Computer Factors

2021 ◽  
pp. 277-299
Author(s):  
Harold Thimbleby

Understanding how computers can avoid bugs and mistakes is the first step towards programming safer and more dependable systems. This chapter introduces some important modern software engineering ideas that help make safer digital systems.

2021 ◽  
Author(s):  
Marisa Leavitt Cohn

This chapter examines how debates about the (im)materiality of software comes to inhabit the practices of software engineering work who manage the temporality of obsolescence and its entanglement with their own careers, language proficiencies, and expertise during the lifetimes of systems they develop or maintain. It describes how bodies of code endure materially in ways that exceed their formal understanding, revealing how the hardwiring of temporality into digital systems takes place through a moral economy of software work that devalues of code as it ages and obsolesces. The habitus of the programmer is set within a disciplinary regime that sustains the imaginary of software as immaterial, infinitely flexible and malleable in spite of routine encounters with its material recalcitrance.


2020 ◽  
Vol 43 ◽  
Author(s):  
Valerie F. Reyna ◽  
David A. Broniatowski

Abstract Gilead et al. offer a thoughtful and much-needed treatment of abstraction. However, it fails to build on an extensive literature on abstraction, representational diversity, neurocognition, and psychopathology that provides important constraints and alternative evidence-based conceptions. We draw on conceptions in software engineering, socio-technical systems engineering, and a neurocognitive theory with abstract representations of gist at its core, fuzzy-trace theory.


Author(s):  
T. A. Dodson ◽  
E. Völkl ◽  
L. F. Allard ◽  
T. A. Nolan

The process of moving to a fully digital microscopy laboratory requires changes in instrumentation, computing hardware, computing software, data storage systems, and data networks, as well as in the operating procedures of each facility. Moving from analog to digital systems in the microscopy laboratory is similar to the instrumentation projects being undertaken in many scientific labs. A central problem of any of these projects is to create the best combination of hardware and software to effectively control the parameters of data collection and then to actually acquire data from the instrument. This problem is particularly acute for the microscopist who wishes to "digitize" the operation of a transmission or scanning electron microscope. Although the basic physics of each type of instrument and the type of data (images & spectra) generated by each are very similar, each manufacturer approaches automation differently. The communications interfaces vary as well as the command language used to control the instrument.


Author(s):  
N. K. Jha ◽  
S. Gupta
Keyword(s):  

IEE Review ◽  
1992 ◽  
Vol 38 (3) ◽  
pp. 112
Author(s):  
Stuart Bennett

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