Exception Handling Research Articles

Mix Testing: Specifying and Testing ABI Compatibility of C/C++ Atomics Implementations

The correctness of complex software depends on the correctness of both the source code and the compilers that generate corresponding binary code. Compilers must do more than preserve the semantics of a single source file: they must ensure that generated binaries can be composed with other binaries to form a final executable. The compatibility of composition is ensured using an Application Binary Interface (ABI), which specifies details of calling conventions, exception handling, and so on. Unfortunately, there are no official ABIs for concurrent programs, so different atomics mappings, although correct in isolation, may induce bugs when composed. Indeed, today, mixing binaries generated by different compilers can lead to an erroneous resulting binary. We present mix testing : a new technique designed to find compiler bugs when the instructions of a C/C++ test are separately compiled for multiple compatible architectures and then mixed together. We define a class of compiler bugs, coined mixing bugs , that arise when parts of a program are compiled separately using different mappings from C/C++ atomic operations to assembly sequences. To demonstrate the generality of mix testing, we have designed and implemented a tool, atomic-mixer, which we have used: (a) to reproduce one existing non-mixing bug that state-of-the-art concurrency testing tools are limited to being able to find (showing that atomic-mixer at least meets the capabilities of these tools), and (b) to find four previously-unknown mixing bugs in LLVM and GCC, and one prospective mixing bug in mappings proposed for the Java Virtual Machine. Lastly, we have worked with engineers at Arm to specify, for the first time, an atomics ABI for Armv8, and have used atomic-mixer to validate the LLVM and GCC compilers against it.

Exploring the Human-Centric Interaction Paradigm: Augmented Reality-Assisted Head-Up Display Design for Collaborative Human-Machine Interface in Cockpit

Human-cybernetic interfaces (HCI) focuses on the integration and synergy of human-centric design, human factors (HFs) and economics, and human–machine interaction (HMI). The scrutiny of single pilot operations (SPO) approval from civil aviation authorities (CAAs) is subject to the aviation safety and pilot capability during exceptional handling and flight emergency. Airliners advocate the possibility from dual pilot operations (DPO) to SPO because of the financial considerations and captain shortage in the post-pandemic era. One could expect that SPO can only realise when reduced crew operations initiative is proven to be safe and airworthy. Public concerns pilot mental workload and potentially low situational awareness (SA) when handling overwhelmed multi-source information from the HMI in a cockpit, leading to degraded skills and flying performance. Advanced head up display (HUD) design, an integrated transparent display, can assist pilots in maintaining their optimal performance when SPO exercised. In this study, we are interested to design a SPO-favoured cockpit design with HUD and investigate the potential of integrating augmented reality (AR) and HUD in SPO in flight operations. An experiment involving 21 pilots was conducted to assess the effectiveness of AR-HUD on SA and workload in DPO, SPO, and SPO with AR-HUD scenarios. The Situation Awareness Present Assessment Method (SPAM) and a self-rated workload scale were used to evaluate SA and workload levels. Eye-tracking data was also collected to analyse behavioural performance. Results indicated that the AR-HUD scenario achieved optimal workload and SA levels and demonstrated superior performance in handling emergencies. Eye-tracking data revealed that AR-HUD facilitated a more equitable distribution of gaze between instruments and external view. In conclusion, the integration of AR in cockpit design introduces a human-centric interaction paradigm, contributing to aviation safety, SPO implementation and adaptive HMI design.

Carving out Control Code: Automated Identification of Control Software in Autopilot Systems

Cyber-physical systems interact with the world through software controlling physical effectors. Carefully designed controllers, implemented as safety-critical control software, also interact with other parts of the software suite, and may be difficult to separate, verify, or maintain. Moreover, some software changes, not intended to impact control system performance, do change controller response through a variety of means including interaction with external libraries or unmodeled changes only existing in the cyber system (e.g., exception handling). As a result, identifying safety-critical control software, its boundaries with other embedded software in the system, and the way in which control software evolves could help developers isolate, test, and verify control implementation, and improve control software development. In this work we present an automated technique, based on a novel application of machine learning, to detect commits related to control software, its changes, and how the control software evolves. We leverage messages from developers (e.g., commit comments), and code changes themselves to understand how control software is refined, extended, and adapted over time. We examine three distinct, popular, real-world, safety-critical autopilots – ArduPilot, Paparazzi UAV, and LibrePilot to test our method demonstrating an effective detection rate of 0.95 for control-related code changes.

