Syntactic-Semantic Incrementality for Agile Verification

Abstract Modern software systems are continuously evolving, often because systems requirements change over time. Responding to requirements changes is one of the principles of agile methodologies. In this paper we envision the seamless integration of automated verification techniques within agile methodologies, thanks to the support for incrementality. Incremental verification accommodates the changes that occur within the schedule of frequent releases of software agile processes. We propose a general approach to developing families of verifiers that can support incremental verification for different kinds of artifacts and properties. The proposed syntactic-semantic approach is rooted in operator precedence grammars and their support for incremental parsing. Incremental verification procedures are encoded as attribute grammars, whose incremental evaluation goes hand in hand with incremental parsing

Syntactic-Semantic Incrementality for Agile Verification

Abstract Modern software systems are continuously evolving, often because systems requirements change over time. Responding to requirements changes is one of the principles of agile methodologies. In this paper we envision the seamless integration of automated verification techniques within agile methodologies, thanks to the support for incrementality. Incremental verification accommodates the changes that occur within the schedule of frequent releases of software agile processes. We propose a general approach to developing families of verifiers that can support incremental verification for different kinds of artifacts and properties. The proposed syntactic-semantic approach is rooted in operator precedence grammars and their support for incremental parsing. Incremental verification procedures are encoded as attribute grammars, whose incremental evaluation goes hand in hand with incremental parsing

A Syntactic-Semantic Approach to Incremental Verification

Software verification of evolving systems is challenging mainstream methodologies and tools. Formal verification techniques often conflict with the time constraints imposed by change management practices for evolving systems. Since changes in these systems are often local to restricted parts, an incremental verification approach could be beneficial. This paper introduces SiDECAR, a general framework for the definition of verification procedures, which are made incremental by the framework itself. Verification procedures are driven by the syntactic structure (defined by a grammar) of the system and encoded as semantic attributes associated with the grammar. Incrementality is achieved by coupling the evaluation of semantic attributes with an incremental parsing technique. We show the application of SiDECAR to the definition of two verification procedures: probabilistic verification of reliability requirements and verification of safety properties.Comment: 22 pages, 8 figures. Corrected typo

Syntax-driven program verification of matching logic properties

We describe a novel approach to program verification and its application to verification of C programs, where properties are expressed in matching logic. The general approach is syntax-directed: semantic rules, expressed according to Knuths attribute grammars, specify how verification conditions can be computed. Evaluation is performed by interplaying attribute computation and propagation through the syntax tree with invocation of a solver of logic formulae. The benefit of a general syntax-driven approach is that it provides a reusable reference scheme for implementing verifiers for different languages. We show that the instantiation of a general approach to a specific language does not penalize the efficiency of the resulting verifier. This is done by comparing our C verifier for matching logic with an existing tool for the same programming language and logic. A further key advantage of the syntax-directed approach is that it can be the starting point for an incremental verifier -- which is our long-term research target

Enhancing Reuse of Constraint Solutions to Improve Symbolic Execution

Constraint solution reuse is an effective approach to save the time of constraint solving in symbolic execution. Most of the existing reuse approaches are based on syntactic or semantic equivalence of constraints; e.g. the Green framework is able to reuse constraints which have different representations but are semantically equivalent, through canonizing constraints into syntactically equivalent normal forms. However, syntactic/semantic equivalence is not a necessary condition for reuse--some constraints are not syntactically or semantically equivalent, but their solutions still have potential for reuse. Existing approaches are unable to recognize and reuse such constraints. In this paper, we present GreenTrie, an extension to the Green framework, which supports constraint reuse based on the logical implication relations among constraints. GreenTrie provides a component, called L-Trie, which stores constraints and solutions into tries, indexed by an implication partial order graph of constraints. L-Trie is able to carry out logical reduction and logical subset and superset querying for given constraints, to check for reuse of previously solved constraints. We report the results of an experimental assessment of GreenTrie against the original Green framework, which shows that our extension achieves better reuse of constraint solving result and saves significant symbolic execution time.Comment: this paper has been submitted to conference ISSTA 201

formal methods and agile development towards a happy marriage

Change makes software different from any other artifact created by humans. Although this is known since the 1970s, change is still often handled in an ad hoc manner. Agile development and, more recently, DevOps have been proposed as a solution, and success stories are reported from industry. Still, principled and rigorous foundations that can be taught, practiced, and systematically replicated are lacking. We argue that change has to become a first-class concept and that the development tools used by engineers and the run time environment supporting software execution should be structured in a way that naturally accommodates change. We distinguish between evolution and adaptation and discuss how software can be made self-adaptive, and how it can cooperate with humans in-the-loop, supporting continuous verification and assuring dependability. We discuss how several research approaches that were investigated in the past decade may be integrated and extended in a roadmap of future work leading to progress in tool support and automation to achieve dependable adaptation and evolution

Parallel parsing made practical

The property of local parsability allows to parse inputs through inspecting only a bounded-length string around the current token. This in turn enables the construction of a scalable, data-parallel parsing algorithm, which is presented in this work. Such an algorithm is easily amenable to be automatically generated via a parser generator tool, which was realized, and is also presented in the following. Furthermore, to complete the framework of a parallel input analysis, a parallel scanner can also combined with the parser. To prove the practicality of a parallel lexing and parsing approach, we report the results of the adaptation of JSON and Lua to a form fit for parallel parsing (i.e. an operator-precedence grammar) through simple grammar changes and scanning transformations. The approach is validated with performance figures from both high performance and embedded multicore platforms, obtained analyzing real-world inputs as a test-bench. The results show that our approach matches or dominates the performances of production-grade LR parsers in sequential execution, and achieves significant speedups and good scaling on multi-core machines. The work is concluded by a broad and critical survey of the past work on parallel parsing and future directions on the integration with semantic analysis and incremental parsing

Continuous Reasoning: Scaling the impact of formal methods

This paper describes work in continuous reasoning, where formal reasoning about a (changing) codebase is done in a fashion which mirrors the iterative, continuous model of software development that is increasingly practiced in industry. We suggest that advances in continuous reasoning will allow formal reasoning to scale to more programs, and more programmers. The paper describes the rationale for continuous reasoning, outlines some success cases from within industry, and proposes directions for work by the scientific community

DFKI Workshop on Natural Language Generation

On the Saarbrücken campus sites as well as at DFKI, many research activities are pursued in the field of Natural Language Generation (NLG). We felt that too little is known about the total of these activities and decided to organize a workshop in order to share ideas and promote the results. This DFKI workshop brought together local researchers working on NLG. Several papers are co-authored by international researchers. Although not all NLG activities are covered in the present document, the papers reviewed for this workshop clearly demonstrate that Saarbrücken counts among the important NLG sites in the world