On the Application of Formal Techniques for Dependable Concurrent Systems

The pervasiveness of computer systems in virtually every aspect of daily life entails a growing dependence on them. These systems have become integral parts of our societies as we continue to use and rely on them on a daily basis. This trend of digitalization is set to carry on, bringing forth the question of how dependable these systems are. Our dependence on these systems is in acute need for a justification based on rigorous and systematic methods as recommended by internationally recognized safety standards. Ensuring that the systems we depend on meet these recommendations is further complicated by the increasingly widespread use of concurrent systems, which are notoriously hard to analyze due to the substantial increase in complexity that the interactions between different processing entities engenders. In this thesis, we introduce improvements on existing formal analysis techniques to aid in the development of dependable concurrent systems. Applying formal analysis techniques can help us avoid incidents with catastrophic consequences by uncovering their triggering causes well in advance. This work focuses on three types of analyses: data-flow analysis, model checking and error propagation analysis. Data-flow analysis is a general static analysis technique aimed at predicting the values that variables can take at various points in a program. Model checking is a well-established formal analysis technique that verifies whether a program satisfies its specification. Error propagation analysis (EPA) is a dynamic analysis whose purpose is to assess a program's ability to withstand unexpected behaviors of external components. We leverage data-flow analysis to assist in the design of highly available distributed applications. Given an application, our analysis infers rules to distribute its workload across multiple machines, improving the availability of the overall system. Furthermore, we propose improvements to both explicit and bounded model checking techniques by exploiting the structure of the specification under consideration. The core idea behind these improvements lies in the ability to abstract away aspects of the program that are not relevant to the specification, effectively shortening the verification time. Finally, we present a novel approach to EPA based on symbolic modeling of execution traces. The symbolic scheme uses a dynamic sanitizing algorithm to eliminate effects of non-determinism in the execution traces of multi-threaded programs.The proposed approach is the first to achieve a 0% rate of false positives for multi-threaded programs. The work in this thesis constitutes an improvement over existing formal analysis techniques that can aid in the development of dependable concurrent systems, particularly with respect to availability and safety

Block-level test scheduling under power dissipation constraints

As dcvicc technologies such as VLSI and Multichip Module (MCM) become mature, and larger and denser memory ICs arc implemented for high-performancc digital systems, power dissipation becomes a critical factor and can no longer be ignored cither in normal operation of the system or under test conditions. One of the major considerations in test scheduling is the fact that heat dissipated during test application is significantly higher than during normal operation (sometimes 100 - 200% higher). Therefore, this is one of the recent major considerations in test scheduling. Test scheduling is strongly related to test concurrency. Test concurrency is a design property which strongly impacts testability and power dissipation. To satisfy high fault coverage goals with reduced test application time under certain power dissipation constraints, the testing of all components on the system should be performed m parallel to the greatest extent possible. Some theoretical analysis of this problem has been carried out, but only at IC level. The problem was basically described as a compatible test clustering, where the compatibility among tests was given by test resource and power dissipation conflicts at the same time. From an implementation point of view this problem was identified as an Non-Polynomial (NP) complete problem In this thesis, an efficient scheme for overlaying the block-tcsts, called the extended tree growing technique, is proposed together with classical scheduling algorithms to search for power-constrained blocktest scheduling (PTS) profiles m a polynomial time Classical algorithms like listbased scheduling and distribution-graph based scheduling arc employed to tackle at high level the PTS problem. This approach exploits test parallelism under power constraints. This is achieved by overlaying the block-tcst intervals of compatible subcircuits to test as many of them as possible concurrently so that the maximum accumulated power dissipation is balanced and does not exceed the given limit. The test scheduling discipline assumed here is the partitioned testing with run to completion. A constant additive model is employed for power dissipation analysis and estimation throughout the algorithm

Model based test suite minimization using metaheuristics

Software testing is one of the most widely used methods for quality assurance and fault detection purposes. However, it is one of the most expensive, tedious and time consuming activities in software development life cycle. Code-based and specification-based testing has been going on for almost four decades. Model-based testing (MBT) is a relatively new approach to software testing where the software models as opposed to other artifacts (i.e. source code) are used as primary source of test cases. Models are simplified representation of a software system and are cheaper to execute than the original or deployed system. The main objective of the research presented in this thesis is the development of a framework for improving the efficiency and effectiveness of test suites generated from UML models. It focuses on three activities: transformation of Activity Diagram (AD) model into Colored Petri Net (CPN) model, generation and evaluation of AD based test suite and optimization of AD based test suite. Unified Modeling Language (UML) is a de facto standard for software system analysis and design. UML models can be categorized into structural and behavioral models. AD is a behavioral type of UML model and since major revision in UML version 2.x it has a new Petri Nets like semantics. It has wide application scope including embedded, workflow and web-service systems. For this reason this thesis concentrates on AD models. Informal semantics of UML generally and AD specially is a major challenge in the development of UML based verification and validation tools. One solution to this challenge is transforming a UML model into an executable formal model. In the thesis, a three step transformation methodology is proposed for resolving ambiguities in an AD model and then transforming it into a CPN representation which is a well known formal language with extensive tool support. Test case generation is one of the most critical and labor intensive activities in testing processes. The flow oriented semantic of AD suits modeling both sequential and concurrent systems. The thesis presented a novel technique to generate test cases from AD using a stochastic algorithm. In order to determine if the generated test suite is adequate, two test suite adequacy analysis techniques based on structural coverage and mutation have been proposed. In terms of structural coverage, two separate coverage criteria are also proposed to evaluate the adequacy of the test suite from both perspectives, sequential and concurrent. Mutation analysis is a fault-based technique to determine if the test suite is adequate for detecting particular types of faults. Four categories of mutation operators are defined to seed specific faults into the mutant model. Another focus of thesis is to improve the test suite efficiency without compromising its effectiveness. One way of achieving this is identifying and removing the redundant test cases. It has been shown that the test suite minimization by removing redundant test cases is a combinatorial optimization problem. An evolutionary computation based test suite minimization technique is developed to address the test suite minimization problem and its performance is empirically compared with other well known heuristic algorithms. Additionally, statistical analysis is performed to characterize the fitness landscape of test suite minimization problems. The proposed test suite minimization solution is extended to include multi-objective minimization. As the redundancy is contextual, different criteria and their combination can significantly change the solution test suite. Therefore, the last part of the thesis describes an investigation into multi-objective test suite minimization and optimization algorithms. The proposed framework is demonstrated and evaluated using prototype tools and case study models. Empirical results have shown that the techniques developed within the framework are effective in model based test suite generation and optimizatio