Automatic Software Repair: a Bibliography

This article presents a survey on automatic software repair. Automatic software repair consists of automatically finding a solution to software bugs without human intervention. This article considers all kinds of repairs. First, it discusses behavioral repair where test suites, contracts, models, and crashing inputs are taken as oracle. Second, it discusses state repair, also known as runtime repair or runtime recovery, with techniques such as checkpoint and restart, reconfiguration, and invariant restoration. The uniqueness of this article is that it spans the research communities that contribute to this body of knowledge: software engineering, dependability, operating systems, programming languages, and security. It provides a novel and structured overview of the diversity of bug oracles and repair operators used in the literature

Evaluation of the HARDMAN comparability methodology for manpower, personnel and training

The methodology evaluation and recommendation are part of an effort to improve Hardware versus Manpower (HARDMAN) methodology for projecting manpower, personnel, and training (MPT) to support new acquisition. Several different validity tests are employed to evaluate the methodology. The methodology conforms fairly well with both the MPT user needs and other accepted manpower modeling techniques. Audits of three completed HARDMAN applications reveal only a small number of potential problem areas compared to the total number of issues investigated. The reliability study results conform well with the problem areas uncovered through the audits. The results of the accuracy studies suggest that the manpower life-cycle cost component is only marginally sensitive to changes in other related cost variables. Even with some minor problems, the methodology seem sound and has good near term utility to the Army. Recommendations are provided to firm up the problem areas revealed through the evaluation

KYTC Maintenance Field Operations Guide Supplement

The Kentucky Transportation Cabinet (KYTC) is tasked with managing an asset portfolio that includes over 27,500 miles of roadway and 9,000 bridges. Keeping these assets in sound condition demands significant effort from KYTC’s Division of Maintenance, which includes activities ranging from mowing and litter pickup to cleaning out culverts and performing emergency roadway work. Despite the immense responsibilities shouldered by Maintenance personnel, until this project the Cabinet’s 12 districts lacked a systematic method for capturing and recording maintenance activities. Through a series of workshops held in each KYTC’s district with Section Engineer and Maintenance Supervisors, researchers at the Kentucky Transportation Center (KTC) facilitated efforts to inventory routine maintenance activities, document how frequently each activity is done, and capture the ways in which maintenance functions are adjusted in response to special projects (which generally receive priority over general maintenance functions). Key products of this research include a Statewide Maintenance Calendar, which defines — based on a combination of stakeholder feedback and statistical analysis — optimal time intervals for undertaking key maintenance activities, as well as district-specific maintenance calendars. Having recourse to these calendars will help district staff more efficiently plan, schedule, and coordinate maintenance functions

Dagstuhl Reports : Volume 1, Issue 2, February 2011

Online Privacy: Towards Informational Self-Determination on the Internet (Dagstuhl Perspectives Workshop 11061) : Simone Fischer-Hübner, Chris Hoofnagle, Kai Rannenberg, Michael Waidner, Ioannis Krontiris and Michael Marhöfer Self-Repairing Programs (Dagstuhl Seminar 11062) : Mauro Pezzé, Martin C. Rinard, Westley Weimer and Andreas Zeller Theory and Applications of Graph Searching Problems (Dagstuhl Seminar 11071) : Fedor V. Fomin, Pierre Fraigniaud, Stephan Kreutzer and Dimitrios M. Thilikos Combinatorial and Algorithmic Aspects of Sequence Processing (Dagstuhl Seminar 11081) : Maxime Crochemore, Lila Kari, Mehryar Mohri and Dirk Nowotka Packing and Scheduling Algorithms for Information and Communication Services (Dagstuhl Seminar 11091) Klaus Jansen, Claire Mathieu, Hadas Shachnai and Neal E. Youn

Oracle-Guided Design and Analysis of Learning-Based Cyber-Physical Systems

We are in world where autonomous systems, such as self-driving cars, surgical robots, robotic manipulators are becoming a reality. Such systems are considered \textit{safety-critical} since they interact with humans on a regular basis. Hence, before such systems can be integrated into our day to day life, we need to guarantee their safety. Recent success in machine learning (ML) and artificial intelligence (AI) has led to an increase in their use in real world robotic systems. For example, complex perception modules in self-driving cars and deep reinforcement learning controllers in robotic manipulators. Although powerful, they introduce an additional level of complexity when it comes to the formal analysis of autonomous systems. In this thesis, such systems are designated as Learning-Based Cyber-Physical Systems~(LB-CPS). In this thesis, we take inspiration from the Oracle-Guided Inductive Synthesis~(OGIS) paradigm to develop frameworks which can aid in achieving formal guarantees in different stages of an autonomous system design and analysis pipeline. Furthermore, we show that to guarantee the safety of LB-CPS, the design (synthesis) and analysis (verification) must consider feedback from the other. We consider five important parts of the design and analysis process and show a strong coupling among them, namely (i) Robust Control Synthesis from High Level Safety Specifications; (ii) Diagnosis and Repair of Safety Requirements for Control Synthesis; (iii) Counter-example Guided Data Augmentation for training high-accuracy ML models; (iv) Simulation-Guided Falsification and Verification against Adversarial Environments; and (v) Bridging Model and Real-World Gap. Finally, we introduce a software toolkit \verifai{} for the design and analysis of AI based systems, which was developed to provide a common formal platform to implement design and analysis frameworks for LB-CPS

Investigating the Optimal Management Strategy for a Healthcare Facility Maintenance Program

Reacting to the need to transform and the increasing pressure to outsource all non-core activities, Air Force Material Command Surgeon General discontinued its previous use of full service contracts with original equipment manufacturers and adopted a relatively new maintenance outsourcing strategy: strategic partnering with an equipment management firm. The objective of this study is to create a decision-model for selecting the optimal management strategy for a healthcare organization\u27s facility maintenance program. This study used personal interviews with facility management personnel from MAJCOMs to collect and analyze data. This study offers a re-conceptualized framework for viewing and understanding the various maintenance programs and their interrelationships. Additionally, the study evaluates the strategic fit between maintenance programs and strategic objectives and finally examines the strength of the strategic fit and how it relates to overall customer satisfaction of the maintenance program. The data from the interviews tested the interviewee\u27s relative satisfaction with their programs and analyzed each management program and determined which strategic objectives resulted in satisfaction. This research found that facilities should determine their particular level of risk. Facilities that prefer term vs. whole insurance may be more satisfied with a program that hedges its risk by utilizing multiple OEMs or 3rd party providers. Facilities that desire stable pricing and cost structures and consolidated management would do well to investigate single OEMs or single comprehensive providers