The tierless implementations use just two conceptually-similar \glspl{DSL} embedded in the same host language, and a single paradigm (\cref{table_t4t:languages,table_t4t:paradigms}). In contrast, the tiers in \gls{PRS} and \gls{PWS} use six or more very different languages, and both imperative and declarative paradigms. Multiple languages are commonly used in other typical software systems like web stacks, e.g.\ a recent survey of open source projects reveals that on average at least five different languages are used \citep{mayer2015empirical}. Interoperating components in multiple languages and paradigms raises a plethora of issues.
-Interoperation \emph{increases the cognitive load on the developer} who must simultaneously think in multiple languages and paradigms. This is commonly known as semantic friction or impedance mismatch \citep{ireland2009classification}. A simple illustration of this is that the tiered \gls{PRS} source code comprises some 38 source and configuration files, whereas the tierless \gls{CRS} requires just 3 files (\cref{table_t4t:multi}). The source could be structured as a single file, but to separate concerns is structured into three modules, one each for \glspl{SDS}, types, and control logic \citep{wang_maintaining_2018}.
+Interoperation \emph{increases the cognitive load on the developer} who must simultaneously think in multiple languages and paradigms. This is commonly known as semantic friction or impedance mismatch \citep{ireland_classification_2009}. A simple illustration of this is that the tiered \gls{PRS} source code comprises some 38 source and configuration files, whereas the tierless \gls{CRS} requires just 3 files (\cref{table_t4t:multi}). The source could be structured as a single file, but to separate concerns is structured into three modules, one each for \glspl{SDS}, types, and control logic \citep{wang_maintaining_2018}.
The developer must \emph{correctly interoperate the components}, e.g.\ adhere to the \gls{API} or communication protocols between components. The interoperation often entails additional programming tasks like marshalling or demarshalling data between components. For example, in the tiered \gls{PRS} and \gls{PWS} architectures, \gls{JSON} is used to serialise and deserialise data strings from the \gls{PYTHON} collector component before storing the data in the Redis database (\cref{lst_t4t:json}).
%e.g.\ to marshall and demarshall data between components.
% Phil: so widely known that a citation is unnecessary \citep{madsen1990strong}.
That said, many distributed system components written in languages that primarily use static typing, like \gls{HASKELL} and Scala, use some dynamic typing, e.g.\ to ensure that the data arriving in a message has the anticipated type \citep{epstein2011towards,gupta2012akka}.
-In a typical tiered multi-language \gls{IOT} system the developer must integrate software in different languages with very different type systems, and potentially executing on different hardware. The challenges of maintaining type safety have long been recognised as a major component of the semantic friction in multi-language systems, e.g.\ \citep{ireland2009classification}.
+In a typical tiered multi-language \gls{IOT} system the developer must integrate software in different languages with very different type systems, and potentially executing on different hardware. The challenges of maintaining type safety have long been recognised as a major component of the semantic friction in multi-language systems, e.g.\ \citep{ireland_classification_2009}.
Even if the different languages used in two components are both strongly typed, they may attribute, often quite subtly, different types to a value. Such type errors can lead to runtime errors, or the application silently reporting erroneous data. Such errors can be hard to find. Automatic detection of such errors is sometimes possible, but requires an addition tool like Jinn \citep{Jinn,Furr2005}.
%Such errors can be hard to debug, partly because there is very limited tool support for detecting them
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