineering Workshops (ASEW ’20) - International Workshop on Sustainable Software Engineering (SUSTAIN-SE)This paper extends previous work on the concept of a new software energy metric: Energy Debt. This metric is a reflection on the implied cost, in terms of energy consumption over time, of choosing an energy flawed software implementation over a more robust and efficient, yet time consuming, approach.
This paper presents the implementation a SonarQube tool called E-Debitum which calculates the energy debt of Android applications throughout their versions. This plugin uses a robust, well defined, and extendable smell catalogue based on current green software literature, with each smell defining the potential energy savings. To conclude, an experimental validation of E-Debitum was executed on 3 popular Android applications with various releases, showing how their energy debt fluctuated throughout releases.This work is financed by National Funds through the Portuguese
funding agency, FCT -Fundação para a Ciência e a Tecnologia within
project UIDB/50014/2020
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