In programming courses, the traditional assessment approach tends to evaluate student performance by scoring one or more project-level summative assignments. This approach no longer meets the requirements of a quality programming language education. Based on an upgraded peer code review model, we propose a formative assessment approach to assess the learning of computer programming languages, and develop an online assessment system (OOCourse) to implement this approach. Peer code review and inspection is an effective way to ensure the high quality of a program by systematically checking the source code. Though it is commonly applied in industrial and open-source software development, it is rarely taught and practiced in undergraduate-level programming courses. We conduct a case study using the formative assessment method in a sophomore level Object-Oriented Design and Construction course with more than 240 students. We use Moodle (an online learning system) and some relevant plugins to conduct peer code review. We also conduct data mining on the running data from the peer assessment activities. The case study shows that formative assessment based on peer code review gradually improved the programming ability of students in the undergraduate class.

To evaluate the fault location and the failure prediction models, simulation-based and code-based experiments were conducted to collect the required failure data. The PIE model was applied to simulate failures in the simulation-based experiment. Based on syntax and semantic level fault injections, a hybrid fault injection model is presented. To analyze the injected faults, the difficulty to inject (DTI) and difficulty to detect (DTD) are introduced and are measured from the programs used in the code-based experiment. Three interesting results were obtained from the experiments: 1) Failures simulated by the PIE model without consideration of the program and testing features are unreliably predicted; 2) There is no obvious correlation between the DTI and DTD parameters; 3) The DTD for syntax level faults changes in a different pattern to that for semantic level faults when the DTI increases. The results show that the parameters have a strong effect on the failures simulated, and the measurement of DTD is not strict.