Optimization of White Box Testing by Utilizing Branching and Repeating Structures in Java Programs Using Base Path

Software testing is a process created to detect anomalies in the operation of a program or system in order to achieve the expected results. White box testing is a software testing method that tests the internal structure, design and program code. This research aims to produce an optimization method for white box testing in Java programs by utilizing branching and repetition structures using the basis path method, as well as analyzing the effectiveness of the proposed method in generating test cases. The Java program tested in this research includes input function calls, loops, branching, and exception handling. Test case design is carried out by applying the basis path method to achieve comprehensive coverage. The test results show that the base path method is able to produce effective test cases for testing control structures without redundancy. Test case design is assisted by flowgraph and matrix graph modeling. It is hoped that this research can contribute to the optimization of white box testing techniques.

Responsible composition and optimization of integration processes under correctness preserving guarantees

Enterprise Application Integration deals with the problem of connecting heterogeneous applications, and is the centerpiece of current on-premise, cloud and device integration scenarios. For integration scenarios, structurally correct composition of patterns into processes and improvements of integration processes are crucial. In order to achieve this, we formalize compositions of integration patterns based on their characteristics, and describe optimization strategies that help to reduce the model complexity, and improve the process execution efficiency using design time techniques. Using the formalism of timed DB-nets – a refinement of Petri nets – we model integration logic features such as control- and data flow, transactional data storage, compensation and exception handling, and time aspects that are present in reoccurring solutions as separate integration patterns. We then propose a realization of optimization strategies using graph rewriting, and prove that the optimizations we consider preserve both structural and functional correctness. We evaluate the improvements on a real-world catalog of pattern compositions, containing over 900 integration processes, and illustrate the correctness properties in case studies based on two of these processes.

Beyond Surface Beauty: Exploring the Intricate Histopathological Finding in Intrinsic Dentin Discoloration

Dental stains are pigmented deposits that can be intrinsic or extrinsic in origin and are seen on the surface of the teeth. Discoloration of teeth can be due to developmental defects, traumatic injuries, or the intake of several medications. Extrinsic stains create discoloration outside the tooth surface and lay on the surface or in the acquired pellicle, whereas stains within dentin or intrinsic discoloration sometimes come from pulpal or systemic origin. To plan a specific treatment approach and its associated result, it is important to identify the etiologic cause that is creating the stain, in an attempt to provide esthetic treatment for the same. This case report describes the successful management of intrinsic staining of anterior teeth in a 10-year-old girl. The treatment plan included esthetic rehabilitation using composite veneer. The fluoride-releasing composite used provided an acceptable color match and exceptional handling properties and was relatively easy to maintain with its antiplaque effect. This case also represents a unique histopathological finding from ground sections of a retained extracted deciduous tooth.

Overview of advances in ASDEX Upgrade plasma control to support critical physics research for ITER and beyond

The successful operation of fusion reactors requires plasma scenarios with good core confinement and acceptable first wall heat loads that are stable and robust to external perturbations. This poses both physical and technological challenges. One of the technologies that addresses these challenges is a complex feedback control system that supports advances in physical understanding and helps to ensure stable operating conditions. The operation of marginally stable plasmas often leads to off-normal events (such as disruptions) and feedback control can prevent these to some extent. This contribution gives an overview of the main results of the development and operation of the feedback control algorithms on ASDEX Upgrade (AUG). Fueling actuators, using a combination of gas valves and pellet injection, can simultaneously control neutral density of the divertor and the density of the plasma core above the Greenwald limit. Impurity injection is employed to control the position of the X-point radiator, allowing the creation of an ELM-suppressed H-mode with high radiation fraction. Heating actuators are used to control the plasma energy content, which supports advanced tokamak experiments and enables stable I-mode operation, and the electron temperature control, which supports turbulence studies. In control technology, AUG has pioneered the use of virtual actuators, which allow effective use of the limited number of heating actuators, adaptive control policies, and exception handling. Such technologies will also be used in ITER. Advanced nonlinear state observers (RAPTOR, RAPDENS) and codes to evaluate the power deposition properties (RABBIT, TORBEAM) are available for routine use in the AUG feedback controllers. Extensive use of the AUG discharge control system further enhances the research capabilities of this machine.

