Understanding and Generating Patches for Bugs Introduced by Third-party Library Upgrades

During the process of software development, developers rely heavily on third-party libraries to enable functionalities and features in their projects. However, developers are faced with challenges of managing dependency messes when a project evolves. One of the most challenging problems is to handle issues caused by dependency upgrades. To better understand the issues caused by Third-party Library Upgrades (TLU), in this thesis, we conduct a comprehensive study of the bugs caused by dependency upgrades. The study is conducted on a collection of 8,952 open-source Java projects from GitHub and 304 Java projects on Apache Software Foundation (ASF) JIRA systems. We collect 83 bugs caused by inappropriate TLUs in total. Our inspection shows that TLUs are conducted out of different reasons. The most popular reason is that the project is preparing for release and wants to keep its dependencies up-to-date (62.3%). Another popular reason is that the older version of a dependency is not compatible with other dependencies (15.3%). Our inspection also indicates that the problems introduced by inappropriate dependency upgrades can be categorized into different types, i.e., program failures that are detectable statically and dynamically. Then, we investigate developers’ efforts on repairing bugs caused by inappropriate TLUs. We notice that 32.53% of these bugs can be fixed by only modifying the build scripts (which we call TLU-build bugs), 20.48% of them can be fixed by merely modifying the source code (which is called TLU-code bugs), and 16.87% of them require modifications in multiple sources. TLU-build bugs and TLU-code bugs as the two most popular types, are explored more by us. For TLU-code bugs, we summarize the common ways used to fix them. Furthermore, we study whether current repair techniques can fix TLU-code bugs efficiently. For the 14 TLU-code bugs that cause test failures and runtime failures, the study shows that existing automated program repair tools can only work on 6 of the 14 investigated bugs. Each of them can only fix a limited amount of the 6 bugs, but the union of them can finally fix 5 out of 6 bugs. For TLU-build bugs, by leveraging the knowledge from our study, we summarize common patterns to fix build scripts, and propose a technique to automatically fix them. Our evaluation shows the proposed technique can successfully fix 9 out of 14 TLU-build bugs

Time-Independent Reliability Analysis of Bridge System Based on Mixed Copula Models

The actual structural systems have many failure modes. Due to the same random sources owned by the performance functions of these failure modes, there usually exist some nonlinear correlations between the various failure modes. How to handle the nonlinear correlations is one of the main scientific problems in the field of structural system reliability. In this paper, for the two-component systems and multiple-component systems with multiple failure modes, the mixed copula models for time-independent reliability analysis of series systems, parallel systems, series-parallel systems, and parallel-series systems are presented. These obtained mixed copula models, considering the nonlinear correlation between failure modes, are obtained with the chosen optimal copula functions with the Bayesian selection criteria and Monte Carlo Sampling (MCS) method. And a numerical example is provided to illustrate the feasibility and application of the built mixed models for structural system reliability

Determining the local dark matter density with LAMOST data

Measurement of the local dark matter density plays an important role in both Galactic dynamics and dark matter direct detection experiments. However, the estimated values from previous works are far from agreeing with each other. In this work, we provide a well-defined observed sample with 1427 G \& K type main-sequence stars from the LAMOST spectroscopic survey, taking into account selection effects, volume completeness, and the stellar populations. We apply a vertical Jeans equation method containing a single exponential stellar disk, a razor thin gas disk, and a constant dark matter density distribution to the sample, and obtain a total surface mass density of $\rm {78.7 ^{+3.9}_{-4.7}\ M_{\odot}\ pc^{-2}}$up to 1 kpc and a local dark matter density of$0.0159^{+0.0047}_{-0.0057}\,\rm M_{\odot}\,\rm pc^{-3}$. We find that the sampling density (i.e. number of stars per unit volume) of the spectroscopic data contributes to about two-thirds of the uncertainty in the estimated values. We discuss the effect of the tilt term in the Jeans equation and find it has little impact on our measurement. Other issues, such as a non-equilibrium component due to perturbations and contamination by the thick disk population, are also discussed.Comment: 11 pages, 10 figure

Label Transfer from APOGEE to LAMOST: Precise Stellar Parameters for 450,000 LAMOST Giants

In this era of large-scale stellar spectroscopic surveys, measurements of stellar attributes ("labels," i.e. parameters and abundances) must be made precise and consistent across surveys. Here, we demonstrate that this can be achieved by a data-driven approach to spectral modeling. With The Cannon, we transfer information from the APOGEE survey to determine precise Teff, log g, [Fe/H], and [$\alpha$/M] from the spectra of 450,000 LAMOST giants. The Cannon fits a predictive model for LAMOST spectra using 9952 stars observed in common between the two surveys, taking five labels from APOGEE DR12 as ground truth: Teff, log g, [Fe/H], [\alpha/M], and K-band extinction $A_k$. The model is then used to infer Teff, log g, [Fe/H], and [$\alpha$/M] for 454,180 giants, 20% of the LAMOST DR2 stellar sample. These are the first [$\alpha$/M] values for the full set of LAMOST giants, and the largest catalog of [$\alpha$/M] for giant stars to date. Furthermore, these labels are by construction on the APOGEE label scale; for spectra with S/N > 50, cross-validation of the model yields typical uncertainties of 70K in Teff, 0.1 in log g, 0.1 in [Fe/H], and 0.04 in [$\alpha$/M], values comparable to the broadly stated, conservative APOGEE DR12 uncertainties. Thus, by using "label transfer" to tie low-resolution (LAMOST R $\sim$ 1800) spectra to the label scale of a much higher-resolution (APOGEE R $\sim$ 22,500) survey, we substantially reduce the inconsistencies between labels measured by the individual survey pipelines. This demonstrates that label transfer with The Cannon can successfully bring different surveys onto the same physical scale.Comment: 27 pages, 14 figures. Accepted by ApJ on 16 Dec 2016, implementing suggestions from the referee reports. Associated code available at https://github.com/annayqho/TheCanno