435 research outputs found
Porting the NetBeans Java 8 Enhanced For Loop Lambda Expression Refactoring to Eclipse
Java 8 is one of the largest upgrades to the popular language and framework in over a decade. However, the Eclipse IDE is missing several key refactorings that could help developers take advantage of new features in Java 8 more easily. In this paper, we discuss our ongoing work in porting the enhanced for loop to lambda expression refactoring from the NetBeans IDE to Eclipse. We also discuss future plans for new Java 8 refactorings not found in any current IDE
The Immitigable Nature of Assembly Bias: The Impact of Halo Definition on Assembly Bias
Dark matter halo clustering depends not only on halo mass, but also on other
properties such as concentration and shape. This phenomenon is known broadly as
assembly bias. We explore the dependence of assembly bias on halo definition,
parametrized by spherical overdensity parameter, . We summarize the
strength of concentration-, shape-, and spin-dependent halo clustering as a
function of halo mass and halo definition. Concentration-dependent clustering
depends strongly on mass at all . For conventional halo definitions
(), concentration-dependent clustering
at low mass is driven by a population of haloes that is altered through
interactions with neighbouring haloes. Concentration-dependent clustering can
be greatly reduced through a mass-dependent halo definition with for haloes with . Smaller implies larger radii and
mitigates assembly bias at low mass by subsuming altered, so-called backsplash
haloes into now larger host haloes. At higher masses () larger overdensities, , are necessary. Shape- and spin-dependent clustering are
significant for all halo definitions that we explore and exhibit a relatively
weaker mass dependence. Generally, both the strength and the sense of assembly
bias depend on halo definition, varying significantly even among common
definitions. We identify no halo definition that mitigates all manifestations
of assembly bias. A halo definition that mitigates assembly bias based on one
halo property (e.g., concentration) must be mass dependent. The halo
definitions that best mitigate concentration-dependent halo clustering do not
coincide with the expected average splashback radii at fixed halo mass.Comment: 19 pages, 13 figures. Updated to published version. Main result
summarized in Figure 1
FlashProfile: A Framework for Synthesizing Data Profiles
We address the problem of learning a syntactic profile for a collection of
strings, i.e. a set of regex-like patterns that succinctly describe the
syntactic variations in the strings. Real-world datasets, typically curated
from multiple sources, often contain data in various syntactic formats. Thus,
any data processing task is preceded by the critical step of data format
identification. However, manual inspection of data to identify the different
formats is infeasible in standard big-data scenarios.
Prior techniques are restricted to a small set of pre-defined patterns (e.g.
digits, letters, words, etc.), and provide no control over granularity of
profiles. We define syntactic profiling as a problem of clustering strings
based on syntactic similarity, followed by identifying patterns that succinctly
describe each cluster. We present a technique for synthesizing such profiles
over a given language of patterns, that also allows for interactive refinement
by requesting a desired number of clusters.
Using a state-of-the-art inductive synthesis framework, PROSE, we have
implemented our technique as FlashProfile. Across tasks over large
real datasets, we observe a median profiling time of only s.
Furthermore, we show that access to syntactic profiles may allow for more
accurate synthesis of programs, i.e. using fewer examples, in
programming-by-example (PBE) workflows such as FlashFill.Comment: 28 pages, SPLASH (OOPSLA) 201
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