AutoLog: A Log Sequence Synthesis Framework for Anomaly Detection

The rapid progress of modern computing systems has led to a growing interest in informative run-time logs. Various log-based anomaly detection techniques have been proposed to ensure software reliability. However, their implementation in the industry has been limited due to the lack of high-quality public log resources as training datasets. While some log datasets are available for anomaly detection, they suffer from limitations in (1) comprehensiveness of log events; (2) scalability over diverse systems; and (3) flexibility of log utility. To address these limitations, we propose AutoLog, the first automated log generation methodology for anomaly detection. AutoLog uses program analysis to generate run-time log sequences without actually running the system. AutoLog starts with probing comprehensive logging statements associated with the call graphs of an application. Then, it constructs execution graphs for each method after pruning the call graphs to find log-related execution paths in a scalable manner. Finally, AutoLog propagates the anomaly label to each acquired execution path based on human knowledge. It generates flexible log sequences by walking along the log execution paths with controllable parameters. Experiments on 50 popular Java projects show that AutoLog acquires significantly more (9x-58x) log events than existing log datasets from the same system, and generates log messages much faster (15x) with a single machine than existing passive data collection approaches. We hope AutoLog can facilitate the benchmarking and adoption of automated log analysis techniques.Comment: The paper has been accepted by ASE 2023 (Research Track

Experimental analysis of computer system dependability

This paper reviews an area which has evolved over the past 15 years: experimental analysis of computer system dependability. Methodologies and advances are discussed for three basic approaches used in the area: simulated fault injection, physical fault injection, and measurement-based analysis. The three approaches are suited, respectively, to dependability evaluation in the three phases of a system's life: design phase, prototype phase, and operational phase. Before the discussion of these phases, several statistical techniques used in the area are introduced. For each phase, a classification of research methods or study topics is outlined, followed by discussion of these methods or topics as well as representative studies. The statistical techniques introduced include the estimation of parameters and confidence intervals, probability distribution characterization, and several multivariate analysis methods. Importance sampling, a statistical technique used to accelerate Monte Carlo simulation, is also introduced. The discussion of simulated fault injection covers electrical-level, logic-level, and function-level fault injection methods as well as representative simulation environments such as FOCUS and DEPEND. The discussion of physical fault injection covers hardware, software, and radiation fault injection methods as well as several software and hybrid tools including FIAT, FERARI, HYBRID, and FINE. The discussion of measurement-based analysis covers measurement and data processing techniques, basic error characterization, dependency analysis, Markov reward modeling, software-dependability, and fault diagnosis. The discussion involves several important issues studies in the area, including fault models, fast simulation techniques, workload/failure dependency, correlated failures, and software fault tolerance

Supporting Evolution and Maintenance of android Apps

Mobile developers and testers face a number of emerging challenges. These include rapid platform evolution and API instability; issues in bug reporting and reproduction involving complex multitouch gestures; platform fragmentation; the impact of reviews and ratings on the success of their apps; management of crowd-sourced requirements; continuous pressure from the market for frequent releases; lack of effective and usable testing tools; and limited computational resources for handheld devices. Traditional and contemporary methods in software evolution and maintenance were not designed for these types of challenges; therefore, a set of studies and a new toolbox of techniques for mobile development are required to analyze current challenges and propose new solutions. This dissertation presents a set of empirical studies, as well as solutions for some of the key challenges when evolving and maintaining android apps. In particular, we analyzed key challenges experienced by practitioners and open issues in the mobile development community such as (i) android API instability, (ii) performance optimizations, (iii) automatic GUI testing, and (iv) energy consumption. When carrying out the studies, we relied on qualitative and quantitative analyses to understand the phenomena on a large scale by considering evidence extracted from software repositories and the opinions of open-source mobile developers. From the empirical studies, we identified that dynamic analysis is a relevant method for several evolution and maintenance tasks, in particular, because of the need of practitioners to execute/validate the apps on a diverse set of platforms (i.e., device and OS) and under pressure for continuous delivery. Therefore, we designed and implemented an extensible infrastructure that enables large-scale automatic execution of android apps to support different evolution and maintenance tasks (e.g., testing and energy optimization). In addition to the infrastructure we present a taxonomy of issues, single solutions to the issues, and guidelines to enable large execution of android apps. Finally, we devised novel approaches aimed at supporting testing and energy optimization of mobile apps (two key challenges in evolution and maintenance of android apps). First, we propose a novel hybrid approach for automatic GUI-based testing of apps that is able to generate (un)natural test sequences by mining real applications usages and learning statistical models that represent the GUI interactions. In addition, we propose a multi-objective approach for optimizing the energy consumption of GUIs in android apps that is able to generate visually appealing color compositions, while reducing the energy consumption and keeping a design concept close to the original

Studying and Leveraging User-Provided Logs in Bug Reports for Debugging Assistance

