Proving Correctness of Imperative Programs by Linearizing Constrained Horn Clauses

We present a method for verifying the correctness of imperative programs which is based on the automated transformation of their specifications. Given a program prog, we consider a partial correctness specification of the form $\{\varphi\}$ prog $\{\psi\}$, where the assertions $\varphi$ and $\psi$ are predicates defined by a set Spec of possibly recursive Horn clauses with linear arithmetic (LA) constraints in their premise (also called constrained Horn clauses). The verification method consists in constructing a set PC of constrained Horn clauses whose satisfiability implies that $\{\varphi\}$ prog $\{\psi\}$ is valid. We highlight some limitations of state-of-the-art constrained Horn clause solving methods, here called LA-solving methods, which prove the satisfiability of the clauses by looking for linear arithmetic interpretations of the predicates. In particular, we prove that there exist some specifications that cannot be proved valid by any of those LA-solving methods. These specifications require the proof of satisfiability of a set PC of constrained Horn clauses that contain nonlinear clauses (that is, clauses with more than one atom in their premise). Then, we present a transformation, called linearization, that converts PC into a set of linear clauses (that is, clauses with at most one atom in their premise). We show that several specifications that could not be proved valid by LA-solving methods, can be proved valid after linearization. We also present a strategy for performing linearization in an automatic way and we report on some experimental results obtained by using a preliminary implementation of our method.Comment: To appear in Theory and Practice of Logic Programming (TPLP), Proceedings of ICLP 201

The evolution of tropos: Contexts, commitments and adaptivity

Software evolution is the main research focus of the Tropos group at University of Trento (UniTN): how do we build systems that are aware of their requirements, and are able to dynamically reconfigure themselves in response to changes in context (the environment within which they operate) and requirements. The purpose of this report is to offer an overview of ongoing work at UniTN. In particular, the report presents ideas and results of four lines of research: contextual requirements modeling and reasoning, commitments and goal models, developing self-reconfigurable systems, and requirements awareness

Transforming timing diagrams into knowledge acquisition in automated specification

Requirements engineering is an important part of developing programs. It is an essential stage of the software development process that defines what a product or system should to achieve. The UML Timing diagram and Knowledge Acquisition in Automated Specification (KAOS) model are requirements engineering techniques. KAOS is a goal-oriented requirements approach while the Timing diagram is a graphical notation used for explaining software timing requirements. KAOS uses linear temporal logic (LTL) to describe time constraints in goal and operation models. Similarly, the Timing diagram can describe some temporal operators such as X (next), U (until) and R (release) over some period of time. Thus, our aim is to use the Timing diagram to generate parts of a KAOS model. In this paper we demonstrate techniques for creating a KAOS goal model from a Timing diagram. The Timing diagram which is used in this paper is adapted from the UML 2.0 Timing diagram and includes features to support translation into KAOS. We use a case study of a Lift system as an example to explain the translation processes described here