Revisiting Grudin’s eight challenges for developers of groupware technologies 30 years later

Abstract In 1994, Jonathan Grudin wrote his famous paper Eight Challenges for Groupware Developers; The question is whether these challenges still persist, or have we moved on here 30 years later? We revisit the challenges empirically through ethnographic observations in two companies examining their work practices, organizational structure, and cooperative setups concerning their use of groupware technologies. Today, groupware is seamlessly integrated into organizations, considered essential infrastructure that becomes part of the daily work routine. Contextualizing the original challenges proposed by Grudin, we categorize them into cooperative challenges, social challenges, and organizational challenges, and refine their phrasings to reflect present and future considerations faced by developers of groupware technologies. While the main arguments of the social and organizational challenges remain consistent, we rephrase the cooperative challenges as emergent exception handling and exaggerated accessibility to reflect the emerging characteristics associated with the ubiquity and seamless integration of groupware.

Seven insecure academic conditions for students as a basis for implementing teacher professional learning

Student academic performance as a measure of future success. Students who can develop academic performance in the classroom and outside the school are a big part of the success process. However, some children have academic insecurity problems that impact academic performance and may influence future success. Professional teachers must be able to analyze students in this condition. This research aims to analyze students' educational insecurity conditions using seven indicators—a quantitative study with a survey with random sampling on 521 students at school. The academic insecurity scale distributed to students randomly was analyzed through percentages and standard deviations with four categories: very high, high, low, and very low. The results of the research show that the average student's insecure academic condition is in a standard category on seven indicators: students do not want to get out of their comfort zone, like to compare themselves with other individuals, look down on themselves, have to get praise and recognition from other individuals, avoid interaction with the surrounding environment, experiencing failure, and lack of gratitude. Then, 54% of students have an insecure academic condition in the low category and 14% in the shallow category. Academic insecurity is also in the high category at 29% and very high at 3%. The high and very high categories require significant attention from schools and teachers at schools with exceptional handling. Professional teachers must be able to implement fair and enjoyable learning to prevent gaps who experience academic insecurity because they do not receive proper appreciation in the teaching.

Disruption avoidance and investigation of the H-Mode density limit in ASDEX Upgrade

In recent years a strong effort has been made to investigate disruption avoidance schemes in order to aid the development of integrated operational scenarios for ITER. Within the EUROfusion programme the disruptive H-mode density limit (HDL) has been studied on the WPTE (Work Package Tokamak Exploitation) devices ASDEX Upgrade, TCV and JET. Advanced real-time control coupled with improved real-time diagnostics has enabled the routine disruption avoidance of the HDL. This allowed the systematic study of the influence of various plasma parameters on the onset and behavior of the HDL in regimes not easily accessible otherwise. The upper triangularity δtop is found to have a significant influence on the x-point radiator (XPR), which plays a major role for the evolution of the disruptive HDL. At high δtop the gas flow rate at which the onset of the XPR occurs is strongly reduced compared to low δtop . The reduction of δtop has proven to be an effective actuator for the HDL disruption avoidance on ASDEX Upgrade for highly shaped scenarios ( δtop>0.25 ). It is observed that the occurrence of the XPR and the H–L transition at the density limit are two separate events, the order of which depends on the applied auxiliary heating power. At sufficiently high heating power the XPR occurs before the H–L transition. Impurity seeding, used for divertor detachment, influences the onset and the dynamics of the XPR and the behavior of the HDL. The stable existence of the XPR, which is thought to be a requirement for detachment control in future devices, has also been observed without impurity seeding. The implementation of a robust and sustainable operational scenario, e.g. for ITER, requires the combination of continuous control and exception handling. For each disruption path the appropriate observers and actuators have to be validated in present devices. Automation of the dynamic pulse schedule has proven successful to scan the operational space of the HDL without disruption. Applying such a technique to ITER could reduce the machine risk induced by disruptions during commissioning. The methodology to develop physics-based observers, which indicate the entry into a disruption path well in time, and applying the appropriate action before the discharge becomes unstable has proven successful.