Bug reports provide important information for developers to debug user-reported issues. During the debugging process, developers need to study the bug report and examine user-provided logs to understand the system execution paths that lead to the problem. Prior studies on bug reports also found that such user-provided often contain valuable debugging information to developers. In this thesis, we conduct a tool-assisted study to study user-provided logs in bug reports. Our goal is to study any challenges that developers may encounter when analyzing the logs, and how many additional buggy classes can the logs help to identify. In particular, we study both system-generated logs and exception stack traces. Our approach tries to simulate developers' debugging process by 1) identifying the location in the source code where the logs were generated, 2) re-constructing execution paths by finding the call paths are can be traced back from the logs, and 3) studying the additional buggy classes that the re-constructed execution paths identify. We conduct our study on eight large-scale open-source systems with a total of 1,145 bug reports that contain logs. We find that the execution paths cannot be constructed in 32% of the studied bug reports, since many logs can no longer be found in the source code due to code evolution, and users often provide logs that are generated by third-party frameworks. In the rest of the cases, the re-constructed execution paths can identify 15% additional buggy classes in 41% of the bug reports. Through a comprehensive manual study, we find that the main reasons that the re-constructed execution paths fail to identify additional buggy classes are that reporters often only attach logs that describe the unexpected behavior (e.g., stack traces) without additional logs to illustrate the system execution. In summary, this thesis highlights both the challenges and potentials of using user-provided logs to assist developers with debugging. It also revealed common issues with user-provided logs in bug reports, and provided suggestions for future research

Process of designing robust, dependable, safe and secure software for medical devices: Point of care testing device as a case study

This article has been made available through the Brunel Open Access Publishing Fund.Copyright © 2013 Sivanesan Tulasidas et al. This paper presents a holistic methodology for the design of medical device software, which encompasses of a new way of eliciting requirements, system design process, security design guideline, cloud architecture design, combinatorial testing process and agile project management. The paper uses point of care diagnostics as a case study where the software and hardware must be robust, reliable to provide accurate diagnosis of diseases. As software and software intensive systems are becoming increasingly complex, the impact of failures can lead to significant property damage, or damage to the environment. Within the medical diagnostic device software domain such failures can result in misdiagnosis leading to clinical complications and in some cases death. Software faults can arise due to the interaction among the software, the hardware, third party software and the operating environment. Unanticipated environmental changes and latent coding errors lead to operation faults despite of the fact that usually a significant effort has been expended in the design, verification and validation of the software system. It is becoming increasingly more apparent that one needs to adopt different approaches, which will guarantee that a complex software system meets all safety, security, and reliability requirements, in addition to complying with standards such as IEC 62304. There are many initiatives taken to develop safety and security critical systems, at different development phases and in different contexts, ranging from infrastructure design to device design. Different approaches are implemented to design error free software for safety critical systems. By adopting the strategies and processes presented in this paper one can overcome the challenges in developing error free software for medical devices (or safety critical systems).Brunel Open Access Publishing Fund

Problems and Solutions in Mobile Application Testing

Mobiilirakenduste testimise alaste teadusartiklite arv on viimastel aastatel visalt suurenenud. Samas testivad vähesed mobiilirakendustega tegelevad teadlased oma oletusi ja lahendusi firmades. Selle lõputöö eesmärgiks on pakkuda ülevaade teaduskirjanduses mainitud mobiilirakenduste testimisega seotud probleemidest ja potentsiaalsetest lahendustest ning kõrvutada seda alal igapäevaselt tegutsevate professionaalide arvamusega. Kõigepealt viiakse selle töö käigus läbi teaduskirjanduse uuring probleemide ja potentsiaalsete lahenduste väljaselgitamiseks, misjärel intervjueeritakse kuue mobiilirakenduste testimisega tegeleva firma esindajaid, et välja selgitada, kas kirjelduses esile toodud probleemid on olulised ka tööstuses. Intervjuude tulemusena selgus, et kuigi firmad hindavad probleemide tähtsust väga erinevalt, on siiski olemas mõned võtmeprobleemid, mida peetakse oluliseks nii teaduses kui ka tööstuses. Samas on teaduskirjanduses pakutud lahendused tihti liiga teoreetilised, üldised või vananenud, et firmade esindajatele huvi pakkuda.In recent years the amount of scientific papers published on the topic of mobile applications has significantly increased. However, few researchers test their assumptions and solutions in industry. This thesis aims to provide an overview of what current scientific literature considers problems and potential solutions in mobile application testing, and compare it to opinions of industry professionals. A literature review is performed to extract the list of problems and potential solutions, after which representatives of six Estonian companies involved in the field are interviewed to verify whether the problems and solutions proposed in the literature are relevant for industry. The study reveals that while the relevance of each problem is highly variable from one company to another, there are some key problems that are generally considered vital both by research and industry. However, the solution concepts proposed by scientific literature are often too theoretical, general or outdated to be of much interest to industry professionals