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Traditional Concurrency Control (CC) mechanisms ensure absence of undesired interference in transaction-based systems and enforce isolation. However, CC may introduce unpredictable delays that could lead to breached timeliness, which is unwanted for real-time transactions. To avoid deadline misses, some CC algorithms relax isolation in favor of timeliness, whereas others limit possible interleavings by leveraging real-time constraints and preserve isolation. Selecting an appropriate CC algorithm that can guarantee timeliness at an acceptable level of isolation thus becomes an essential concern for system designers. However, trading-off isolation for timeliness is not easy with existing analysis techniques in database and real-time communities. In this paper, we propose to use model checking of a timed automata model of the transaction system, in order to check the traded-off timeliness and isolation. Our solution provides modularization for the basic transactional constituents, which enables flexible modeling and composition of various candidate CC algorithms, and thus reduces the effort of selecting the appropriate CC algorithm.

Real-time DataBase Management Systems (RTDBMS) have been considered as a promising means to manage data for data-centric automotive systems. During the design of an RTDBMS, one must carefully trade off data consistency and timeliness, in order to achieve an acceptable level of both properties. Previously, we have proposed a design process called DAGGERS to facilitate a systematic customization of transaction models and decision on the run-time mechanisms. In this paper, we evaluate the applicability of DAGGERS via an industrially relevant case study that aims to design the transaction management for an on-board diagnostic system, which should guarantee both timeliness and data consistency under concurrent access. To achieve this, we apply the pattern-based approach of DAGGERS to formalize the transactions, and derive the appropriate isolation level and concurrency control algorithm guided by model checking. We show by simulation that the implementation of our designed system satisfies the desired timeliness and derived isolation, and demonstrate that DAGGERS helps to customize desired real-time transaction management prior to implementation.

Data aggregation processes are essential constituents in many data management applications. Due to their complexity, designing data aggregation processes often demands considerable efforts. A study on the features of data aggregation processes will provide a comprehensive view for the designers and ease the design process. Existing works either propose application-specific aggregation solutions, or focus on particular aspects of aggregation processes such as aggregate functions, hence they do not offer a high-level, generic description. In this paper, we propose a taxonomy of data aggregation processes called DAGGTAX, which builds on the results of an extensive survey within various application domains. Our work focuses on the features of aggregation processes and their implications, especially on the temporal data consistency and the process timeliness. We present our taxonomy as a feature diagram, which is a visual notation with formal semantics. The taxonomy can then serve as the foundation of a design tool that enables designers to build an aggregation process by selecting and composing desired features. Based on the implications of the features, we formulate three design rules that eliminate infeasible feature combinations. We also provide a set of design heuristics that could help designers to decide the appropriate mechanisms for achieving the selected features. 

Data aggregation processes are essential constituents for data management in modern computer systems, such as decision support systems and Internet of Things (IoT) systems. Due to the heterogeneity and real-time constraints in such systems, designing appropriate data aggregation processes often demands considerable effort. A study on the characteristics of data aggregation processes is then desirable, as it provides a comprehensive view of such processes, potentially facilitating their design, as well as the development of tool support to aid designers. In this paper, we propose a taxonomy called DAGGTAX, which is a feature diagram that models the common and variable characteristics of data aggregation processes, with a special focus on the real-time aspect. The taxonomy can serve as the foundation of a design tool, which we also introduce, enabling designers to build an aggregation process by selecting and composing desired features, and to reason about the feasibility of the design. We apply DAGGTAX on industrial case studies, showing that DAGGTAX not only strengthens the understanding, but also facilitates the model-driven design of data aggregation processes. © 2017, Springer International Publishing AG.

Data aggregation processes are essential constituents for data management in modern computer systems, such as decision support systems and Internet of Things (IoT) systems, many with timing constraints. Understanding the common and variable features of data aggregation processes, especially their implications to the timerelated properties, is key to improving the quality of the designed system and reduce design effort. In this paper, we present a survey of data aggregation processes in a variety of application domains from literature.We investigate their common and variable features, which serves as the basis of our previously proposed taxonomy called DAGGTAX. By studying the implications of the DAGGTAX features, we formulate a set of constraints to be satisfied during design, which helps to check the correctness of the specifications and reduce the design space. We also provide a set of design heuristics that could help designers to decide the appropriate mechanisms for achieving the selected features. We apply DAGGTAX on industrial case studies, showing that DAGGTAX not only strengthens the understanding, but also serves as the foundation of a design tool which facilitates the model-driven design of data aggregation processes.