EDSR: Empowering super-resolution algorithms with high-quality DIV2K images

Remarkable strides have been made in Enhanced-resolution image reconstruction in recent times. In this research, we propose EDSR, a novel algorithm leveraging high-quality DIV2K images to enhance super-resolution algorithms’ performance. Our approach addresses challenges associated with capturing and reconstructing fine details and textures in low-resolution images. The training process utilizes a deep neural network fed with the extensive DIV2K dataset, comprising meticulously selected high-resolution images for super-resolution tasks. The network learns from these high-quality images to improve super-resolved outputs’ accuracy and fidelity. Extensive experimentation evaluates the effectiveness of the EDSR algorithm in achieving superior results. Experimental outcomes exhibit the remarkable progress made by EDSR compared to other leading super-resolution algorithms. The mean PSNR values obtained using EDSR on various test datasets indicate substantial improvement in image quality. The SSIM scores show enhanced preservation of fine details and textures. In the Nature category, the EDSR algorithm exhibits impressive performance, achieving a mean Peak Signal-to-Noise Ratio (PSNR) of 35.92 dB and a Structural Similarity Index (SSIM) of 0.9321. When analyzing Portrait images, the algorithm consistently maintains high quality, delivering a mean PSNR of 34.17 dB and an SSIM of 0.9125. For Cityscape images, EDSR showcases excellent capabilities with a mean PSNR of 36.05 dB and an SSIM of 0.9382, highlighting its exceptional handling in this category. Lastly, in the Still Life category, the algorithm demonstrates competence, achieving a mean PSNR of 33.79 dB and an SSIM of 0.9024. In conclusion, the proposed EDSR algorithm empowers super-resolution algorithms by leveraging high-quality DIV2K images. The empirical findings validate that EDSR is highly efficient in enhancing image quality and preserving fine details.

Explore the role and emphasis of K-Means, Decision Tree and Distance Based algorithms in data exception detection

K-Means, Decision Tree and Distance-Based algorithms are 3 important ways of classifying data. These three algorithms have different methods and focus on data classification. Therefore, they are always applied into different scenarios. K-Means algorithm is to divide three-dimensional data or two-dimensional data into several clusters to facilitate subsequent data processing and analysis. Decision Tree is based on the “tree” structure to make decisions. It is an important classification and regression method in data mining technology. It is a prediction analysis model expressed in the form of tree structure (including binary tree and multi tree). When it comes to the Distance-Based algorithm, it is a common anomaly detection method applicable to various data domains. It defines outliers based on the nearest neighbor distance. The purpose of this paper is to explore the kernel of three anomaly detection algorithms through an example of data anomaly detection. Therefore, in this paper, all three algorithms’ commonalities and differences will be discussed and illustrated through a case of data exception handling.

Exception Handling in Logic Programming

One problem on logic programming is to express exception handling. We argue that this problem can be solved by adopting linear logic and prioritized-choice disjunctive goal formulas (PCD) of the form G G 0 *1 ⊕ where G0, G1 are goals. These goals have the following intended semantics: sequentially choose the first true goal GI and execute GI where i (= 0 or 1), discarding the rest if any.

