Incorporating real world integrated circuit in a liberal arts computer science program

(1) Background: final year students of computer science engineering degrees must carry out a final degree project (FDP) in order to graduate. Students’ contributions to improve open source software (OSS) through FDPs can offer multiple benefits and challenges, both for the students, the instructors and for the project itself. This work reports on a practical experience developed by four students contributing to mature OSS projects during their FDPs, detailing how they addressed the multiple challenges involved, both from the students and teachers perspective. (2) Methods: we followed the work of four students contributing to two established OSS projects for two academic years and analyzed their work on GitHub and their responses to a survey. (3) Results: we obtained a set of specific recommendations for future practitioners and detailed a list of benefits achieved by steering FDP towards OSS contributions, for students, teachers and the OSS projects. (4) Conclusion: we find out that FDPs oriented towards enhancing OSS projects can introduce students into real-world, practical examples of software engineering principles, give them a boost in their confidence about their technical and communication skills and help them build a portfolio of contributions to daily used worldwide open source applications.

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Application of a Bayesian network to integrated circuit tester diagnosis

Artificial intelligence for engineering design analysis and manufacturing ◽

10.1017/s0890060400002080 ◽

1995 ◽

Vol 9 (1) ◽

pp. 51-65 ◽

Cited By ~ 5

Author(s):

Daniel Mittelstadt ◽

Robert Paasch ◽

Bruce D’Ambrosio

Keyword(s):

Expert System ◽

Real World ◽

Integrated Circuit ◽

Procedural Knowledge ◽

Knowledge Engineering ◽

Bayesian Belief Network ◽

Belief Networks ◽

Diagnostic Problem ◽

Ic Testing ◽

Time Limitations

AbstractResearch efforts to implement a Bayesian belief-network-based expert system to solve a real-world diagnostic problem – the diagnosis of integrated circuit (IC) testing machines – are described. The development of several models of the IC tester diagnostic problem in belief networks also is described, the implementation of one of these models using symbolic probabilistic inference (SPI) is outlined, and the difficulties and advantages encountered are discussed. It was observed that modeling with interdependencies in belief networks simplifies the knowledge engineering task for the IC tester diagnosis problem, by avoiding procedural knowledge and focusing on the diagnostic component’s interdependencies. Several general model frameworks evolved through knowledge engineering to capture diagnostic expertise that facilitated expanding and modifying the networks. However, model implementation was restricted to a small portion of the modeling, that of contact resistance failures, which were due to time limitations and inefficiencies in the prototype inference software we used. Further research is recommended to refine existing methods, in order to speed evaluation of the models created in this research. With this accomplished, a more complete diagnosis can be achieved.

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