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In a software life-cycle Source code repositories serve as vast storage areas for program code, ensuring its maintenance and version control throughout the development process. It is not uncommon for these repositories to house programs with hidden errors, which only manifest under specific input conditions, causing the program to deviate from its intended functionality. The growing intricacy of software design has amplified the time and resources required to pinpoint and rectify these issues. These errors, often unintended by developers, can be challenging to identify and correct. While there are techniques to auto-correct faulty code, the expansive realm of potential solutions for a single bug means there's a scarcity of tools and datasets for effective evaluation of the corrected code. This study presents FIXEVAL, a benchmark that includes flawed code entries from competitive coding challenges and their corresponding corrections. FIXEVAL offers an extensive test suite that not only gauges the accuracy of fixes generated by models but also allows for the assessment of a program's functional correctness. This suite further sheds light on time, memory limits, and acceptance based on specific outcomes. We utilize cutting-edge language models, trained on coding languages, as our reference point and juxtapose them using match-based (essentially token similarity) and execution-based (focusing on functional assessment) criteria. Our research indicates that while match-based criteria might not truly represent the functional precision of fixes generated by models, execution-based approaches offer a comprehensive evaluation tailored to the solution. Consequently, we posit that FIXEVAL paves the way for practical automated error correction and assessment of code generated by models. Dataset and models for all of our experiments are made publicly available at https://github.com/mahimanzum/FixEval. / Master of Science / Think of source code repositories as big digital libraries where computer programs are kept safe and updated. Sometimes, these programs have hidden mistakes that only show up under certain conditions, making the program act differently than planned which we call bugs or errors. As software gets more complex, it takes more time and effort to find and fix these mistakes. Even though there are ways to automatically fix these errors, finding the best solution can be like looking for a needle in a haystack. That's why there aren't many tools to check if the automatic fixes are right. Enter FIXEVAL: our new tool that tests and compares faulty computer code from coding competitions and their fixes. It has a set of tests to see how well the fixed code works and gives insights into its performance and results. We used the latest computer language tools to see how well they fix code, comparing them in two ways: by looking at the code's structure and by testing its function. Our findings? Just looking at the code's structure isn't enough; we need to test how it works in action. We believe FIXEVAL is a big step forward in making sure automatic code fixes are spot-on. Dataset and models for all of our experiments are made publicly available at https://github.com/mahimanzum/FixEval.

Automated grading systems have been researched at various universities for several years. Numerous systems have been developed that automate the process of grading by compiling, executing and testing the students submitted source code. However, such systems are mostly written as UNIX scripts and are restricted to performing one kind of activity. The instructors or teaching assistants have to resort to other methods in order to provide their feedback to the students. The core of this thesis is to research a TA feedback mechanism which will streamline the grading process for the professors and teaching assistants. A web-based grading tool has been developed that allows course staff to enter comments for students' programs directly through a web browser. The interface provides for full direct-manipulation editing of comments, which are then immediately viewable by students when they look up assignment results. Such an interface also has potential to support peer grading of assignments. Teaching assistants of introductory programming level courses were interviewed to learn about the different grading methods they use and were asked their opinion of our new grading interface. TAs were also asked to grade assignments using the traditional paper method as well as the computer using our new grading tool for comparison. Finally, an anonymous survey was sent out to various computer science faculties in different universities to gather information about the expectations they have with respect to TA grading activities for programming assignments and the learning outcomes that these professors desire for their students. / Master of Science

