Time-reversal symmetric resolution of unity without background integrals in open quantum systems

We present a new complete set of states for a class of open quantum systems, to be used in expansion of the Green's function and the time-evolution operator. A remarkable feature of the complete set is that it observes time-reversal symmetry in the sense that it contains decaying states (resonant states) and growing states (anti-resonant states) parallelly. We can thereby pinpoint the occurrence of the breaking of time-reversal symmetry at the choice of whether we solve Schroedinger equation as an initial-condition problem or a terminal-condition problem. Another feature of the complete set is that in the subspace of the central scattering area of the system, it consists of contributions of all states with point spectra but does not contain any background integrals. In computing the time evolution, we can clearly see contribution of which point spectrum produces which time dependence. In the whole infinite state space, the complete set does contain an integral but it is over unperturbed eigenstates of the environmental area of the system and hence can be calculated analytically. We demonstrate the usefulness of the complete set by computing explicitly the survival probability and the escaping probability as well as the dynamics of wave packets. The origin of each term of matrix elements is clear in our formulation, particularly the exponential decays due to the resonance poles.Comment: 62 pages, 13 figure

BCFA: Bespoke Control Flow Analysis for CFA at Scale

Many data-driven software engineering tasks such as discovering programming patterns, mining API specifications, etc., perform source code analysis over control flow graphs (CFGs) at scale. Analyzing millions of CFGs can be expensive and performance of the analysis heavily depends on the underlying CFG traversal strategy. State-of-the-art analysis frameworks use a fixed traversal strategy. We argue that a single traversal strategy does not fit all kinds of analyses and CFGs and propose bespoke control flow analysis (BCFA). Given a control flow analysis (CFA) and a large number of CFGs, BCFA selects the most efficient traversal strategy for each CFG. BCFA extracts a set of properties of the CFA by analyzing the code of the CFA and combines it with properties of the CFG, such as branching factor and cyclicity, for selecting the optimal traversal strategy. We have implemented BCFA in Boa, and evaluated BCFA using a set of representative static analyses that mainly involve traversing CFGs and two large datasets containing 287 thousand and 162 million CFGs. Our results show that BCFA can speedup the large scale analyses by 1%-28%. Further, BCFA has low overheads; less than 0.2%, and low misprediction rate; less than 0.01%.Comment: 12 page

Prepose: privacy, security, and reliability for gesture-based programming

With the rise of sensors such as Microsoft Kinect, gesture-based interfaces have become practical. However, to recognize such gestures, applications need access to users' depth and video, exposing sensitive data about individuals and their environment. Prepose, a domain-specific language for building gesture recognizers, combined with a system architecture that protects privacy, security, and reliability with untrusted applications, addresses these threats

Program boosting: program synthesis via crowd-sourcing

In this paper, we investigate an approach to program synthesis that is based on crowd-sourcing. With the help of crowd-sourcing, we aim to capture the "wisdom of the crowds" to find good if not perfect solutions to inherently tricky programming tasks, which elude even expert developers and lack an easy-to-formalize specification. We propose an approach we call program boosting, which involves crowd-sourcing imperfect solutions to a difficult programming problem from developers and then blending these programs together in a way that improves their correctness. We implement this approach in a system called CROWDBOOST and show in our experiments that interesting and highly non-trivial tasks such as writing regular expressions for URLs or email addresses can be effectively crowd-sourced. We demonstrate that carefully blending the crowd-sourced results together consistently produces a boost, yielding results that are better than any of the starting programs. Our experiments on 465 program pairs show consistent boosts in accuracy and demonstrate that program boosting can be performed at a relatively modest monetary cost