Concurrency control faults may lead to unwanted interleavings, and breach data consistency in distributed transaction systems. However, due to the unpredictable delays between sites, detecting concurrency control faults in distributed transaction systems is difficult. In this paper, we propose a methodology, relying on model-based testing and mutation testing, for designing test cases in order to detect such faults. The generated test inputs are designated delays between distributed operations, while the outputs are the occurrence of unwanted interleavings that are consequences of the concurrency control faults. We mutate the distributed transaction specification with common concurrency control faults, and model them as UPPAAL timed automata, in which designated delays are encoded as stopwatches. Test cases are generated via reachability analysis using UPPAAL Model Checker, and are selected to form an effective test suite. Our methodology can reduce redundant test cases, and find the appropriate delays to detect concurrency control faults effectively.

Many database management systems (DBMS) need to ensure atomicity and isolation of transactions for logical data consistency, as well as to guarantee temporal correctness of the executed transactions. Since the mechanisms for atomicity and isolation may lead to breaching temporal correctness, trade-offs between these properties are often required during the DBMS design. To be able to address this concern, we have previously proposed the pattern-based UPPCART framework, which models the transactions and the DBMS mechanisms as timed automata, and verifies the trade-offs with provable guarantee. However, the manual construction of UPPCART models can require considerable effort and is prone to errors. In this paper, we advance the formal analysis of atomic concurrent real-time transactions with tool-automated construction of UPPCART models. The latter are generated automatically from our previously proposed UTRAN specifications, which are high-level UML-based specifications familiar to designers. To achieve this, we first propose formal definitions for the modeling patterns in UPPCART, as well as for the pattern-based construction of DBMS models, respectively. Based on this, we establish a translational semantics from UTRAN specifications to UPPCART models, to provide the former with a formal semantics relying on timed automata, and develop a tool that implements the automated transformation. We also extend the expressiveness of UTRAN and UPPCART, to incorporate transaction sequences and their timing properties. We demonstrate the specification in UTRAN, automated transformation to UPPCART, and verification of the traded-off properties, via an industrial use case.

Although atomicity, isolation and temporal correctness are crucial to the dependability of many real-time database-centric systems, the selected assurance mechanism for one property may breach another. Trading off these properties requires to specify and analyze their dependencies, together with the selected supporting mechanisms (abort recovery, concurrency control, and scheduling), which is still insufficiently supported. In this paper, we propose a UML profile, called UTRAN, for specifying atomic concurrent real-time transactions, with explicit support for all three properties and their supporting mechanisms. We also propose a pattern-based modeling framework, called UPPCART, to formalize the transactions and the mechanisms specified in UTRAN, as UPPAAL timed automata. Various mechanisms can be modeled flexibly using our reusable patterns, after which the desired properties can be verified by the UPPAAL model checker. Our techniques facilitate systematic analysis of atomicity, isolation and temporal correctness trade-offs with guarantee, thus contributing to a dependable real-time database system.

Many industrial control systems manage critical data using Database Management Systems (DBMS). The correctness of transactions, especially their atomicity, isolation and temporal correctness, is essential for the dependability of the entire system. Existing methods and techniques, however, either lack the ability to analyze the interplay of these properties, or do not scale well for systems with large amounts of transactions and data, and complex transaction management mechanisms. In this paper, we propose to analyze large scale real-time database systems using statistical model checking. We propose a pattern-based framework, by extending our previous work, to model the real-time DBMS as a network of stochastic timed automata, which can be analyzed by UPPAAL Statistical Model Checker. We present an industrial case study, in which we design a collision avoidance system for multiple autonomous construction vehicles, via concurrency control of a real-time DBMS. The desired properties of the designed system are analyzed using our proposed framework.

Many Cyber-Physical Systems (CPSs) require both timeliness of computation and temporal consistency of their data. Therefore, when using real-time databases in a real-time CPS application, the Real-Time Database Management Systems (RTDBMSs) must ensure both transaction timeliness and temporal data consistency. RTDBMSs prevent unwanted interferences of concurrent transactions via concurrency control, which in turn has a significant impact on the timeliness and temporal consistency of data. Therefore it is important to verify, already at early design stages that these properties are not breached by the concurrency control. However, most often such early on guarantees of properties under concurrency control are missing. In this paper we show how to verify transaction timeliness and temporal data consistency using model checking. We model the transaction work units, the data and the concurrency control mechanism as a network of timed automata, and specify the properties in TCTL. The properties are then checked exhaustively and automatically using the UPPAAL model checker. 

