Probabilistic Model Checking for Energy Analysis in Software Product Lines

In a software product line (SPL), a collection of software products is defined by their commonalities in terms of features rather than explicitly specifying all products one-by-one. Several verification techniques were adapted to establish temporal properties of SPLs. Symbolic and family-based model checking have been proven to be successful for tackling the combinatorial blow-up arising when reasoning about several feature combinations. However, most formal verification approaches for SPLs presented in the literature focus on the static SPLs, where the features of a product are fixed and cannot be changed during runtime. This is in contrast to dynamic SPLs, allowing to adapt feature combinations of a product dynamically after deployment. The main contribution of the paper is a compositional modeling framework for dynamic SPLs, which supports probabilistic and nondeterministic choices and allows for quantitative analysis. We specify the feature changes during runtime within an automata-based coordination component, enabling to reason over strategies how to trigger dynamic feature changes for optimizing various quantitative objectives, e.g., energy or monetary costs and reliability. For our framework there is a natural and conceptually simple translation into the input language of the prominent probabilistic model checker PRISM. This facilitates the application of PRISM's powerful symbolic engine to the operational behavior of dynamic SPLs and their family-based analysis against various quantitative queries. We demonstrate feasibility of our approach by a case study issuing an energy-aware bonding network device.Comment: 14 pages, 11 figure

SPEEDY: An Eclipse-based IDE for invariant inference

SPEEDY is an Eclipse-based IDE for exploring techniques that assist users in generating correct specifications, particularly including invariant inference algorithms and tools. It integrates with several back-end tools that propose invariants and will incorporate published algorithms for inferring object and loop invariants. Though the architecture is language-neutral, current SPEEDY targets C programs. Building and using SPEEDY has confirmed earlier experience demonstrating the importance of showing and editing specifications in the IDEs that developers customarily use, automating as much of the production and checking of specifications as possible, and showing counterexample information directly in the source code editing environment. As in previous work, automation of specification checking is provided by back-end SMT solvers. However, reducing the effort demanded of software developers using formal methods also requires a GUI design that guides users in writing, reviewing, and correcting specifications and automates specification inference.Comment: In Proceedings F-IDE 2014, arXiv:1404.578

A Low-Overhead Script Language for Tiny Networked Embedded Systems

With sensor networks starting to get mainstream acceptance, programmability is of increasing importance. Customers and field engineers will need to reprogram existing deployments and software developers will need to test and debug software in network testbeds. Script languages, which are a popular mechanism for reprogramming in general-purpose computing, have not been considered for wireless sensor networks because of the perceived overhead of interpreting a script language on tiny sensor nodes. In this paper we show that a structured script language is both feasible and efficient for programming tiny sensor nodes. We present a structured script language, SCript, and develop an interpreter for the language. To reduce program distribution energy the SCript interpreter stores a tokenized representation of the scripts which is distributed through the wireless network. The ROM and RAM footprint of the interpreter is similar to that of existing virtual machines for sensor networks. We show that the interpretation overhead of our language is on par with that of existing virtual machines. Thus script languages, previously considered as too expensive for tiny sensor nodes, are a viable alternative to virtual machines