Automated Electric Transportation (AET) proposes a system of automated platooning vehicles electrically powered by the roadway via wireless inductive power transfer. This has the potential to provide roadway transportation that is less congested, more flexible, cleaner, safer, and faster than the current system. The focus of this research is to show how platooning can be accomplished in a safe manner and what capacities such an automated platooning system can achieve. To accomplish this, first two collision models are developed to show the performance of automated platoons during an emergency braking scenario: a stochastic model coded in Matlab/Simulink and a deterministic model with closed-form solutions. The necessary parameters for safe platooning are then defined: brake variances, communication delays, and maximum acceptable collision speeds. The two collision models are compared using the Student's t-test to show their equivalence. It is shown that while the two do not yield identical results, in most cases the results of the deterministic model are more conservative than and reasonably close to the results of the deterministic model. The deterministic model is then used to develop a capacity model describing automated platooning flow as a function of speed and platoon size. For conditions where platooning is initially unsafe, three amelioration protocols are evaluated: brake derating, collaborative braking, and increasing the maximum acceptable collision speed. Automated platooning flow is evaluated for all of these scenarios, compared both with each other and with traditional roadway flow patterns. The results of these models show that when platooning is initially safe, very high vehicle flows are possible: for example, over 12,000 veh/hr for initial speeds of 30 m/s and 10 vehicle platoons. Varying system paramaters can have large ramifications for overall capacity. For example, autonomous (non-platooning) vehicles do not promise anywhere near this level, and in many cases struggle to approach the capacity of traditional roadways. Additionally, ensuring safety under an emergency braking standard requires very small communication delays and, most importantly, tight braking variances between the vehicles within a platoon. As proposed by AET, a single type of electric vehicle, combined with modern wireless communications, can make platooning safer than was previously possible without requiring amelioration. Both brake derating and collaborative braking can make platooning safer, but they reduce capacity and may not be practical for real-world implementation. Stricter versions of these, cumulative brake derating and exponential collaborative braking, are also evaluated. Both can degrade capacity to near current roadway levels, especially if a large degree of amelioration is required. Increasing maximum acceptable collision speed, such as through designing vehicles to better withstand rear-end collisions, shows more promise in enabling safe intraplatoon interactions, especially for scenarios with small communication delays (i.e. under 50 ms).

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.

Report (M. Eng.)--Virginia Polytechnic Institute and State University, 1993. / Vita. Abstract. Includes bibliographical references (leaves 80-82). Also available via the Internet.

The deployment of Automated Vehicles (AV) is starting to become widespread throughout transportation, resulting in the recognition and awareness by legislative leaders of the potential impact on transportation operations. To assist transportation operators in making the needed preparations for these vehicles, an in-depth study regarding the impact of AV and Connected Automated Vehicles (CAV) is needed. In this research, the impact of AV and CAV on the highway setting is studied. This study addresses car-following models that are currently used for simulating AV and CAV. Diverse car-following models, such as the Intelligent Driver Model (IDM), the IDM with traffic adaptive driving Strategy (SIDM), the Improved IDM (IIDM), the IIDM with Constant-Acceleration Heuristic (CAH), and the MIcroscopic model for Simulation of Intelligent Cruise control (MIXIC) were examined with the state-of-the-art vehicle trajectory data. The Highway Drone dataset (HighD) were analyzed through the implementation of genetic algorithm to gain more insight about the trajectories of these vehicles. In 2020, there is no commercially available gully automated vehicle available to the public, although many companies are conducting in field testing. This research generated AV trajectories based on the actual vehicle trajectories from the High-D dataset and adjusts those trajectories to account for ideal AV operations. The analysis from the fitted trajectory data shows that the calibrated IIDM with CAH provides a best fit on AV behavior. Next, the AV and CAV were modeled in microscopic perspective to show the impact of these vehicles on a corridor. The traffic simulation software, VISSIM, modified by implementing an external driver model to govern the interactions between Legacy Vehicles (LV), AV, and CAV on a basic and merging highway segment as well as a model of the Interstate 95 corridor south of Richmond, Virginia. From the analysis, this research revealed that the AV and CAV could increase highway capacity significantly. Even with a small portion of AV or CAV, the roadway capacity increased. On I-95, CAV performed better than AV because of Cooperative Adaptive Cruise Control (CACC) and platooning due to CAV's ability to coordinate movement through communication; however, in weaving segments, CAV underperformed AV. This result indicates that the CAV algorithms would need to be flexible in order to maintain flow in areas with weaving sections. Lastly, diverse operational conditions, such as different heavy vehicle market penetration and different aggressiveness were examined to support traffic operators transition to the introduction of AV and CAV. Based on the analysis, the study concludes that the different aggressiveness could mitigate congestion in all cases if the proper aggressiveness level is selected considering the current traffic condition. Overall, the dissertation provides guidance to researchers, traffic operators, and lawmakers to model, simulate, and evaluate AV and CAV on highways. / Doctor of Philosophy / The deployment of Automated Vehicles (AV) is starting to become widespread throughout transportation, resulting in the recognition and awareness by legislative leaders of the potential impact on transportation operations. To assist transportation operators in making the needed preparations for these vehicles, an in-depth study regarding the impact of AV and Connected Automated Vehicles (CAV) is needed. In this research, the impact of AV and CAV on the highway setting is studied. This study addresses car-following models that are currently used for simulating AV and CAV. Diverse car-following models, such as the Intelligent Driver Model (IDM), the IDM with traffic adaptive driving Strategy (SIDM), the Improved IDM (IIDM), the IIDM with Constant-Acceleration Heuristic (CAH), and the MIcroscopic model for Simulation of Intelligent Cruise control (MIXIC) were examined with the state-of-the-art vehicle trajectory data. The Highway Drone dataset (HighD) were analyzed through the implementation of genetic algorithm to gain more insight about the trajectories of these vehicles. In 2020, there is no commercially available gully automated vehicle available to the public, although many companies are conducting in field testing. This research generated AV trajectories based on the actual vehicle trajectories from the High-D dataset and adjusts those trajectories to account for ideal AV operations. The analysis from the fitted trajectory data shows that the calibrated IIDM with CAH provides a best fit on AV behavior. Next, the AV and CAV were modeled in microscopic perspective to show the impact of these vehicles on a corridor. The traffic simulation software, VISSIM, modified by implementing an external driver model to govern the interactions between Legacy Vehicles (LV), AV, and CAV on a basic and merging highway segment as well as a model of the Interstate 95 corridor south of Richmond, Virginia. From the analysis, this research revealed that the AV and CAV could increase highway capacity significantly. Even with a small portion of AV or CAV, the roadway capacity increased. On I-95, CAV performed better than AV because of Cooperative Adaptive Cruise Control (CACC) and platooning due to CAV's ability to coordinate movement through communication; however, in weaving segments, CAV underperformed AV. This result indicates that the CAV algorithms would need to be flexible in order to maintain flow in areas with weaving sections. Lastly, diverse operational conditions, such as different heavy vehicle market penetration and different aggressiveness were examined to support traffic operators transition to the introduction of AV and CAV. Based on the analysis, the study concludes that the different aggressiveness could mitigate congestion in all cases if the proper aggressiveness level is selected considering the current traffic condition. Overall, the dissertation provides guidance to researchers, traffic operators, and lawmakers to model, simulate, and evaluate AV and CAV on highways.

