Automated Debugging Program debugging is a process of identifying and fixing bugs. Identifying root causes is the hardest, thus the most expensive, component of debugging. Developers often take a slice of the statements involved in a failure, hypothesize a set of potential causes in an ad hoc manner, and iteratively verify and refine their hypotheses until root causes are located. Obviously, this process can be quite tedious and time-consuming. Furthermore, as software systems are getting increasingly complex, the inefficiencies of the manual debugging process are getting magnified. Many automated approaches have been proposed to facilitate program debugging. All these approaches share the same ultimate goal, which is to help developers quickly and accurately pinpoint the root causes of failures. This course will cover state-of-the-art automated debugging approaches from both practical and research perspectives and will consist of two main parts. The goal of the first part is two folds: 1) To turn program debugging from a black art (as many believe) into a systematic and well-organized discipline; and 2) To provide students with enough background information to read and understand the scientific literature. The topics which will be covered in the first part are: How Failures Come To Be, Tracking Problems, Making Programs Fail, Reproducing Problems, Simplifying Problems, Scientific Debugging, Deducing Errors, and Mining and Detecting Anomalies. The second part of the course will survey the related literature by dividing it into four broad categories, namely static- analysis-based, dynamic-analysis-based, model-based, and empirical approaches.
Automated Debugging (CS 460)
| Programs\Type | Required | Core Elective | Area Elective |
| Computer Science and Engineering | * | ||
| Computer Science and Engineering | * | ||
| Electronics Engineering | * | ||
| Electronics Engineering | * | ||
| Industrial Engineering | * | ||
| Industrial Engineering (Previous Name: Manufacturing Systems Engineering) | * | ||
| Materials Science and Nano Engineering | * | ||
| Materials Science and Nano Engineering (Previous Name: Materials Science and Engineering) | * | ||
| Mechatronics Engineering | * | ||
| Mechatronics Engineering | * | ||
| Microelectronics | * | ||
| Telecommunications | * |
CONTENT
LEARNING OUTCOMES
- Describe and apply the principles of systematic program debugging.
- Identify, formulate, analyze, and solve basic problems related to automating the debugging process.
- Design and implement basic automated debugging tools.
- Use, analyze, and evaluate state-of-the-art debugging tools.
- Read and understand the related scientific literature.
PROGRAMME OUTCOMES
1. Understand the world, their country, their society, as well as themselves and have awareness of ethical problems, social rights, values and responsibility to the self and to others.
2. Understand different disciplines from natural and social sciences to mathematics and art, and develop interdisciplinary approaches in thinking and practice.
3. Think critically, follow innovations and developments in science and technology, demonstrate personal and organizational entrepreneurship and engage in life-long learning in various subjects; have the ability to continue to educate him/herself.
4. Communicate effectively in Turkish and English by oral, written, graphical and technological means.
5. Take individual and team responsibility, function effectively and respectively as an individual and a member or a leader of a team; and have the skills to work effectively in multi-disciplinary teams.
1. Possess sufficient knowledge of mathematics, science, fundamental engineering, computational methods and program-specific engineering topics; use theoretical and applied knowledge of these areas in complex engineering problems.
2. Identify, define, formulate and solve complex engineering problems while considering the UN Sustainable Development Goals; choose and apply suitable analysis, design, estimation/prediction and modeling methods for this purpose.
3. Develop, choose and use modern techniques and tools that are needed for analysis and solution of complex problems faced in engineering applications; use information technologies effectively.
4. Have the ability to design a complex system, process, instrument or a product under realistic constraints and conditions, with the goal of fulfilling creative current and future requirements.
5. Use research methods, including conducting literature reviews, designing experiments, performing experiments, collecting data, analyzing results, and interpreting results, to investigate complex engineering problems or discipline-specific research topics.
6. Possess knowledge of business practices such as project management, risk management, change management, and economic feasibility analysis; awareness on entrepreneurship and innovation.
7. Possess knowledge of impact of engineering solutions on society, health and safety, the economy, sustainability, and the environment within the framework of the UN Sustainable Development Goals; awareness on legal outcomes of engineering solutions; awareness of acting impartially and inclusively without any form of discrimination; act in accordance with ethical principles, possessing knowledge of professional and ethical responsibilities.
8. Communicate effectively, both orally and in writing, on technical subjects, considering the diverse characteristics of the target audience (such as education, language, and profession).