Inevitably, reading is one of the requirements to be undergone. To improve the performance and quality, someone needs to have something new every day. It will suggest you to have more inspirations, then. However, the needs of inspirations will make you searching for some sources. Even from the other people experience, internet, and many books. Books and internet are the recommended media to help you improving your quality and performance.

Feature-Oriented Software Product Lines

This paper presents algorithms for the automatic synthesis of real-time controllers by finding a winning strategy for certain games defined by the timed-automata of Alur and Dill. In such games, the outcome depends on the players' actions as well as on their timing. We believe that these results will pave the way for the application of program synthesis techniques to the construction of real-time embedded systems from their specifications.

On the synthesis of discrete controllers for timed systems

Software-product-line engineering has gained considerable momentum in recent years, both in industry and in academia. A software product line is a family of software products that share a common set of features. Software product lines challenge traditional analysis techniques, such as type checking, model checking, and theorem proving, in their quest of ensuring correctness and reliability of software. Simply creating and analyzing all products of a product line is usually not feasible, due to the potentially exponential number of valid feature combinations. Recently, researchers began to develop analysis techniques that take the distinguishing properties of software product lines into account, for example, by checking feature-related code in isolation or by exploiting variability information during analysis. The emerging field of product-line analyses is both broad and diverse, so it is difficult for researchers and practitioners to understand their similarities and differences. We propose a classification of product-line analyses to enable systematic research and application. Based on our insights with classifying and comparing a corpus of 123 research articles, we develop a research agenda to guide future research on product-line analyses.

https://www.infosun.fim.uni-passau.de/publications/docs/TAK14.pdf

A Classification and Survey of Analysis Strategies for Software Product Lines

This paper provides a comprehensive survey of Machine Learning Testing (ML testing) research. It covers 138 papers on testing properties (e.g., correctness, robustness, and fairness), testing components (e.g., the data, learning program, and framework), testing workflow (e.g., test generation and test evaluation), and application scenarios (e.g., autonomous driving, machine translation). The paper also analyses trends concerning datasets, research trends, and research focus, concluding with research challenges and promising research directions in machine learning testing.

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Machine Learning Testing: Survey, Landscapes and Horizons

We apply a model checker to the problem of test generation using a new application of mutation analysis. We define syntactic operators, each of which produces a slight variation on a given model. The operators define a form of mutation analysis at the level of the model checker specification. A model checker generates countersamples which distinguish the variations from the original specification. The countersamples can easily be turned into complete test cases, that is, with inputs and expected results. We define two classes of operators: those that produce test cases from which a correct implementation must differ, and those that produce test cases with which it must agree. There are substantial advantages to combining a model checker with mutation analysis. First, test case generation is automatic; each countersample is a complete test case. Second, in sharp contrast to program-based mutation analysis, equivalent mutant identification is also automatic. We apply our method to an example specification and evaluate the resulting test sets with coverage metrics on a Java implementation.

Using Model Checking to Generate Tests from Specifications | NIST

The premise of variability-intensive systems, specifically in software product line engineering, is the ability to produce a large family of different systems efficiently. Many such systems are critical. Thorough quality assurance techniques are thus required. Unfortunately, most quality assurance techniques were not designed with variability in mind. They work for single systems, and are too costly to apply to the whole system family. In this paper, we propose an efficient automata-based approach to linear time logic (LTL) model checking of variability-intensive systems. We build on earlier work in which we proposed featured transitions systems (FTSs), a compact mathematical model for representing the behaviors of a variability-intensive system. The FTS model checking algorithms verify all products of a family at once and pinpoint those that are faulty. This paper complements our earlier work, covering important theoretical aspects such as expressiveness and parallel composition as well as more practical things like vacuity detection and our logic feature LTL. Furthermore, we provide an in-depth treatment of the FTS model checking algorithm. Finally, we present SNIP, a new model checker for variability-intensive systems. The benchmarks conducted with SNIP confirm the speedups reported previously.

