Human grading of introductory programming assignments is tedious and error-prone, hence researchers have attempted to develop tools that support automatic assessment of programming code. However, most such efforts often focus only on scoring solutions, rather than assessing whether students correctly understand the problems. To aid the students improve programming skills, effective feedback on programming assignments plays an important role. Individual feedback generation is tedious and painstaking process. We present a tool that not only automatically generates the static and dynamic program analysis outcomes, but also clusters similar code submissions to provide scalable and effective feedback to the students. We studied our tool on data from introductory Java programming assignments of year 1 course in School of Information Systems. In this paper, we share the details of our tool and findings of our experiments on 261 code submissions.