Decision Making under Uncertainty in Software Engineering: Release Readiness

本研究探讨了软件缺陷的检测。该研究的目的是解决“何时停止测试软件并发布它？'.在“立即交付！由于时间和预算的限制，真实的生活中的软件管理人员不会只观察一个因素，比如缺陷率。管理人员将他们的先验知识与代表不同生命周期过程的因素及其对软件产品最终可靠性的影响的历史数据相结合。此外，产品可靠性与软件开发生命周期（SDLC）活动密切相关。SDLC中的每个阶段都必须通过考虑产品，过程和人员相关因素的关系，以及这些阶段之间的关系及其对最终软件产品可靠性的影响来建模。以前在发布计划方面的研究很好地解决了如何根据涉众的偏好确定SDLC过程的优先级。然而，还需要对SDLC过程之间的因果关系进行建模，以确定版本是否在其可靠性方面准备就绪。本研究旨在了解SDLC活动导致停止测试活动决定的因果关系。本研究以实证分析为基础，旨在建立一个量化软件产品发布准备度的模型。软件工程领域的其他研究人员也可以使用该模型。我的目标是开发一个贝叶斯模型，该模型使用基于数据可用性和质量的定量和定性数据。这种混合模式将通过将从组织系统中提取的本地数据与通过问卷调查收集的专家判断相结合来提供灵活性。我还计划扩展我现有的软件度量收集工具Prest，以包括更多的度量以及分析、缺陷和可靠性预测的功能。拟议的研究计划是高度相关的加拿大软件开发行业。在加拿大的软件开发公司，协助他们的管理人员在不确定情况下做出决策，可以使用该工具。

This research investigates the detection of software defects. The aim of the research is to address the question of "when to stop testing the software and release it?'. Under the constant pressure of "Deliver Now!' due time and budget constraints, software managers in real life do not observe only one factor, such as defect rates. Managers combine their prior knowledge with historical data about factors representing different lifecycle processes and their effects on the final reliability of software product. Furthermore, product reliability is strongly connected with software development life cycle (SDLC) activities. Each phase in the SDLC has to be modeled by considering the relations of product, process, and people related factors, as well as the relationships between these phases and their impacts on the final software product reliability. Previous studies in release planning well addressed how SDLC processes can be prioritized based on stakeholder preferences. However, there is also a need to model casual relations between SDLC processes to decide if the release is ready in terms of its reliability. This research aims to understand cause - effect relationships of SDLC activities leading decisions to stop testing activity. This research program is based on empirical analyses and aims to develop a model to quantify release readiness of software product. Other researchers in the software engineering domain can also use this model. My objective is to develop a Bayesian model that uses both quantitative and qualitative data based on data availability and quality. Such a hybrid model would give flexibility by combining local data extracted from organizational systems with expert judgments collected through questionnaires. I also plan to extend my existing software metrics collection tool, Prest, to include more metrics, and capabilities for analysis, defect and reliability prediction. The proposed research program is highly relevant to the Canadian software development industry. Software development companies in Canada to assist their managers to make decisions under uncertainty can use the tool.