The Problem of Justification of Empirical Hypotheses in Software Testing

Angius, Nicola

doi:10.1007/s13347-014-0159-6

Cited by 12 publications

(10 citation statements)

References 27 publications

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“…Model-based hypotheses concerning future computations of a represented software system are tested up to a certain time fixed by testers; they are assigned a probabilistic evaluation according to statistical estimations of future incorrect executions based on past observed failures (Littlewood and Strigini 2000). Accordingly, they assume the epistemological status of probabilistic statements that are corroborated by failed attempts of falsification (Angius 2014) .…”

Section: Discovering Empirical Theories Of Software Systemsmentioning

confidence: 99%

Discovering Empirical Theories of Modular Software Systems. An Algebraic Approach

Angius

Stefaneas

2016

Synthese Library

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This paper is concerned with the construction of theories of software systems yielding adequate predictions of their target systems' computations. It is first argued that mathematical theories of programs are not able to provide predictions that are consistent with observed executions. Empirical theories of software systems are here introduced semantically, in terms of a hierarchy of computational models that are supplied by formal methods and testing techniques in computer science. Both deductive top-down and inductive bottom-up approaches in the discovery of semantic software theories are refused to argue in favour of the abductive process of hypothesising and refining models at each level in the hierarchy, until they become satisfactorily predictive. Empirical theories of computational systems are required to be modular, as modular are most software verification and testing activities. We argue that logic relations must be thereby defined among models representing different modules in a semantic theory of a modular software system. We exclude that scientific structuralism is able to define module relations needed in software modular theories. The algebraic Theory of Institutions is finally introduced to specify the logic structure of modular semantic theories of computational systems.

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Section: Discovering Empirical Theories Of Software Systemsmentioning

confidence: 99%

Discovering Empirical Theories of Modular Software Systems. An Algebraic Approach

Angius

Stefaneas

2016

Synthese Library

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“…Thereby, the types of hypotheses formulated in digital forensics are similar to those formulated in software testing because both digital forensics and software testing are idiographically oriented towards what is unique (not towards what is universally general). For this reason, the meta-scientific methodological considerations about the problem of justification of empirical hypotheses in software testing [1] should also be studied carefully by digital forensic theoreticians.…”

Section: Related Workmentioning

confidence: 99%

Notions of Hypothesis in Digital Forensics

Tewelde¹,

Grüner²,

Olivier³

2015

IFIP Advances in Information and Communication Technology

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With the growing scientification of the discipline of digital forensics, the notion of "scientific hypothesis" is becoming increasingly important, because all empirical science is hypothetical, not apodictic. Although the word "hypothesis" is used widely in the digital forensics literature, its usage is not sufficiently reflected from a philosophy of science point of view. This chapter discusses this problem with particular reference to Carrier's methodological work in which the notion of hypothesis plays a prominent role.

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“…The target paper stresses that, even in this case, there still remain executions that are not analysed. However, one is here in the similar situation in which only those behaviours of an empirical system that falsify a given hypothesis are observed: both scientific experiments and software tests are theory-laden in so far as tested behaviours are only those that are likely to falsify the hypothesis or the specification, respectively (Angius 2014). The authors suggest that software tests are not exploratory (Franklin 1989), and many executions remain untested; yet, the same happens with scientific experiments in NSIS: a scientific experiment is, by definition, a set of biased observations that are not exhaustive (Bunge 1998, pp.…”

Section: The Problem Of Induction In Software Intensive Sciencementioning

confidence: 99%

“…The probabilities involved increase or decrease as new executions are observed. The software reliability estimation process involves a Bayesian confirmation of hypotheses on softwareintensive systems which characterises common statistical approaches in science (Angius 2014).…”

Section: The Problem Of Induction In Software Intensive Sciencementioning

confidence: 99%

Computational Idealizations in Software Intensive Science: a Comment on Symons’ and Horner’s paper

Angius

2014

Philos. Technol.

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This commentary on John Symons' and Jack Horner's paper, besides sharing its main argument, challenges the authors' statement that there is no effective method to evaluate software-intensive systems as a distinguishing feature of software intensive science. It is underlined here how analogous methodological limitations characterise the evaluations of empirical systems in non-software intensive sciences. The authors' claim that formal methods establish the correctness of computational models rather than of the represented programme is here compared with the empirical adequacy problem typifying the model-based reasoning approach in physics, and the remark that testing all the paths of a software-intensive system is unfeasible is related to the enumerative induction problem in the justification of empirical law-like hypotheses in non-software intensive sciences.

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The Problem of Justification of Empirical Hypotheses in Software Testing

Cited by 12 publications

References 27 publications

Discovering Empirical Theories of Modular Software Systems. An Algebraic Approach

Discovering Empirical Theories of Modular Software Systems. An Algebraic Approach

Notions of Hypothesis in Digital Forensics

Computational Idealizations in Software Intensive Science: a Comment on Symons’ and Horner’s paper

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