SBIR Phase II: Efficient static analysis tools for detecting bugs and improving developer productivity

这个SBIR第二阶段项目开发软件产品，以提高软件质量和开发人员的生产力。计算机在我们的生活中无处不在，大多数应用程序都需要高可靠性，可用性和安全性。尽管努力提高质量，错误仍然太常见，成本太高。 为了解决这些问题，该团队在静态分析和错误检测方面进行了研究-采用基于模式的方法-将数据挖掘应用于软件代码分析。 第二阶段的工作重点是将工具集成到软件开发生命周期中，为客户提供从工具中获益的最佳方式。该团队还将开发所需的功能（分支质量管理、补丁挖掘）和代码搜索--所有新的、独特的、更广泛的和重要的技术用途都是由客户在第一阶段确定的。这些工具一旦商业化，可以使不同业务部门（IT，金融，政府，娱乐，保险等）的大部分IT部门受益，以提高他们的软件质量和生产力，并通过自动错误检测降低软件开发成本。与传统的手动工作相比，程序员通常需要1-2周的时间来检测一个bug，所提出的工具可以在1-2小时内轻松地自动识别数百万行代码中的数百个bug。一旦检测到错误（无论是从这些工具，或任何其他工具，这些工具可以用来确保错误修复应用于整个代码。 除了检测软件错误之外，所提出的工具还可以用于检测来自开源或其他软件的非法软件剽窃。

This SBIR Phase II project develops software products to improve software quality and developer productivity. Computers are used everywhere in our lives with most applications requiring high reliability, availability, and security. Despite efforts to improve quality, bugs are still too common and costly. To address these problems the team has conducted research in static-analysis and bug detection - taking a pattern-based approach - applying data-mining to software code analysis. The Phase II effort will focus on integration of the tools into the software development lifecycle providing customers an optimal way to benefit from the tools. The team will also develop needed functionality (Branch Quality Management, Patch-Mining) and code search - all new, unique, broader and important usages of technology identified by customers from Phase I. The tools, once commercialized, can benefit a large percentage of IT departments in different business segments (IT, finance, government, entertainment, insurance, etc) to improve their software quality and productivity and reduce the software development cost via automatic bug detection. In contrast to traditional manual effort that usually takes a programmer 1-2 weeks to detect a bug, the proposed tools can easily identify hundreds of bugs in millions lines of code automatically in 1-2 hours. Once a bug is detected (either from these tools, or any other tools, the tools can be used to ensure that the bug-fix is applied throughout the code. In addition to detecting software bugs, the proposed tools can also be used to detect illegal software plagiarism from open source or other software.