Ivo Krka

An architecture-driven software mobility framework

Software architecture has been shown to provide an appropriate level of granularity for assessing a software systems quality attributes (e.g., performance and dependability). Similarly, previous research has adopted an architecture-centric approach to reasoning about and managing the run-time adaptation of software systems. For mobile and pervasive software systems, which are known to be innately dynamic and unpredictable, the ability to assess a systems quality attributes and manage its dynamic run-time behavior is especially important. In the past, researchers have argued that a software architecture-based approach can be instrumental in facilitating mobile computing. In this paper, we present an integrated architecture-driven framework for modeling, analysis, implementation, deployment, and run-time migration of software systems executing on distributed, mobile, heterogeneous computing platforms. In particular, we describe the frameworks support for dealing with the challenges posed by both logical and physical mobility. We also provide an overview of our experience with applying the framework to a family of distributed mobile robotics systems. This experience has verified our envisioned benefits of the approach, and has helped us to identify several avenues of future work.

Using dynamic execution traces and program invariants to enhance behavioral model inference

Software behavioral models have proven useful for design, validation, verification, and maintenance. However, existing approaches for deriving such models sometimes overgeneralize what behavior is legal. We outline a novel approach that utilizes inferred likely program invariants and method invocation sequences to obtain an object-level model that describes legal execution sequences. The key insight is using program invariants to identify similar states in the sequences. We exemplify how our approach improves upon certain aspects of the state-of-the-art FSA-inference techniques.

Synthesizing partial component-level behavior models from system specifications

Initial system specifications, such as use-case scenarios and properties, only partially specify the future system. We posit that synthesizing partial component-level behavior models from these early specifications can improve software development practices. In this paper, we provide a novel algorithm for deriving a Modal Transition System (MTS) for individual system components from system-level scenario and property specifications. The generated MTSs capture the possible component implementations that (1) necessarily provide the behavior required by the scenarios, (2) restrict behavior forbidden by the properties, and (3) leave the behavior that is neither explicitly required nor forbidden as undefined. We also show how our algorithm helps to discover potential design flaws.

Scalable and Accurate Prediction of Availability of Atomic Web Services

The modern information systems on the Internet are often implemented as composite services built from multiple atomic services. These atomic services have their interfaces publicly available while their inner structure is unknown. The quality of the composite service is dependent on both the availability of each atomic service and their appropriate orchestration. In this paper, we present LUCS, a formal model for predicting the availability of atomic web services that enhances the current state-of-the-art models used in service recommendation systems. LUCS estimates the service availability for an ongoing request by considering its similarity to prior requests according to the following dimensions: the users and services geographic location, the service load, and the services computational requirements. In order to evaluate our model, we conducted experiments on services deployed in different regions of the Amazon cloud. For each service, we varied the geographic origin of its incoming requests as well as the request frequency. The evaluation results suggest that our model significantly improves availability prediction when all of the LUCS input parameters are available, reducing the prediction error by 71 percent compared to the current state-of-the-art.

Engineering Heterogeneous Robotics Systems: A Software Architecture-Based Approach

RoboPrism, a framework that supports software-architecture-based development of robotic systems, is accessible to nonexperts in robotics, deals effectively with heterogeneity in distributed and mobile robotics systems, and facilitates adaptation in complex, dynamic environments.

Hierarchical Label Propagation and Discovery for Machine Generated Email

Machine-generated documents such as email or dynamic web pages are single instantiations of a pre-defined structural template. As such, they can be viewed as a hierarchy of template and document specific content. This hierarchical template representation has several important advantages for document clustering and classification. First, templates capture common topics among the documents, while filtering out the potentially noisy variabilities such as personal information. Second, template representations scale far better than document representations since a single template captures numerous documents. Finally, since templates group together structurally similar documents, they can propagate properties between all the documents that match the template. In this paper, we use these advantages for document classification by formulating an efficient and effective hierarchical label propagation and discovery algorithm. The labels are propagated first over a template graph (constructed based on either term-based or topic-based similarities), and then to the matching documents. We evaluate the performance of the proposed algorithm using a large donated email corpus and show that the resulting template graph is significantly more compact than the corresponding document graph and the hierarchical label propagation is both efficient and effective in increasing the coverage of the baseline document classification algorithm. We demonstrate that the template label propagation achieves more than 91% precision and 93% recall, while increasing the label coverage by more than 11%.

A Comprehensive Exploration of Challenges in Architecture-Based Reliability Estimation

A plasma processing apparatus such as a plasma etching apparatus, which is not subject to arcing to the gas distributor plate which is caused by secondary potentials generated by polymers adhering to a gas distribution plate. The gas distribution plate is electrically isolated from the ground electric potential, and does not have any polarity. The gas distribution plate may be formed of an insulating material. Furthermore, a support plate may be adapted to fix the gas distribution plate to a chamber of the apparatus in such a manner that the gas distribution plate is detachably coupled with the support plate. Thereby, it is easier to separate the gas distribution plate from the apparatus to remove the accumulated polymers during the plasma process.

Architecture-level reliability prediction of concurrent systems

Stringent requirements on modern software systems dictate evaluation of dependability qualities, such as reliability, as early as possible in a systems life cycle. A primary shortcoming of the existing design-time reliability prediction approaches is their lack of support for modeling and analyzing concurrency in a scalable way. To address the scalability challenge, we propose SHARP, an architecture-level reliability prediction framework that analyzes a hierarchical scenario-based specification of system behavior. It achieves scalability by utilizing the scenario relations embodied in this hierarchy. SHARP first constructs and solves models of basic scenarios, and combines the obtained results based on the defined scenario dependencies; the dependencies we handle are sequential and parallel execution of multiple scenarios. This process iteratively continues through the scenario hierarchy until finally obtaining the system reliability estimate. Our evaluations performed on real-world specifications indicate that SHARP is (a) almost as accurate as a traditional non-hierarchical method, and (b) more scalable than other existing techniques.

From system specifications to component behavioral models

Early system specifications, such as use-case scenarios and properties, rarely completely specify the system. Partial models of system-level behavior, derived from these specifications, have proven useful in early system analysis. We believe that the scope of possible analyses can be enhanced by utilizing component-level partial models. In this paper, we outline an algorithm for deriving a component-level Modal Transition System (MTS) from system-level scenario and property specifications. The generated MTSs capture the possible component implementations that (1) necessarily provide the behavior required by the scenarios, (2) restrict behavior forbidden by the properties, and (3) leave the behavior that is neither explicitly required nor forbidden as undefined. We discuss how these generated models can help discover system-design flaws, support requirements elicitation, and help select off-the-shelf components.

The anatomy and physiology of the grid revisited

In this paper, we revisit the widely cited domain-specific software architecture (DSSA) for the domain of grid computing We have comprehensively studied 18 grid systems over the past five years, observing that, while individual grid systems are widely used and deemed successful, the grid DSSA is underspecified and makes it difficult to pinpoint what makes a software system a grid. Inspired by this conclusion, we describe our work-in-progress towards answering this important question.