Textual information driven software quality improvement

社会对软件和信息技术的依赖和依赖， 无处不在的手持设备。典型的青少年每天不会超过几分钟， 触摸手机、MP3播放器或游戏机。消费者要求更复杂 程序，更多的功能和最高的质量。软件开发人员必须不断发展 这么多的节目。然而，由于几个原因，进化程序是困难的。高级别 文档是稀缺的或过时的，因此，大多数时候开发人员必须依赖于唯一的 最新的信息来源：源代码本身，以及在可用和最新的情况下， 错误跟踪系统、邮件列表、论坛或博客中包含的信息。 软件的不断变化进一步加剧了信息的不一致性。的来源 信息本质上是文本，是自然语言，因此很难系统地使用，因为 它们是模糊的，例如，“path”可以指开发人员的文件系统路径， 在地图上为地图导航系统的用户显示。我们推测，信息不一致损害 程序理解，它增加了程序理解的努力，并最终增加了错误倾向。 这项研究计划的长期目标是促进信息的一致性，从而增加 软件质量通过识别文本歧义和不一致， 改进，以及文本信息的半自动重构（包括代码注释和 标识符）。更准确地说，我们将量化上下文和信息不一致对错误的影响 当考虑作为文本信息的来源时， 代码本身、错误报告、邮件列表、论坛和博客。一旦发现不一致， 将提出量化的适当改进建议，并根据开发人员的决定 将执行重构动作以减轻或完全消除不一致。

Society's reliance and dependence on software and information technology is nowhere more obvious than in the ubiquity of hand-held devices. The typical teenager will go no more than a few minutes per day without touching either a cell phone, an MP3 player or a gaming console. Consumers demand more sophisticated programs, more features, and the highest possible quality. Software developers must continuously evolve this huge number of programs. However, evolving programs is difficult for several reasons. High-level documentation is scarce or outdated and, thus, most of the times developers must rely on the only up-to-date sources of information: the source code itself, and, when available and up to date, on textual information contained into bug-tracking systems, mailing lists, forums or blogs. The problem of changing software is further exacerbated information inconsistency. The sources of information are by nature textual, in natural language, and, thus, difficult to use systematically because they are ambiguous, e.g., "path" could refer to a filesystem path for a developer while it may refer to a path on a map for a user of a map navigation system. We conjecture that information inconsistency impairs program understanding, it increases program understanding effort, and, ultimately, fault proneness. The long term goal of this research program is to promote information consistency and thus increase software quality through the identification of textual ambiguities and inconsistency, the recommendation of improvements, and the semi-automatic refactoring of textual information (including code comments and identifiers). More precisely, we will quantify the effect of context and information inconsistency on fault and change proneness and on program understanding effort, when considering as source of textual information the code itself, bug reports, mailing lists, forums and blogs. Once the inconsistency will be identified and quantified appropriate recommendations of improvements will be made, and, based on developers decisions refactoring actions, to mitigate or completely remove inconsistency, will be performed.