SHF: Small: Collaborative Research: Helping Mobile App Developers Make Implementation Decisions Based on App Store Analytics

SHF：小型：协作研究：帮助移动应用程序开发人员根据应用程序商店分析做出实施决策

• 批准号: 1619455
• 负责人: William Halfond
• 金额: $ 25.69万
• 依托单位: University of Southern California
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-07-01 至 2020-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1619455&HistoricalAwards=false
• 关键词: SHF; Small; Collaborative; Research; Helping

The growth of mobile apps in recent years has been aided by Frameworks, Services, and Third Party Libraries (FSTPL), which provide support for user interfaces, advertising, analytics, and other critical app functionality. These FSTPLs enhance developer productivity, improve security, make key functionality easily accessible, and modularize complex and error-prone components. Our prior work shows that there is a tradeoff between the benefits of using FSTPLs and the impact they have on end users; however, developers lack clear guidance on how to manage these tradeoffs. Best practices that can be found online are generally anecdotal and sometimes contradictory. For developers who wish to improve their apps while maintaining the use of FSTPLs, there is no way to quantify or estimate the magnitude or impact of their FSTPL related design and implementation decisions. This motivates us to investigate techniques that can help developers more accurately evaluate FSTPL tradeoffs. The results of this investigation will advance the state of the art in software engineering methodology and education, benefiting society by leading to the development of apps with higher reliability and usability. For methodology, this will result in techniques to help developers improve the quality of their apps. For education it will enhance training of future software developers in using analytical techniques to drive software design and implementation decisions.In this proposal the PIs will investigate techniques to help app developers evaluate their usage of FSTPLs and their impact on end users? experience. The proposed work will include the design of techniques and methodologies for quantifying the way developers use FSTPLs in their apps and correlating their usage with user ratings and reviews that will be mined from the app stores. Within this project, the PIs will focus on two thrusts. The first will be to design program analysis based techniques that can measure and quantify the usage patterns of FSTPLs in mobile apps. The second will be to perform empirical investigations by applying the program analysis based techniques on apps from app stores and using statistical analysis to understand relationships between the gathered data and various user feedback based metrics, such as the ratings of apps, to learn best and worst practices for using FSTPLs. The techniques and methodologies produced by these two thrusts will allow developers to analyze their apps and determine if their usage of FSTPLs could negatively or positively impact the user experience. The approach will provide objective and quantifiable guidance to developers to make refactoring choices, redesign components, and other such decisions about their apps. Therefore developers will be able to understand how their design and implementation choices affect the users? perception of their apps. More broadly, the proposed work will define a methodology for guiding developers in making design decisions and a way to tie these decisions to ratings based outcomes.

近年来移动应用的增长得益于框架、服务和第三方库(FSTPL)，它们为用户界面、广告、分析和其他关键应用功能提供支持。这些FSTPL提高了开发人员的工作效率，提高了安全性，使关键功能易于访问，并将复杂且容易出错的组件模块化。我们之前的工作表明，在使用FSTPL的好处和它们对最终用户的影响之间存在权衡；然而，开发人员缺乏关于如何管理这些权衡的明确指导。可以在网上找到的最佳实践通常是轶事，有时甚至是相互矛盾的。对于希望在保持使用FSTPL的同时改进其应用程序的开发人员来说，无法量化或估计其与FSTPL相关的设计和实施决策的规模或影响。这促使我们研究可以帮助开发人员更准确地评估FSTPL权衡的技术。这项调查的结果将推动软件工程方法论和教育的发展，通过开发可靠性和可用性更高的应用程序来造福社会。在方法上，这将导致技术来帮助开发人员提高他们的应用程序的质量。在教育方面，它将加强对未来软件开发人员的培训，使用分析技术来驱动软件设计和实现决策。在这项提案中，PI将调查技术，以帮助应用程序开发人员评估他们对FSTPL的使用及其对最终用户的影响？经验。拟议的工作将包括设计技术和方法，以量化开发人员在其应用程序中使用FSTPL的方式，并将其使用与将从应用程序商店挖掘的用户评级和评论相关联。在这个项目中，PI将重点放在两个方面。第一个将是设计基于程序分析的技术，可以测量和量化移动应用程序中FSTPL的使用模式。第二个将是通过对应用商店中的应用程序应用基于程序分析的技术并使用统计分析来了解收集的数据与各种基于用户反馈的指标(如应用程序的评级)之间的关系，以了解使用FSTPL的最佳和最差实践，从而进行实证调查。这两项努力产生的技术和方法将允许开发人员分析他们的应用程序，并确定他们对FSTPL的使用是否会对用户体验产生负面或积极的影响。该方法将为开发人员提供客观和可量化的指导，以做出重构选择、重新设计组件和其他关于其应用程序的决策。因此，开发人员将能够理解他们的设计和实现选择如何影响用户？对他们的应用程序的感知。更广泛地说，拟议的工作将定义一种指导开发人员做出设计决策的方法，以及一种将这些决策与基于评级的结果联系起来的方法。