Incorporating Data into EFSM Inference

This is the author accepted manuscript. The final version is available from Springer Verlag via the DOI in this record17th International Conference, SEFM 2019 Oslo, Norway, September 18–20, 2019Models are an important way of understanding software systems. If they do not already exist, then we need to infer them from system behaviour. Most current approaches infer classical FSM models that do not consider data, thus limiting applicability. EFSMs provide a way to concisely model systems with an internal state but existing inference techniques either do not infer models which allow outputs to be computed from inputs, or rely heavily on comprehensive white-box traces that reveal the internal program state, which are often unavailable. In this paper, we present an approach for inferring EFSM models, including functions that modify the internal state. Our technique uses black-box traces which only contain information visible to an external observer of the system. We implemented our approach as a prototype

Inference of Extended Finite State Machines

This is the final version. Available from AFP via the link in this recordIn this AFP entry, we provide a formal implementation of a state-merging technique to infer extended finite state machines (EFSMs), complete with output and update functions, from black-box traces. In particular, we define the subsumption in context relation as a means of determining whether one transition is able to account for the behaviour of another. Building on this, we define the direct subsumption relation, which lifts the subsumption in context relation to EFSM level such that we can use it to determine whether it is safe to merge a given pair of transitions. Key proofs include the conditions necessary for subsumption to occur and that subsumption and direct subsumption are preorder relations. We also provide a number of different heuristics which can be used to abstract away concrete values into registers so that more states and transitions can be merged and provide proofs of the various conditions which must hold for these abstractions to subsume their ungeneralised counterparts. A Code Generator setup to create executable Scala code is also defined

Active inference of EFSMs without reset

Extended finite state machines (EFSMs) model stateful systems with internal data variables, and have many software engineering applications, including system analysis and test case generation. Where such models are not available, it is desirable to reverse engineer them by observing system behaviour, but existing approaches are either limited to classical FSM models with no internal data state, or implicitly require the ability to reset the system under inference, which may not always be possible. In this paper, we present an extension to the hW-inference algorithm that can infer EFSM models, complete with guards and internal data update functions, from systems without a reliable reset, although there are currently some restrictions on the type of system and model

APPLICATION AND REFINEMENTS OF THE REPS THEORY FOR SAFETY CRITICAL SOFTWARE

With the replacement of old analog control systems with software-based digital control systems, there is an urgent need for developing a method to quantitatively and accurately assess the reliability of safety critical software systems. This research focuses on proposing a systematic software metric-based reliability prediction method. The method starts with the measurement of a metric. Measurement results are then either directly linked to software defects through inspections and peer reviews or indirectly linked to software defects through empirical software engineering models. Three types of defect characteristics can be obtained, namely, 1) the number of defects remaining, 2) the number and the exact location of the defects found, and 3) the number and the exact location of defects found in an earlier version. Three models, Musa's exponential model, the PIE model and a mixed Musa-PIE model, are then used to link each of the three categories of defect characteristics with reliability respectively. In addition, the use of the PIE model requires mapping defects identified to an Extended Finite State Machine (EFSM) model. A procedure that can assist in the construction of the EFSM model and increase its repeatability is also provided. This metric-based software reliability prediction method is then applied to a safety-critical software used in the nuclear industry using eleven software metrics. Reliability prediction results are compared with the real reliability assessed by using operational failure data. Experiences and lessons learned from the application are discussed. Based on the results and findings, four software metrics are recommended. This dissertation then focuses on one of the four recommended metrics, Test Coverage. A reliability prediction model based on Test Coverage is discussed in detail and this model is further refined to be able to take into consideration more realistic conditions, such as imperfect debugging and the use of multiple testing phases

A comprehensive approach to the euro-area debt crisis

The euro area‘s sovereign debt crisis continues though significant steps have been taken to resolve it. This paper proposes a comprehensive solution to the crisis based on three pillars: a plan to restore banking sector soundness in the whole euro area, a resolution of sovereign debt crisis -including a revision of EU assistance facilities and a reduction of the Greek public debt- and a strategy to foster growth and competitiveness. The paper provides novel estimates and analysis focusing on the current situation of Greece, Ireland, Portugal and Spain

Reverse-engineering EFSMs with data dependencies

EFSMs provide a way to model systems with internal data variables. In situations where they do not already exist, we need to infer them from system behaviour. A key challenge here is inferring the functions which relate inputs, outputs, and internal variables. Existing approaches either work with white-box traces, which expose variable values, or rely upon the user to provide heuristics to recognise and generalise particular data-usage patterns. This paper presents a preprocessing technique for the inference process which generalises the concrete values from the traces into symbolic functions which calculate output from input, even when this depends on values not present in the original traces. Our results show that our technique leads to more accurate models than are produced by the current state-of-the-art and that somewhat accurate models can still be inferred even when the output of particular transitions depends on values not present in the original traces

An Online Agent-Based Search Approach in Automated Computer Game Testing with Model Construction

The complexity of computer games is ever increasing. In this setup, guiding an automated test algorithm to find a solution to solve a testing task in a game's huge interaction space is very challenging. Having a model of a system to automatically generate test cases would have a strong impact on the effectiveness and efficiency of the algorithm. However, manually constructing a model turns out to be expensive and time-consuming. In this study, we propose an online agent-based search approach to solve common testing tasks when testing computer games that also constructs a model of the system on-the-fly based on the given task, which is then exploited to solve the task. To demonstrate the efficiency of our approach, a case study is conducted using a game called Lab Recruits