International Telemetering Conference Proceedings / November 04-07, 1991 / Riviera Hotel and Convention Center, Las Vegas, Nevada / The Telemetry Test Station has been developed at the Digital Systems Division, ISRO Satellite Centre, to test House Keeping Telemetry Packages which will be flown onboard satellites. The main feature of the Test Staion is its configurability, since it is intended to be used with different types of (low bit rate) telemetry packages. Other features include automation of test procedure, and reduction in testing time/increase in repeatability due to minimisation of manual interaction. Since the test station comprises GPIB controlled equipment, hardware and software, thf configurability should be built in at all levels and stages, from design to implementation. Thus since the specification is subject to change, the configuration for structure of the system is traosferred from the designer to the user. This results in a large part of the system being devoted to user interface design, since the computer which is an integral part of the setup must be ‘invisible’ to the user. Due to specialised requirements the user and the system are treated at peer level i.e, at any time during the entire test session, the user can override system process and verify/correct it and equally, the system must also verify/correct user input especially with regard to critical test procedures. The test tession itself (after configuration) is divided into three equally important sections: preprocessing, test and analysis. All the data required during the test run should be made ready before the actual test. Since it has been found by experience that this is not always convenient, the preprocessing software is integrated in to the test session so that the user can perform this at any time. Similarly, the results of the test can also be analysed immediately or even during the test to improve subsequent procedures. This paper describes the prototype telemetry test station which has been built and tested over the past two years. This performance has been satisfactory. The system integration features and design problems and solution are high lighted.

ITC/USA 2011 Conference Proceedings / The Forty-Seventh Annual International Telemetering Conference and Technical Exhibition / October 24-27, 2011 / Bally's Las Vegas, Las Vegas, Nevada / An automated missile testing environment, reliant on telemetry data, demands automated control of telemetry devices. Software reuse across many missile products (Wikipedia)i and different lab environments requires a software control product that has a simple interface and an ease of modification across different telemetry device vendors. This paper describes a software application that integrates telemetry control/status into automated test and provides a simplified GUI to expedite manual testing. Results from this application show telemetry overhead time reduced by 74%, with a rapid payback on our investment of less than six months.

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