A general software defect-proneness prediction framework

This is the author's accepted manuscript. The final published article is available from the link below. Copyright @ 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.BACKGROUND - Predicting defect-prone software components is an economically important activity and so has received a good deal of attention. However, making sense of the many, and sometimes seemingly inconsistent, results is difficult. OBJECTIVE - We propose and evaluate a general framework for software defect prediction that supports 1) unbiased and 2) comprehensive comparison between competing prediction systems. METHOD - The framework is comprised of 1) scheme evaluation and 2) defect prediction components. The scheme evaluation analyzes the prediction performance of competing learning schemes for given historical data sets. The defect predictor builds models according to the evaluated learning scheme and predicts software defects with new data according to the constructed model. In order to demonstrate the performance of the proposed framework, we use both simulation and publicly available software defect data sets. RESULTS - The results show that we should choose different learning schemes for different data sets (i.e., no scheme dominates), that small details in conducting how evaluations are conducted can completely reverse findings, and last, that our proposed framework is more effective and less prone to bias than previous approaches. CONCLUSIONS - Failure to properly or fully evaluate a learning scheme can be misleading; however, these problems may be overcome by our proposed framework.National Natural Science Foundation of Chin

Interplay of defect cluster and the stability of xenon in uranium dioxide by density functional calculations

Self-defect clusters in bulk matrix might affect the thermodynamic behavior of fission gases in nuclear fuel such as uranium dioxide. With first-principles LSDA+U calculations and taking xenon as a prototype, we find that the influence of oxygen defect clusters on the thermodynamics of gas atoms is prominent, which increases the solution energy of xenon by a magnitude of 0.5 eV, about 43% of the energy difference between the two lowest lying states at 700 K. Calculation also reveals a thermodynamic competition between the uranium vacancy and tri-vacancy sites to incorporate xenon in hyper-stoichiometric regime at high temperatures. The results show that in hypo-stoichiometric regime neutral tri-vacancy sites are the most favored position for diluted xenon gas, whereas in hyper-stoichiometric condition they prefer to uranium vacancies even after taking oxygen self-defect clusters into account at low temperatures, which not only confirms previous studies but also extends the conclusion to more realistic fuel operating conditions. The observation that gas atoms are ionized to a charge state of Xe+ when at a uranium vacancy site due to strong Madelung potential implies that one can control temperature to tune the preferred site of gas atoms and then the bubble growth rate. A solution to the notorious meta-stable states difficulty that frequently encountered in DFT+U applications, namely, the quasi-annealing procedure, is also discussed.Comment: 22 pages, 7 figures, accepted by Phys. Rev. B for publicatio

Computation of the p6p^6 order low-energy constants with tensor sources

We present the results of calculations of the $p^4$ and $p^6$ order low-energy constants for the chiral Lagrangian with tensor sources for both two and three flavors of pseudoscalar mesons. This is a generalization of our previous work on similar calculations without tensor sources in terms of the quark self-energy $\Sigma(p^2)$, based on the first principle derivation of the low-energy effective Lagrangian and computation of the low-energy constants with some rough approximations. With the help of partial integration and some epsilon relations, we find that some $p^6$ order operators with tensor sources appearing in the literature are related to each other. That leaves 98 independent terms for $n$-flavor, 92 terms for three-flavor, and 65 terms for two-flavor cases. We also find that the odd-intrinsic-parity chiral Lagrangian with tensor sources cannot independently exist in any order of low-energy expansion.Comment: 29 page

Absolute continuity of symmetric Markov processes

We study Girsanov's theorem in the context of symmetric Markov processes, extending earlier work of Fukushima-Takeda and Fitzsimmons on Girsanov transformations of ``gradient type.'' We investigate the most general Girsanov transformation leading to another symmetric Markov process. This investigation requires an extension of the forward-backward martingale method of Lyons-Zheng, to cover the case of processes with jumps.Comment: Published by the Institute of Mathematical Statistics (http://www.imstat.org) in the Annals of Probability (http://www.imstat.org/aop/) at http://dx.doi.org/10.1214/00911790400000043

Comparative analysis of the applicability of BIM query languages for energy analysis

Paper no. 036A range of query languages have been used or developed to query partial information from Building Information Model (BIM)-based databases and files in recent decades. This paper aims to investigate the applicability of existing BIM query languages to extract necessary information from BIMs for energy analysis. A total of 16 query languages categorized into two groups, namely programming or generic query language, and domain specific query language, are summarized through extensive literature review. The key requirements of BIM data query for energy analysis are also developed, which include MVD based query support, custom query support, and easiness to construct queries. Taking these requirements as the criteria, the applicability of the 16 query languages is compared and analyzed. This paper then proposes some suggestions for developing effective and efficient building information query mechanisms for energy analysis.postprin

Ground-state phase diagram of the quantum Rabi model

The Rabi model plays a fundamental role in understanding light-matter interaction. It reduces to the Jaynes-Cummings model via the rotating-wave approximation, which is applicable only to the cases of near resonance and weak coupling. However, recent experimental breakthroughs in upgrading light-matter coupling order require understanding the physics of the full quantum Rabi model (QRM). Despite the fact that its integrability and energy spectra have been exactly obtained, the challenge to formulate an exact wavefunction in a general case still hinders physical exploration of the QRM. Here we unveil a ground-state phase diagram of the QRM, consisting of a quadpolaron and a bipolaron as well as their changeover in the weak-, strong- and intermediate-coupling regimes, respectively. An unexpected overweighted antipolaron is revealed in the quadpolaron state, and a hidden scaling behavior relevant to symmetry breaking is found in the bipolaron state. An experimentally accessible parameter is proposed to test these states, which might provide novel insights into the nature of the light-matter interaction for all regimes of the coupling strengths.Comment: 14 pages, 13 figures, Physical Review A, in pres