In order to guarantee transaction timeliness, Realtime Database Management Systems (RTDBMSs) often relax data consistency by relaxing the ACID transaction properties. Such relaxation varies depending on the application and thus different transaction management mechanisms have to be decided for developing a tailored RTDBMS. However, current RTDBMSs development does not include systematic verification of timeliness and desired ACID properties. Consequently, the implemented transaction management mechanisms may breach timeliness of transactions. In this paper, we propose a process called DAGGERS for developing a tailored RTDBMS that guarantees timeliness and desired data consistency for real-time systems by employing model-checking techniques during the process. Based on the characteristics of the desired data manipulations, transaction models are designed and then formally verified iteratively together with selected run-time mechanisms, in order to achieve the desired/necessary trade-offs between timeliness and data consistency. The outcome of DAGGERS is thus a tailored transaction management with guaranteed appropriate trade-offs, as well as the model-checking based worst-case execution times and blocking times of transactions under these mechanisms and assumptions of the hardware architecture.

Efficient monitoring of a cloud system involves multiple aggregation processes and large amounts of data with various and interdependent requirements. A thorough understanding and analysis of the characteristics of data aggregation processes can help to improve the software quality and reduce development cost. In this paper, we propose a systematic approach for designing data aggregation processes in cloud monitoring systems. Our approach applies a feature-oriented taxonomy called DAGGTAX (Data AGGregation TAXonomy) to systematically specify the features of the designed system, and SAT-based analysis to check the consistency of the specifications. Following our approach, designers first specify the data aggregation processes by selecting and composing the features from DAGGTAX. These specified features, as well as design constraints, are then formalized as propositional formulas, whose consistency is checked by the Z3 SAT solver. To support our approach, we propose a design tool called SAFARE (SAt-based Feature-oriented dAta aggREgation design), which implements DAGGTAX-based specification of data aggregation processes and design constraints, and integrates the state-of-the-art solver Z3 for automated analysis. We also propose a set of general design constraints, which are integrated by default in SAFARE. The effectiveness of our approach is demonstrated via a case study provided by industry, which aims to design a cloud monitoring system for video streaming. The case study shows that DAGGTAX and SAFARE can help designers to identify reusable features, eliminate infeasible design decisions, and derive crucial system parameters.

Efficient auto-scaling of cloud resources relies on the monitoring of the cloud, which involves multiple aggregation processes and large amounts of data with various and interdependent requirements. A systematic way of describing the data together with the possible aggregations is beneficial for designers to reason about the properties of these aspects as well as their implications on the design, thus improving quality and lowering development costs. In this paper, we propose to apply DAGGTAX, a feature-oriented taxonomy for organizing common and variable data and aggregation process properties, to the design of cloud monitoring systems. We demonstrate the effectiveness of DAGGTAX via a case study provided by industry, which aims to design a cloud monitoring system that serves auto-scaling for a video streaming system. We design the cloud monitoring system by selecting and composing DAGGTAX features, and reason about the feasibility of the selected features. The case study shows that the application of DAGGTAX can help designers to identify reusable features, analyze trade-offs between selected features, and derive crucial system parameters.

In this paper the data-entity approach for efficientdesign-time management of run-time data in componentbasedreal-time embedded systems is presented. The approachformalizes the concept of a data entity which enabledesign-time modeling, management, documentationand analysis of run-time data items. Previous studies ondata management for embedded real-time systems showthat current data management techniques are not adequate,and therefore impose unnecessary costs and quality problemsduring system development. It is our conclusion thatdata management needs to be incorporated as an integralpart of the development of the entire system architecture.Therefore, we propose an approach where run-time datais acknowledged as first class objects during developmentwith proper documentation and where properties such asusage, validity and dependency can be modeled. In thisway we can increase the knowledge and understanding ofthe system. The approach also allows analysis of data dependencies,type matching, and redundancy early in the developmentphase as well as in existing systems.

We introduce the concept of database proxies intended to mitigate the gap between two disjoint productivity-enhancing techniques: Component Based Software Engineering (CBSE) and Real-Time Database Management Systems (RTDBMS). The two techniques promote opposing design goals and their coexistence is neither obvious nor intuitive. CBSE promotes encapsulation and decoupling of component internals from the component environment, whilst an RTDBMS provide mechanisms for efficient and predictable global data sharing. A component with direct access to an RTDBMS is dependent on that specific RTDBMS and may not be useable in an alternative environment. For components to remain encapsulated and reusable, database proxies decouple components from an underlying database residing in the component framework, while providing temporally predictable access to data maintained in a database. Our approach provide access to features such as extensive data modeling tools, predictable access to hard real-time data, dynamic access to soft real-time data using standardized queries and controlled data sharing; thus allowing developers to employ the full potential of both CBSE and an RTDBMS. Our approach primarily targets embedded systems with a subset of functionality with real-time requirements. The implementation results show that the benefits of using proxies do not come at the expense of significant run-time overheads or less accurate timing predictions.

