18,742 research outputs found
Moving forward with combinatorial interaction testing
Combinatorial interaction testing (CIT) is an efficient and effective method of detecting failures that are caused by the interactions of various system input parameters. In this paper, we discuss CIT, point out some of the difficulties of applying it in practice, and highlight some recent advances that have improved CIT’s applicability to modern systems. We also provide a roadmap for future research and directions; one that we hope will lead to new CIT research and to higher quality testing of industrial systems
Report from GI-Dagstuhl Seminar 16394: Software Performance Engineering in the DevOps World
This report documents the program and the outcomes of GI-Dagstuhl Seminar
16394 "Software Performance Engineering in the DevOps World".
The seminar addressed the problem of performance-aware DevOps. Both, DevOps
and performance engineering have been growing trends over the past one to two
years, in no small part due to the rise in importance of identifying
performance anomalies in the operations (Ops) of cloud and big data systems and
feeding these back to the development (Dev). However, so far, the research
community has treated software engineering, performance engineering, and cloud
computing mostly as individual research areas. We aimed to identify
cross-community collaboration, and to set the path for long-lasting
collaborations towards performance-aware DevOps.
The main goal of the seminar was to bring together young researchers (PhD
students in a later stage of their PhD, as well as PostDocs or Junior
Professors) in the areas of (i) software engineering, (ii) performance
engineering, and (iii) cloud computing and big data to present their current
research projects, to exchange experience and expertise, to discuss research
challenges, and to develop ideas for future collaborations
The Progress, Challenges, and Perspectives of Directed Greybox Fuzzing
Most greybox fuzzing tools are coverage-guided as code coverage is strongly
correlated with bug coverage. However, since most covered codes may not contain
bugs, blindly extending code coverage is less efficient, especially for corner
cases. Unlike coverage-guided greybox fuzzers who extend code coverage in an
undirected manner, a directed greybox fuzzer spends most of its time allocation
on reaching specific targets (e.g., the bug-prone zone) without wasting
resources stressing unrelated parts. Thus, directed greybox fuzzing (DGF) is
particularly suitable for scenarios such as patch testing, bug reproduction,
and specialist bug hunting. This paper studies DGF from a broader view, which
takes into account not only the location-directed type that targets specific
code parts, but also the behaviour-directed type that aims to expose abnormal
program behaviours. Herein, the first in-depth study of DGF is made based on
the investigation of 32 state-of-the-art fuzzers (78% were published after
2019) that are closely related to DGF. A thorough assessment of the collected
tools is conducted so as to systemise recent progress in this field. Finally,
it summarises the challenges and provides perspectives for future research.Comment: 16 pages, 4 figure
Semantic Modeling of Analytic-based Relationships with Direct Qualification
Successfully modeling state and analytics-based semantic relationships of
documents enhances representation, importance, relevancy, provenience, and
priority of the document. These attributes are the core elements that form the
machine-based knowledge representation for documents. However, modeling
document relationships that can change over time can be inelegant, limited,
complex or overly burdensome for semantic technologies. In this paper, we
present Direct Qualification (DQ), an approach for modeling any semantically
referenced document, concept, or named graph with results from associated
applied analytics. The proposed approach supplements the traditional
subject-object relationships by providing a third leg to the relationship; the
qualification of how and why the relationship exists. To illustrate, we show a
prototype of an event-based system with a realistic use case for applying DQ to
relevancy analytics of PageRank and Hyperlink-Induced Topic Search (HITS).Comment: Proceedings of the 2015 IEEE 9th International Conference on Semantic
Computing (IEEE ICSC 2015
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