Driving Decision Making of Autonomous Vehicle According to Queensland Overtaking Traffic Rules

Improving the safety of autonomous vehicles (AVs) by making driving decisions in accordance with traffic rules is a complex task. Traffic rules are often expressed in a way that allows for interpretation and exceptions, making it difficult for AVs to follow them. This paper proposes a novel methodology for driving decision making in AVs based on defeasible deontic logic (DDL). We use DDL to formalize traffic rules and facilitate automated reasoning, allowing for the effective handling of rule exceptions and the resolution of vague terms in rules. To supplement the information provided by traffic rules, we incorporate an ontology for AV driving behaviour and environment information. By applying automated reasoning to formalized traffic rules and ontology-based AV driving information, our methodology enables AVs to make driving decisions in accordance with traffic rules. We present a case study focussing on the overtaking traffic rule to illustrate the usefulness of our methodology. Our evaluation demonstrates the effectiveness of the proposed driving decision-making methodology, highlighting its potential to improve the safety of AVs on the road.

A mixed method study of DevOps challenges

DevOps practices combine software development and IT (Information Technology) operations. The continuous needs for rapid but quality software development requires the adoption of high-quality DevOps tools. There is a growing number of DevOps related posts in popular online developer forum Stack Overflow (SO). While previous research analyzed SO posts related to build/release engineering, we are aware of no research that specifically focused on DevOps related discussions. This paper aims to learn the challenges developers face while using the currently available DevOps tools and techniques along with the organizational challenges in DevOps practices. We conduct an empirical study by applying topic modeling on 174K SO posts that contain DevOps discussions. We then validate and extend the empirical study findings with a survey of 21 professional DevOps practitioners. We find that: (1) There are 23 DevOps topics grouped into four categories: Cloud & CI/CD Tools, Infrastructure as Code, Container & Orchestration, and Quality Assurance. (2) The topic category ‘Cloud & CI/CD Tools’ contains the highest number of topics (10) which cover 48.6% of all questions in our dataset, followed by the category Infrastructure as Code (28.9%). (3) The file management is the most popular topic followed by Jenkins Pipeline, while infrastructural Exception Handling and Jenkins Distributed Architecture are the most difficult topics (with least accepted answers). (4) In the survey, developers mention that it requires hands-on experience before current DevOps tools can be considered easy. They raised the needs for better documentation and learning resources to learn the rapidly changing DevOps tools and techniques. Practitioners also emphasized on the formal training approach by the organizations for DevOps skill development. Architects and managers can use the findings of this research to adopt appropriate DevOps technologies, and organizations can design tool or process specific DevOps training programs.

The Support of MISRA C++ Analyzer for Reliability of Embedded Systems

Cyber-Physical Systems (CPS) are increasingly used in many complex applications, such as autonomous delivery drones, the automotive CPS design, power grid control systems, and medical robotics. However, existing programming languages lack certain design patterns for CPS designs, including temporal semantics and concurrency models. Future research directions may involve programming language extensions to support CPS designs. On the other hand, JSF++, MISRA, and MISRA C++ are providing specifications intended to increase the reliability of safety-critical systems. This article also describes the development of rule checkers based on the MISRA C++ specification using the Clang open-source tool, which allows for the annotation of code and the easy extension of the MISRA C++ specification to other programming languages and systems. This is potentially useful for future CPS language research extensions to work with reliability software specifications using the Clang tool. Experiments were performed using key C++ benchmarks to validate our method in comparison with the well-known Coverity commercial tool. We illustrate key rules related to class, inheritance, template, overloading, and exception handling. Open-source benchmarks that violate the rules detected by our checkers are also illustrated. A random graph generator is further used to generate diamond case with multiple inheritance testdata for our software validations. The experimental results demonstrate that our method can provide information that is more detailed than that obtained using Coverity for nine open-source C++ benchmarks. Since the Clang tool is widely used, it will further allow developers to annotate their own extensions.

Implementing Backjumping by Means of Exception Handling

AbstractWe discuss how to implement backjumping (or intelligent backtracking) in Prolog by using the built-ins throw/1 and catch/3. We show that it is impossible in a general case, contrary to a claim that “backjumping is exception handling." We provide two solutions. One works for binary programs; in a general case it imposes a restriction on where backjumping may originate. The other restricts the class of backjump targets. We also discuss implementing backjumping by using backtracking and the Prolog database. Additionally, we explain the semantics of Prolog exception handling in the presence of coroutining.

