Novice programmers are difficult to debug on their own because of their lacking of prior knowledge. If we want to help them, first we need to able to check the correctness of a novice¡¦s program. And whenever any error is found, we could provide some suggestion to assist them in debugging. We use concolic testing algorithm to automatically generate test inputs. The test inputs generation of the concolic testing is directed by negating path conditions and is produced by solving path constraints. By using of concolic testing, we are able to explore as much more branches as we can. And once we found an error, we will try to locate it for novice programmers. We propose a new method called concolic debugging. Its idea comes from concolic testing. The concolic debugging algorithm initiates with a given failed test, and try to locate the faulty block by negating and backtracking the path conditions of the failed test. We use concolic testing to improve assessing style of the automated assessment system. 86.67% of our sample programs are successfully assessed by concolic testing algorithm on our new automated assessment system. And we also found our concolic debugging is much more stable and accuracy on fault localization then spectrum-based fault localization.

The development of software today, the company has their own test system usually. Because there has a few bugs in the every software. And it will make the damage of company¡¦s property or security of information. We can find the bugs in the software by the test systems. But the few bugs will appear repeatedly even if you have been fixed it. In this time, it will be effective if we use the automatic test systems. They can solve the waste of time and cost. Appearance of the automatic test system has been solved the defect of the test method in the past. In this paper will mention two kind of automatic test systems, one of them is concolic testing, and another is random testing. In the 2009, there had the few of evidence to discuss that the concolic testing was more effective than the random testing, but there wasn¡¦t have the enough demonstration. So I hope to prove that the effectiveness comparison between concolic and random testing by this paper.

As dynamic web applications are becoming widespread nearly in every area, ASP.NET is one of the popular development languages in this domain. The errors in these web applications can reduce the credibility of the site and cause possible loss of a number of clients. Therefore, testing these applications becomes significant. We present an automated tool to test ASP.NET web applications against execution errors and HTML errors that cause displaying inaccurate and incomplete information. Our tool, called Mamoste, adapts concolic testing technique which interleaves concrete and symbolic executions to generate test inputs dynamically. Mamoste also considers page events as inputs which cannot be handled with concolic testing. We have performed experiments on a subset of an heavily used ASP.NET application of a government office. We have found 366 HTML errors and a faulty component which is used almost every ASP.NET page in this application. In addition, Mamoste discovered that a common user control is misused in several generated pages.

The overall goal of this research is to reduce the cost of software development and improve the quality of software. Symbolic execution is a program-analysis technique that is used to address several problems that arise in developing high-quality software. Despite the fact that the symbolic execution technique is well understood, and performing symbolic execution on simple programs is straightforward, it is still not possible to apply the technique to the general class of large, real-world software. A symbolic-execution system can be effectively applied to large, real-world software if it has at least the two features: efficiency and automation. However, efficient and automatic symbolic execution of real-world programs is a lofty goal because of both theoretical and practical reasons. Theoretically, achieving this goal requires solving an intractable problem (i.e., solving constraints). Practically, achieving this goal requires overwhelming effort to implement a symbolic-execution system that can precisely and automatically symbolically execute real-world programs. This research makes three major contributions. 1. Three new techniques that address three important problems of symbolic execution. Compared to existing techniques, the new techniques * reduce the manual effort that may be required to symbolically execute those programs that either generate complex constraints or parts of which cannot be symbolically executed due to limitations of a symbolic-execution system. * improve the usefulness of symbolic execution (e.g., expose more bugs in a program) by enabling discovery of more feasible paths within a given time budget. 2. A novel approach that uses symbolic execution to generate test inputs for Apps that run on modern mobile devices such as smartphones and tablets. 3. Implementations of the above techniques and empirical results obtained from applying those techniques to real-world programs that demonstrate their effectiveness.