Using Dart’s Libraries

Translating each of a UNIX software system's source files into an object file, and linking the object files into an executable file, can be a time-consuming process. Object file generation accounts for most of this time. Tools that recognize and avoid unnecessary object file regeneration are very popular. Many such tools are named MAKE. A software system often contains a parameter file. A parameter file is a source file, textually included by every other source file, which defines macros shared by multiple source files. Each object file depends on the parameter file, according to file dependencies. MAKE-like tools only understand file dependencies. So, when a software developer changes a macro in a parameter file, every object file is regenerated, regardless of whether its corresponding source file actually refers to the changed macro. Unnecessary object file regeneration can be avoided by replacing some file dependencies with macro dependencies, which express that an object file depends on a macro. DEP is a tool implementing a method for automatically detecting and maintaining a software system's file and macro dependencies. DEP works with any flavour of MAKE to minimize the cost of rebuilding an executable file.

Unified builds are a simple but effective technique to reduce the build time of large software projects. Unified builds generate large compiler tasks by bundling multiple source files into one, resulting in a significant reduction in build time through removal of redundant work incurred by shared headers. However, unified builds have a negative effect on incremental builds because each compiler task gets larger. An ad-hoc unification strategy causes an excessive slowdown in incremental builds. A rough report from WebKit says the worst slowdown is 20% (6s → 7s), but our investigation shows it is as high as 479% (19s → 110s). In this paper, we investigate the characteristics of unified builds to find a sweet spot, which generates compiler tasks that reduce the full build time without increasing the incremental build time. An in-depth analysis of WebKit reveals 1) source files with higher header similarity should be unified, 2) source files that have significant differences in compile times should not be unified, and 3) source files that are not frontend-intensive should not be unified. Our case study shows the total build time is reduced by 2.66%, and the worst slowdown falls from 479% to 129%. These findings will be of help in deriving a more intelligent strategy of unification and give a basis for discussions on future build systems, compilers, and module systems that cooperatively generate efficient compiler tasks.

CHAPTER 11 - Using the Pentium Optimizer Program

The goal of the Biological General Repository for Interaction Datasets (BioGRID) (http://www.thebiogrid.org) is to archive and freely disseminate collections of genetic and protein interactions from major model organisms. BioGRID currently houses over 335,000 interactions curated from high-throughput datasets and individual focused studies found in the primary literature, as derived from some 23,000 publications. Complete coverage of the entire literature for both the budding yeast Saccharomyces cerevisiae and the fission yeast Schizosaccharomyces pombe has been achieved, resulting in the curation of over 246,000 interactions, and efforts to expand curation across multiple species are underway. Through collaborations with the Gene Ontology (GO) Consortium and the Linking Animal Models to Human Disease Initiative (LAMHDI), we are focusing our curation efforts across model organisms on particular areas of biology to enable insights into conserved networks and pathways that are relevant to human health.The BioGRID 3.0 web interface contains new search and display features that enable rapid queries across multiple data types and sources. A dedicated Interaction Management System (IMS) is used to track all curation and to prioritize publications across multiple curation projects. BioGRID data are incorporated in several model organism databases and other biological databases. The entire BioGRID interaction collection may be downloaded in multiple file formats, including PSI MI XML, and source code for BioGRID is freely available without any restrictions. This work is supported by NIH NCRR grant R01 RR024031 to MT and KD, and by grants from the CIHR and BBSRC to MT.

As citizens debate the morality of using global surveillance to enforce cyber security, software technologies that can proliferate illegal distribution of copyright material are evolving rapidly. One such technology is Peer-to-Peer networking which, through well-known implementations such as Napster, Bittorrent and eMule, has enabled users to share files at optimal speeds and at near infinite scale. This technology is contentious in that it can distribute highly desired files globally in minutes if not seconds and determining illegal vs legal applications is a challenge. Recently, a new player Xunlei has arrived on the Peer-to-Peer scene with an impressive network and unprecedented global reach. Xunlei, a proprietary Peer-to-Peer network, is unique in that it aggregates multiple file sources together seamlessly enabling content to be consumed via a single client. The aggregated approach raises some ethical dilemmas. Is it a good thing that centralised management of Peer-to-Peer networks exists? Is it a form of populous control? Where will it lead as Peer-to-Peer usage becomes more mainstream? Finally, does it threaten an individual's privacy? This paper investigates the Xunlei network as it stands today and takes valuable steps towards addressing these questions, and to defining future fields of research.

Binary similarity analysis is critical to many code-reuse-related issues, where function matching is its fundamental task. “1-to-1” mechanism has been applied in most binary similarity analysis works, in which one function in a binary file is matched against one function in a source file or binary file. However, we discover that the function mapping is a more complex problem of “1-to-n” (one binary function matches multiple source functions or binary functions) or even “n-to-n” (multiple binary functions match multiple binary functions) due to the existence offunction inlining, different from traditional understanding.In this article, we investigate the effect of function inlining on binary similarity analysis. We carry out three studies to investigate the extent of function inlining, the performance of existing works under function inlining, and the effectiveness of existing inlining-simulation strategies. Firstly, a scalable and lightweight identification method is designed to recover function inlining in binaries. 88 projects (compiled in 288 versions and resulting in 32,460,156 binary functions) are collected and analyzed to construct four inlining-oriented datasets for four security tasks in the software supply chain, including code search, OSS (Open Source Software) reuse detection, vulnerability detection, and patch presence test. Datasets reveal that the proportion of function inlining ranges from 30–40% when using O3 and sometimes can reach nearly 70%. Then, we evaluate four existing works on our dataset. Results show most existing works neglect inlining and use the “1-to-1” mechanism. The mismatches cause a 30% loss in performance during code search and a 40% loss during vulnerability detection. Moreover, most inlined functions would be ignored during OSS reuse detection and patch presence test, thus leaving these functions risky. Finally, we analyze two inlining-simulation strategies on our dataset. It is shown that they miss nearly 40% of the inlined functions, and there is still a large space for promotion. By precisely recovering when function inlining happens, we discover that inlining is usually cumulative when optimization increases. Thus, conditional inlining and incremental inlining are recommended to design a low-cost and high-coverage inlining-simulation strategy.