Constructing exception handling chains for testing Java virtual machine implementations

AbstractThe Java virtual machine (JVM) is the cornerstone of the Java platforms. A JVM's exception handling implementation interrupts, when the objective application encounters an exception (or an error), the normal execution of the application and performs specific handling tasks. However, little research has been done in systematically validating JVMs' exception handling implementations—test programs or even applications need to be carefully designed for throwing/catching exceptions at runtime; a JVM's exception handling implementation is also complicated, making it challenging to design tests for testing all of its functionalities. Inspired by the recent success of fuzz testing of compilers and JVM implementations, we introduce EHCBuilder, the first technique for fuzzing JVMs' exception handling implementations. The key idea is to construct exception handling chains, each of which abstracts a program's execution into a sequence of exception throwings, catchings, and/or handlings. A classfile seed can then be mutated into test programs with diverse exception handling chains, enabling (1) exceptions to be continuously thrown and caught at runtime, and (2) JVMs' exception handling implementations to be much more thoroughly tested. We have implemented EHCBuilder and evaluated EHCBuilder on popular JVM implementations including OpenJDK's HotSpot, Eclipse's OpenJ9, Azul's Zulu, and Oracle's GraalVM. Our results show that EHCBuilder can generate programs with very intricate exception handling chains and reveal differences among JVMs' exception handling implementations: Up to thousands of lines of source code in HotSpot's exception handling implementation are covered more than the original benchmarks; during 39 K iterations, EHCBuilder generates exception handling chains of different lengths, revealing 258 runtime differences. We classify the differences into four categories, and reveal a fast throw issue confirmed by HotSpot developers and another initCause issue confirmed by the OpenJ9 community.

Computationally Efficient Simulation of Calcium Signaling in Cardiomyocytes.

The objective of this paper is to develop a computationally efficient simulation model of Calcium signalling in cardiomyocytes. The model considered here consists of more than two million stiff, nonlinear, and stochastic systems, each of which is composed of 62 state equations. The size of the model, combined with the broad numerical scale, non-continuous stochastic state-transitions, and underlying physiological constraints, presents a significant implementation challenge. The method involves development of specialised algorithms for parallelisation, which include fully-implicit Runge-Kutta integration with both L-stability and step-size control, Newton's root finding method with exception handling, and Conjugate Residual Squared for solving linear systems not of full-rank within available computational precision. Parallelisation of the problem across the systems is employed to allow for practical scaling with computing resources. The results produce sparks and waves akin to those observed in actual laboratory experiments within an acceptable timeframe. Performance measures of the simulation model with respect to accuracy and computation time are also given. The conclusion is that the methodologies utilised in this work are can simulate cardiomyocyte's calcium signalling in a computationally efficient manner with the results produced replicating those in the laboratory. The significance of this paper is that computational models such as the one developed here provide a way to simulate and understand the complex biological interactions operating in organisms. Accurate simulations are extremely computationally intensive and this pursuit is considered as the grand challenge for computational science into the 21st century.

A case study of the real-time framework for the implementation of the ITER plasma control system

ITER CODAC is in the process of developing a tailored software solution to carry out necessary control functions for tokamak operation. CODAC has successfully completed the final review of the implementation of the ITER Plasma Control System (PCS) for first plasma (FP), and formally commenced its production in accordance with the conversion mechanism of the Real-Time Framework (RTF) software suite. Rich functionality of RTF built-ins and its flexibility of reconfigurable applications facilitates the development and deployment of complex real-time applications such as commonly found within PCS and the ITER diagnostics.In the practical application of the framework, CODAC has prototyped PCS architecture components to verify how actual operation complies with the intended design. Prototyping initiates CODAC preparation for system validation and verification, and its commissioning. Agile production is based on the model presented in the PCS Simulation Platform (PCSSP). Several fundamental functions such as exception handling, quality tag controlling, and signal watchdog functionality have been implemented and continue to evolve. CODAC demonstrated a mechanism by which individual function models coordinate and cooperate with each other to achieve desired higher-level functions. Operation of prototype and real-life experiments verified the application is compliant with the design input and even adaptable and extendable in various system attributes.This paper will introduce the PCS prototyping and its execution as well as integrated operation function in the ITER environment.