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The aim of this paper is to briefly explore creative thinking in computer science, and compare it to natural sciences, mathematics or engineering. It is also meant as polemics with some theses of the pioneer work under the same title by Daniel Saunders and Paul Thagard because I point to important motivations in computer science the authors do not mention, and give examples of the origins of problems they explicitly deny. Computer science is a very specific field for it relates the abstract, theoretical discipline – mathematics, on the one hand, and engineering, often concerned with very practical tasks of building computers, on the other. It is like engineering in that it is concerned with solving practical problems or implementing solutions, often with strongly financial reasons, e.g. increasing a company's income. It is like mathematics in that is deals with abstract symbols, logical relations, algorithms, computability problems, etc. Saunders and Thagard analyse rich experimental material from historical and contemporary work in computer science and argue that, as opposed to natural sciences, computer science is not concerned with describing and explaining natural phenomena. Now, I argue that there is a field of research in artificial intelligence (which, in turn, is a branch of computer science), called machine discovery, where explanation of natural phenomena, finding experimental laws and explanatory models is the primary goal. This goal is achieved by constructing computer systems whose job is to simulate various processes involved in scientific discovery done by human researchers, and help them in making new discoveries. On the other hand, motivations that give rise to ingenious projects in computer science can be very strange and include curiosity, fun or attempts to be famous out of boring, stable life of a successful programmer in a big corporation. A good example is the phenomenon of open-source software, especially the development of the Linux operating system and its applications when, from economical point of view, Microsoft absolutely dominated the software market of personal computers.

DBLP (https://dblp.org/) is a comprehensive collection of computer science publications from major and minor journals and conference proceedings. From this dump, we remove arXiv preprints. Our dataset consists of 1.9 million publications from 1970 to 2014 that are authored by 1.1 million authors. We have added citations among publications by combining DBLP with the AMiner dataset (https://www.aminer.org/citation) via publication titles and years. There are 6.6 million citations among publications. Author names in DBLP are disambiguated. To infer the gender of authors, we have used a method that combines the results of name-based and image-based gender detection services. Since the accuracy is very low for Chinese and Korean names, we label their gender as unknown to reduce noise in our analysis.

Info and entertainment goes digital -- Lights, cameras, coding: computer science in television and film -- On the air: computer science in radio -- Low tech goes high tech: computer science in publishing -- Reaching the masses: computer science in new media.

Historical Overview -- Office Information Systems Engineering -- Update Languages vs. Query Languages -- OPUS: An Extensible Optimizer for Up-to-Date Database Systems -- A Hyperlcon Interface to a Blackboard System for Planning Research Projects -- Chusaurus: A Writing Tool Resource for Non-Native Users of English -- Trends in Representing the Semantics of Natural Language Sentences: A Comparative Study -- Extending Partial Evaluation in Logic Programming -- Modules, Macros and Lisp -- Using Filters to Improve the Efficiency of Game-Playing Learning Procedures -- An O(n2.5) Time Heuristic Algorithm for a Class of Large Weighted Edge Colouring Problem -- Randomized Sorting of Shuffled Monotone Sequences -- A Classification of Quadratic Algorithms for Multiplying Polynomials of Small Degree Over Finite Fields -- An Algorithm for Computing Multivariate Polynomial Resultants -- New Absorbing and Ergodic Doubly-Linked List Reorganizing Heuristics -- Skip Sort-An Adaptive Randomized Algorithm or Expected Time Adaptivity is Best -- Data Structures and Access Methods for Read-Only Optical Disks -- Mixed-Radix Huffman Codes -- A Schema Manipulation Mechanism for an OODB Model -- Versions in the Context of Object-Oriented Database Systems -- Ddraw: An Object-Oriented Design Tool -- A Graphical Interactive Object-Oriented Development System -- A Concurrent Object-Oriented Paradigm for Attribute Grammars -- Preserving Distributed Data Coherence Using Asynchronous Broadcasts -- An Implementation of Service Rebalancing -- Bit Optimal Distributed Consensus -- An Efficient Distributed Termination -- Allocating Modules to Processors in a Distributed System with Limited Memory -- The Complexity of Algorithmic Problems on Succint Instances (Invited paper -- Parallel Algorithms for NP-Complete Problems (Invited paper -- Parallel Search in Sorted Multisets, and NP-Complete Problems -- Towards Understanding the Effective Parallelization of Sequential Algorithms -- On the Density of the Probabilistic Polynomial Classes -- Modelling and Simulation of a Pseudosystolic Processor for Matrix Algorithms -- The Caracas Multiprocessor System -- A New Communication Systems Architecture Supporting Migration to OSI -- Modelling and Analysis of Time Critical Applications on Local Area Networks -- Matrix Multiplication on Digital Signal Processors and Hierarchical Memory Systems -- Author Index.

This thesis investigates computer science student projects and some of the processes involved in the running of such projects. The reason for this investigation is that there are some interesting claims concerning the use of projects as learning approach. For example, they are supposed to give an extra challenge to the students and prepare them for working life, by adding known development methods from industry the sense of reality is emphasized, and involving industry partners as mock clients also increases the feeling of reality, but still unclear if these features contribute to the students' learning and what can be done to increase the potential for learning. There are thus interesting pedagogical challenges with computer science student projects. There is a need to better understand the effects on learning outcomes as a function of how a student project is designed. The focus in this thesis is on the effects of role taking in the project groups, work allocation, and goal setting in student projects. In this thesis, three studies investigating different aspects of processes in computer science student projects are presented. A number of conclusions are drawn, which serve as a starting point for further research. The first study investigates how power is distributed within a group of students in a full semester computer science project course. Perceived competence of fellow students contributes to personal influence in the student project groups, and three qualitatively different ways of experiencing competence among other students have been identified. The second study investigates experiences of the process of decision-making in a full semester computer science project course. Six categories describing the experience of decision-making have been identified spanning from the experience of decision-making in individual decisions too small and unimportant to handle by anyone else than the individual to the experience of decision-making as a democratic process involving both the full group and the context in which the group acts. The third study investigates Swedish engineering students' conceptions of engineering, where dealing with problems and their solutions and creativity are identified as core concepts. Subject concepts, as math, and physics do not appear in any top position. "Math", for example, accounts for only five percent of the total mentioned engineering terms. "Physics", the second highest ranked subject term, only accounts for circa 1 percent. By combining the results from the three studies, four central areas of general interest for designing and running student projects have been identified. These four features are: 1) the mechanism for work allocation; 2) students connection to external stakeholders; 3) focus on result or process; and 4) level of freedom in the project task. These four features are related to the results from the three studies in this thesis. The thesis is concluded by proposing an analytical framework based on those four features. The intention with the framework is to provide a useful tool for the analysis and development of future computer science student projects.