This thesis presents new techniques for data management of run-time dataobjects in component-based embedded real-time systems. These techniquesenable data to be modeled, analyzed and structured to achieve proper datamanagement during development, maintenance  and execution.The evolution of real-time embedded systems has resulted in an increasedsystem complexity beyond what was thought possible just a few years ago.Over the years, new techniques and tools have been developed to managesoftware and communication complexity. However, as this thesis show, currenttechniques and tools for data management are not sufficient. Today,development of real-time embedded systems focuses on the function aspects ofthe system, in most cases disregarding data management.The lack of proper design-time data management often results in ineffectivedocumentation routines and poor overall system knowledge. Contemporarytechniques to manage run-time data do not satisfy demands on flexibility,maintainability and extensibility. Based on an industrial case-study thatidentifies a number of problems within current data management techniques,both during design-time and  run-time, it is clear that data managementneeds to be incorporated as an integral part of the development of theentire system architecture.As a remedy to the identified problems, we propose a design-time data entityapproach, where the importance of data in the system is elevated to beincluded in the entire design phase with proper documentation, properties,dependencies and analysis methods to increase the overall system knowledge.Furthermore, to efficiently manage data during run-time, we introducedatabase proxies to enable the fusion between two existing techniques;Component Based Software Engineering (CBSE) and Real-Time DatabaseManagement Systems (RTDBMS). A database proxy allows components to bedecoupled from the underlying data management strategy without violating thecomponent encapsulation and communication interface.

We introduce the concept of database proxies capable of mitigating the gap between two disjoint productivityenhancing techniques: Component Based Software Engineering (CBSE) and Real-Time Database Management Systems (RTDBMS). The coexistence of the two techniques is neither obvious nor intuitive since CBSE and RTDBMS promotes opposing design goals; CBSE promotes encapsulation and decoupling of component internals from the component environment, whilst RTDBMS provide mechanisms for efficient and predictable global data sharing. Database proxies decouple components from an underlying database residing in the component framework. This enables components to remain encapsulated and reusable, while providing temporally predictable access to data maintained in a database. We specifically target embedded systems with a subset of functionality with real-time requirements. Our implementation results show that the above benefits do not come at the expense of run-time overheads or less accurate timing predictions.

AUTOSAR has been introduced as a remedy for the increasing complexity and rising costs within automotive systems development. However, AUTOSAR does not provide sufficient support for the increased complexity with respect to data management. Database proxies have been presented as a promising solution to provide software component technologies with the capabilities of a state-of-the-art real-time database management system. In this paper, we show how an industrial AUTOSAR development environment can be extended to include support for real-time data management.

We propose to integrate a real-time databasemanagement system into the basic software of the AUTOSARcomponent model. This integration can be performed withoutviolating the fundamental principles of the component-basedapproach of the AUTOSAR standard. Our database-centricapproach allows developers to focus on application developmentinstead of reinventing data management techniques ordevelop solutions using internal data structures. We use stateof-the-art database pointer techniques to achieve predictabletiming, and database proxies to maintain component encapsulationand independence of data-management strategy. Thepaper illustrates the feasibility of our proposal when databaseproxies are used to manage the data communication betweencomponents and to perform run-time monitoring on the virtualfunction bus. Our implementation results show that the abovebenefits do not come at the expense of run-time overheadsor less accurate timing predictions. Under typical workloadconditions, our concept only introduces in the order of 4%CPU overhead.

Efficient design-time management and documentation of run-time data elements are of paramount importance when developing and maintaining modern real-time systems. In this paper, we present the results of an industrial case-study in which we have studied the state of practice in data management and documentation. Representatives from five companies within various business segments have been interviewed and our results show that various aspects of current data management and documentation are problematic and not yet mature. Results show that companies today have a fairly good management of distributed signals, while internal ECU signals and states are, in many cases, not managed at all. This lack of internal data management results in costly development and maintenance and is often entirely dependent of the know-how of single individual experts.

Furthermore, it has, in several cases, resulted in unused and excessive data in the systems due to the fact that

whether or not a data is used is unknown.

In this paper we present a technique to allow the use of

real-time database management together with componentbased

software development, to achieve an information centric

run-time platform for the development of embedded

real-time systems. The technique allows components to

benefit from the advantages of a real-time database management

system while still retaining desirable component

properties, such as isolation and a high level of reusability.

