Automated measurement of API usability: The API Concepts Framework

Scheller, Thomas; Kühn, Eva

doi:10.1016/j.infsof.2015.01.009

Cited by 56 publications

(50 citation statements)

References 26 publications

(82 reference statements)

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“…Aesthetic and minimalist design -It might seem obvious that a smaller and less complex API is likely to be more usable. One empirical study did find that for classes, the number of other classes in the same package/namespace had an influence on the success of finding the desired one [20]. However, we found no correlation between the number of elements in an API and its usability, as long as they had appropriate names and were well-organized [25].…”

Section: Evaluating the Api Designcontrasting

confidence: 63%

“…For example, adding more different kinds of objects that can be drawn does not necessarily complicate a graphics package, and adding convenience constructors that take different sets of parameters can improve usability [20]. An important factor seems to be having distinct prefixes for the different method names, so they can easily differentiated by typing a small number of characters for code-completion in the editor [20]. 9.…”

Section: Evaluating the Api Designmentioning

confidence: 99%

“…For example, one tool can evaluate APIs against a set of nine metrics including looking for: method overloaded but with different return types, too many parameters in a row with the same types, and consistency of parameter orderings across different methods [18]. Similarly, the API Concepts Framework takes the context of use into account because it evaluates both the API and samples of code using the API [20]. It can measure a variety of metrics already mentioned, including whether multiple methods have the same prefix (and thus may be annoying to use in code completion menus) and the use of the factory pattern.…”

Section: Evaluating the Api Designmentioning

confidence: 99%

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Improving API usability

2016

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Section: Evaluating the Api Designcontrasting

confidence: 63%

Section: Evaluating the Api Designmentioning

confidence: 99%

Section: Evaluating the Api Designmentioning

confidence: 99%

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Improving API usability

2016

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“…API usability and design is also discussed by Myers and Stylos in [32]. Scheller [43] tries to automatically measure the usability of API in terms of interface complexity -complexity of methods, constructors, fields, etc. Sawant studied how APIs are used [42] and developed a meta-model of API usage.…”

Section: Api Analysismentioning

confidence: 99%

API Evolution and Compatibility: A Data Corpus and Tool Evaluation.

Jezek¹,

Dietrich²

2017

JOT

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The development of software components with independent release cycles is nowadays widely supported by multiple languages and frameworks. A critical feature of any such platform is to safeguard composition by ensuring backward compatibility of substituted components. In recent years, some tooling has been developed to help developers and DevOps engineers to establish whether components are backward compatible by means of static analysis. We investigate the state of the art in this space by benchmarking such tools for Java. For this purpose, we have developed a compact benchmark data set of less than 200KB. Using this dataset, we study possible API changes of Java libraries, and whether the tools investigated can detect them. We find that only a small number of tools suitable to analyse API evolution exist. Those tools are only infrequently maintained by small communities. All tools investigated have some shortcomings in that they fail to detect certain API incompatibilities.

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“…50 The result was: "the PeerSpace.net framework is better suited to implement complex distributed systems than the SOA-focused WCF framework, however, even in case of SOA patterns like request/multiple-response the PeerSpace could keep up and even surpass the WCF framework's API usability". 49 We plan to carry out further usability studies in the future work.…”

Section: Peer Modelmentioning

confidence: 99%

Reusable Coordination Components: Reliable Development of Cooperative Information Systems

Kühn

2016

Int. J. Coop. Info. Syst.

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Today's emerging trends like factory of the future, big data, Internet-of-things, intelligent traffic solutions, cyber-physical systems, wireless sensor networks, smart home, smart city and smart grid raise new challenges on software development. They are characterized by high concurrency, distribution and dynamics as well as huge numbers of heterogeneous devices, resources and users that must collaborate in a reliable way. The management of the interactions and dependencies between the participants is a complex task posing massive coordination problems. The here proposed approach is twofold: (i) to analyze similarities in the communication and synchronization behavior of such applications and to identify coordination patterns; and (ii) to give a precise specification of them by means of a suitable coordination model which enables the development of coordination pattern-based software components as solutions. The vision is to compose advanced cooperative information systems from proven, configurable, reusable, generic components that run on a suitable target platform, in order to reduce software development time, risks and costs. In this paper we delimit the idea of "coordination patterns" from other related pattern approaches and motivate the need for a well-defined model to specify them. Several coordination models to achieve this goal are discussed, and the advantages of a new coordination model termed the "Peer Model" are pointed out. The feasibility of the approach to identify coordination patterns, to model them and to provide generic components that can be reused in different scenarios through configuration and composition is evaluated by means of a coordination pattern found in several industrial use cases.

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Automated measurement of API usability: The API Concepts Framework

Cited by 56 publications

References 26 publications

Improving API usability

Improving API usability

API Evolution and Compatibility: A Data Corpus and Tool Evaluation.

Reusable Coordination Components: Reliable Development of Cooperative Information Systems

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