6,910 research outputs found
Feedback Generation for Performance Problems in Introductory Programming Assignments
Providing feedback on programming assignments manually is a tedious, error
prone, and time-consuming task. In this paper, we motivate and address the
problem of generating feedback on performance aspects in introductory
programming assignments. We studied a large number of functionally correct
student solutions to introductory programming assignments and observed: (1)
There are different algorithmic strategies, with varying levels of efficiency,
for solving a given problem. These different strategies merit different
feedback. (2) The same algorithmic strategy can be implemented in countless
different ways, which are not relevant for reporting feedback on the student
program.
We propose a light-weight programming language extension that allows a
teacher to define an algorithmic strategy by specifying certain key values that
should occur during the execution of an implementation. We describe a dynamic
analysis based approach to test whether a student's program matches a teacher's
specification. Our experimental results illustrate the effectiveness of both
our specification language and our dynamic analysis. On one of our benchmarks
consisting of 2316 functionally correct implementations to 3 programming
problems, we identified 16 strategies that we were able to describe using our
specification language (in 95 minutes after inspecting 66, i.e., around 3%,
implementations). Our dynamic analysis correctly matched each implementation
with its corresponding specification, thereby automatically producing the
intended feedback.Comment: Tech report/extended version of FSE 2014 pape
Quantum algorithms for highly non-linear Boolean functions
Attempts to separate the power of classical and quantum models of computation
have a long history. The ultimate goal is to find exponential separations for
computational problems. However, such separations do not come a dime a dozen:
while there were some early successes in the form of hidden subgroup problems
for abelian groups--which generalize Shor's factoring algorithm perhaps most
faithfully--only for a handful of non-abelian groups efficient quantum
algorithms were found. Recently, problems have gotten increased attention that
seek to identify hidden sub-structures of other combinatorial and algebraic
objects besides groups. In this paper we provide new examples for exponential
separations by considering hidden shift problems that are defined for several
classes of highly non-linear Boolean functions. These so-called bent functions
arise in cryptography, where their property of having perfectly flat Fourier
spectra on the Boolean hypercube gives them resilience against certain types of
attack. We present new quantum algorithms that solve the hidden shift problems
for several well-known classes of bent functions in polynomial time and with a
constant number of queries, while the classical query complexity is shown to be
exponential. Our approach uses a technique that exploits the duality between
bent functions and their Fourier transforms.Comment: 15 pages, 1 figure, to appear in Proceedings of the 21st Annual
ACM-SIAM Symposium on Discrete Algorithms (SODA'10). This updated version of
the paper contains a new exponential separation between classical and quantum
query complexit
Renyi entropies as a measure of the complexity of counting problems
Counting problems such as determining how many bit strings satisfy a given
Boolean logic formula are notoriously hard. In many cases, even getting an
approximate count is difficult. Here we propose that entanglement, a common
concept in quantum information theory, may serve as a telltale of the
difficulty of counting exactly or approximately. We quantify entanglement by
using Renyi entropies S(q), which we define by bipartitioning the logic
variables of a generic satisfiability problem. We conjecture that
S(q\rightarrow 0) provides information about the difficulty of counting
solutions exactly, while S(q>0) indicates the possibility of doing an efficient
approximate counting. We test this conjecture by employing a matrix computing
scheme to numerically solve #2SAT problems for a large number of uniformly
distributed instances. We find that all Renyi entropies scale linearly with the
number of variables in the case of the #2SAT problem; this is consistent with
the fact that neither exact nor approximate efficient algorithms are known for
this problem. However, for the negated (disjunctive) form of the problem,
S(q\rightarrow 0) scales linearly while S(q>0) tends to zero when the number of
variables is large. These results are consistent with the existence of fully
polynomial-time randomized approximate algorithms for counting solutions of
disjunctive normal forms and suggests that efficient algorithms for the
conjunctive normal form may not exist.Comment: 13 pages, 4 figure
P?=NP as minimization of degree 4 polynomial, integration or Grassmann number problem, and new graph isomorphism problem approaches
While the P vs NP problem is mainly approached form the point of view of
discrete mathematics, this paper proposes reformulations into the field of
abstract algebra, geometry, fourier analysis and of continuous global
optimization - which advanced tools might bring new perspectives and approaches
for this question. The first one is equivalence of satisfaction of 3-SAT
problem with the question of reaching zero of a nonnegative degree 4
multivariate polynomial (sum of squares), what could be tested from the
perspective of algebra by using discriminant. It could be also approached as a
continuous global optimization problem inside , for example in
physical realizations like adiabatic quantum computers. However, the number of
local minima usually grows exponentially. Reducing to degree 2 polynomial plus
constraints of being in , we get geometric formulations as the
question if plane or sphere intersects with . There will be also
presented some non-standard perspectives for the Subset-Sum, like through
convergence of a series, or zeroing of fourier-type integral for some natural . The last discussed
approach is using anti-commuting Grassmann numbers , making nonzero only if has a Hamilton cycle. Hence,
the PNP assumption implies exponential growth of matrix representation of
Grassmann numbers. There will be also discussed a looking promising
algebraic/geometric approach to the graph isomorphism problem -- tested to
successfully distinguish strongly regular graphs with up to 29 vertices.Comment: 19 pages, 8 figure
Quantum Simulation Logic, Oracles, and the Quantum Advantage
Query complexity is a common tool for comparing quantum and classical
computation, and it has produced many examples of how quantum algorithms differ
from classical ones. Here we investigate in detail the role that oracles play
for the advantage of quantum algorithms. We do so by using a simulation
framework, Quantum Simulation Logic (QSL), to construct oracles and algorithms
that solve some problems with the same success probability and number of
queries as the quantum algorithms. The framework can be simulated using only
classical resources at a constant overhead as compared to the quantum resources
used in quantum computation. Our results clarify the assumptions made and the
conditions needed when using quantum oracles. Using the same assumptions on
oracles within the simulation framework we show that for some specific
algorithms, like the Deutsch-Jozsa and Simon's algorithms, there simply is no
advantage in terms of query complexity. This does not detract from the fact
that quantum query complexity provides examples of how a quantum computer can
be expected to behave, which in turn has proved useful for finding new quantum
algorithms outside of the oracle paradigm, where the most prominent example is
Shor's algorithm for integer factorization.Comment: 48 pages, 46 figure
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