The prevalence of software systems has become an integral part of modern-day living. Software usage has increased significantly, leading to its growth in both size and complexity. Consequently, software development is becoming a more time-consuming process. In an attempt to accelerate the development cycle, the testing phase is often neglected, leading to the deployment of flawed systems that can have significant implications on the users daily activities. This work presents TestLab, an intelligent automated software testing framework that attempts to gather a set of testing methods and automate them using Artificial Intelligence to allow continuous testing of software systems at multiple levels from different scopes, ranging from developers to end-users. The tool consists of three modules, each serving a distinct purpose. The first two modules aim to identify vulnerabilities from different perspectives, while the third module enhances traditional automated software testing by automatically generating test cases through source code analysis.

翻译：[translated abstract in Chinese] 软件系统的普及已成为现代生活不可或缺的一部分。随着软件使用量的显著增长，其规模与复杂度也随之提升，导致软件开发过程日益耗时。为加速开发周期，测试阶段常被忽视，从而部署存在缺陷的系统，对用户的日常活动造成重大影响。本文提出TestLab——一种智能自动化软件测试框架，旨在收集多种测试方法，并利用人工智能实现自动化，支持从开发者到最终用户的不同层面、多视角的连续软件系统测试。该工具包含三个模块，各具独特功能：前两个模块旨在从不同角度识别漏洞，第三个模块则通过源代码分析自动生成测试用例，增强传统自动化软件测试能力。