We propose that a database is integrated in the component

framework, and introduce the concept of database

proxies to decouple components from the database schema.

The resulting system fully benefits from the advantages of

component-based software development, such as reusability,

all component interaction through interfaces, etc, combined

with the advantages of a real-time database management

system, i.e., system openness, controlled data access,

and dynamic query language capabilities.

This paper introduces query mechanisms that allow automotive control-systems (using a distributed real-time database management system(RTDBMS)) to be queried, monitored and stimulated during run-time without violating its temporal properties. The mechanisms are completely transparent to the control application since they are handled by the RTDBMS. The COMET RTDBMS is extended with ad hoc capabilities to support the introduction of subscription and substitution queries, which are used for monitoring and stimulation. These queries are intended to be used by service and calibration tools to help in the development and maintenance of modern automotive systems. Using these queries could reduce development costs, result in higher quality of the system design and consequently yield higher reliability.

As the complexity of vehicle control-systems increases, the amount of information that these systems are intended to handle also increases. This thesis provides concepts relating to real-time database management systems to be used in such control-systems. By integrating a real-time database management system into a vehicle control-system, data management on a higher level of abstraction can be achieved. Current database management concepts are not sufficient for use in vehicles, and new concepts are necessary. A case-study at Volvo Construction Equipment Components AB in Eskilstuna, Sweden presented in this thesis, together with a survey of existing database platforms confirms this. The thesis specifically addresses data access issues by introducing; (i) a data access method, denoted database pointers, which enables data in a real-time database management system to be accessed efficiently. Database pointers, which resemble regular pointers variables, permit individual data elements in the database to be directly pointed out, without risking a violation of the database integrity. (ii) two concurrency-control algorithms, denoted 2V-DBP and 2V-DBP-SNAP which enable critical (hard real-time) and non-critical (soft real-time) data accesses to co-exist, without blocking of the hard real-time data accesses or risking unnecessary abortions of soft real-time data accesses. The thesis shows that 2V-DBP significantly outperforms a standard real-time concurrency control algorithm both with respect to lower response-times and minimized abortions. (iii) two concepts, denoted substitution and subscription queries that enable service- and diagnostics-tools to stimulate and monitor a control-system during run-time. The concepts presented in this thesis form a basis on which a data management concept suitable for embedded real-time systems, such as vehicle control-systems, can be built.

We present 2V-DBP-SNAP an algorithm that allows hard real-time tasks in an embedded real-time control system to read a snapshot of a number of data elements in a real-time database. Furthermore, 2V-DBP-SNAP allows these data elements to be shared with soft real-time tasks, which access them using a database query language, and with other hard real-time tasks that use database pointers. 2V-DBP-SNAP allows temporal behavior and memory consumption to be accurately predicted. Introducing snapshot transactions is beneficial for embedded control-systems, such as for engine control in an automotive system, since a snapshot of the state of the environment can be collected, e.g., the state of all cylinders in the engine. 2V-DBP-SNAP is lightweight and predictable, both with respect to computational and memory overhead, and is therefore highly suited for resource constrained systems.

We present a case study of a class of embedded hard real-time control applications in the vehicular industry which, in addition to meeting transaction and task deadlines, emphasize data validity requirements. We elaborate on how a database could be integrated into the studied application and how the database management system (DBMS) could be designed to suit this particular class of systems.

Memory corruption due to program faults is one of the most common failures in computer software. For software running in a sequential manner and for multi-tasking software with synchronized data accesses, it has been shown that program faults causing memory corruption can be detected by analyzing the relations between defines and uses of variables (DU coverage-based testing). However, using such methods in testing for memory corruption where globally shared data is accessed through asynchronous events will not be sufficient since they lack the possibility to analyse the cases where preemption of tasks may lead to interleaving failures. In this paper, we propose the use of a system level shared variable DU analysis of multi-tasking realtime software. By analyzing the temporal attributes of each access to globally shared data, our method handles asynchronous data accesses. When used in system-level testing, the result from the analysis can discover failures such as ordering, synchronization and interleaving failures. The result can also serve a as measure for coverage and complexity in data dependency at system level.

The paper presents Save-IDE, an Integrated Development Environment for thedevelopment of component-based embedded systems. Save-IDE supports efficient development of dependable embedded systems by providing tools for design of embedded software systems using a dedicated component model, formal specification and analysis of component and system behaviors already in early development phases, and a fully automated transformation of the system of components into an executable image.