Featured Transition Systems: Foundations for Verifying Variability-Intensive Systems and Their Application to LTL Model Checking

We present SNIP, an efficient model checker for software product lines (SPLs). Variability in software product lines is generally expressed in terms of features, and the number of potential products is exponential in the number of features. Whereas classical model checkers are only capable of checking properties against each individual product in the product line, SNIP exploits specifically designed algorithms to check all products in a single step. This is done by using a concise mathematical structure for product line behaviour, that exploits similarities and represents the behaviour of all products in a compact manner. Specification of an SPL in SNIP relies on the combination of two specification languages: TVL to describe the variability in the product line, and fPromela to describe the behaviour of the individual products. SNIP is thus one of the first tools equipped with specification languages to formally express both the variability and the behaviours of the products of the product line. The paper assesses SNIP and suggests that this is the first model checker for SPLs that can be used outside the academic arena.

/pdf/model-checking-software-product-lines-with-snip-33byztojge.pdf

Model checking software product lines with SNIP

Model checking techniques for software product lines (SPL) are actively researched. A major limitation they currently have is the inability to deal efficiently with non-Boolean features and multi-features. An example of a non-Boolean feature is a numeric attribute such as maximum number of users which can take different numeric values across the range of SPL products. Multi-features are features that can appear several times in the same product, such as processing units which number is variable from one product to another and which can be configured independently. Both constructs are extensively used in practice but currently not supported by existing SPL model checking techniques. To overcome this limitation, we formally define a language that integrates these constructs with SPL behavioural specifications. We generalize SPL model checking algorithms correspondingly and evaluate their applicability. Our results show that the algorithms remain efficient despite the generalization.

https://hal.inria.fr/hal-01087792/document

Beyond boolean product-line model checking: dealing with feature attributes and multi-features

Software Product Lines (SPLs) are families of similar software products built from a common set of features. As the number of products of an SPL is potentially exponential in the number of its features, the model checking problem is harder than for single software. A practical way to face this exponential blow-up is to reuse common behaviour between products. We previously introduced Featured Transition Systems (FTS), a mathematical model that serves as a basis for efficient SPL model checking techniques. In this paper, we present ProVeLines, a product line of verifiers for SPLs that incorporates the results of over three years of research on formal verification of SPLs. Being itself a product line, our tool is flexible and extensible, and offers a wide range of solutions for SPL modelling and verification.

/pdf/provelines-a-product-line-of-verifiers-for-software-product-4ht5qzkxur.pdf

ProVeLines: a product line of verifiers for software product lines

Software Product Line (SPL) engineering is a software engineering paradigm that exploits the commonality between similar software products to reduce life cycle costs and time-to-market. Many SPLs are critical and would benefit from efficient verification through model checking. Model checking SPLs is more difficult than for single systems, since the number of different products is potentially huge. In previous work, we introduced Featured Transition Systems (FTS), a formal, compact representation of SPL behaviour, and provided efficient algorithms to verify FTS. Yet, we still face the state explosion problem, like any model checking-based verification. Model abstraction is the most relevant answer to state explosion. In this paper, we define a novel simulation relation for FTS and provide an algorithm to compute it. We extend well-known simulation preservation properties to FTS and thus lay the theoretical foundations for abstraction-based model checking of SPLs. We evaluate our approach by comparing the cost of FTS-based simulation and abstraction with respect to product-by-product methods. Our results show that FTS are a solid foundation for simulation-based model checking of SPL.

https://hal.inria.fr/hal-01087659/document

Maxime Cordy

Papers

Featured Transition Systems: Foundations for Verifying Variability-Intensive Systems and Their Application to LTL Model Checking

Model checking software product lines with SNIP

Beyond boolean product-line model checking: dealing with feature attributes and multi-features

ProVeLines: a product line of verifiers for software product lines

Simulation-based abstractions for software product-line model checking