Some issues in the 'archaeology' of software evolution

During a software project's lifetime, the software goes through many changes, as components are added, removed and modified to fix bugs and add new features. This paper is intended as a lightweight introduction to some of the issues arising from an `archaeological' investigation of software evolution. We use our own work to look at some of the challenges faced, techniques used, findings obtained, and lessons learnt when measuring and visualising the historical changes that happen during the evolution of software

Some issues in the 'archaeology' of software evolution

During a software project's lifetime, the software goes through many changes, as components are added, removed and modified to fix bugs and add new features. This paper is intended as a lightweight introduction to some of the issues arising from an `archaeological' investigation of software evolution. We use our own work to look at some of the challenges faced, techniques used, findings obtained, and lessons learnt when measuring and visualising the historical changes that happen during the evolution of software

Analysis and improvement of business process models using spreadsheets

Software in general is thoroughly analyzed before it is released to its users. Business processes often are not - at least not as thoroughly as it could be - before they are released to their users, e.g., employees or software agents. This paper ascribes this practice to the lack of suitable instruments for business process analysts, who design the processes, and aims to provide them with the necessary instruments to allow them to also analyze their processes. We use the spreadsheet paradigm to represent business process analysis tasks, such as writing metrics and assertions, running performance analysis and verification tasks, and reporting on the outcomes, and implement a spreadsheet-based tool for business process analysis. The results of two independent user studies demonstrate the viability of the approach

Simulation of rapid loading systems in iron ore mines

In the mining industry, it is observed that sudden break-down of any equipment may stop the entire system, resulting in drastic production losses and enhancing the cost production. In this paper, the probability of sudden break down of each equipment are individually analyzed from their previous performances where the frequency of occurrences, duration and the time-interval of each breakdown has given an additional stress and the non-availability of that equipment on the entire system is discussed. Computerized best fit matching is found out for preventive maintenance of this equipment by developing different sub-routines and simulation models. Optimum utilization of those equipment shows a particular steady- state production from the mine. Advanced technology is used for the operation of the open-pit mining. Hazard due to open cast mining is less than that of underground mines and the recent trend is to adopt the former one. For the mechanization, different types of machineries are used, such as shovel, dumper, dozer, drill machines, etc. use of more machineries increases the complexity of the operation and as a result it is very difficult to the proper matching of these equipment’s. As these machineries are very costly so unless they are properly matched, reduction in production cost is not possible. Sudden breakdown of one equipment may stop the production from whole mine. So it is needed to analyze the breakdown data by statistical approach to find out the possibility of breakdown of that particular equipment and ask for preventive maintenance. This analysis needed the help of computer for simulating the whole mining system to judge the performance of each equipment. This paper deals with the computerized best fit matching, for preventive maintenance of equipment

A Twenty-Year Look at “Computational Geology,” an Evolving, In-Discipline Course in Quantitative Literacy at the University of South Florida

Since 1996, the Geology (GLY) program at the USF has offered “Computational Geology” as part of its commitment to prepare undergraduate majors for the quantitative aspects of their field. The course focuses on geological-mathematical problem solving. Over its twenty years, the course has evolved from a GATC (geometry-algebra-trigonometry-calculus) in-discipline capstone to a quantitative literacy (QL) course taught within a natural science major. With the formation of the new School of Geosciences in 2013, the merging departments re-examined their various curricular programs. An online survey of the Geology Alumni Society found that “express quantitative evidence in support of an argument” was more favorably viewed as a workplace skill (4th out of 69) than algebra (51st), trig (55th) and calculus 1 and 2 (59th and 60th). In that context, we decided to find out from successful alumni, “What did you get out of Computational Geology?” To that end, the first author carried out a formal, qualitative research study (narrative inquiry protocol), whereby he conducted, recorded, and transcribed semi-structured interviews of ten alumni selected from a list of 20 provided by the second author. In response to “Tell me what you remember from the course,” multiple alumni volunteered nine items: Excel (10 out of 10), Excel modules (8), Polya problem solving (5), “important” (4), unit conversions (4), back-of-the-envelope calculations (4), gender equality (3). In response to “Is there anything from the course that you used professionally or personally since graduating?” multiple alumni volunteered seven items: Excel (9 out of 10), QL/thinking (6), unit conversions (5), statistics (5), Excel modules (3), their notes (2). Outcome analysis from the open-ended comments arising from structured questions led to the identification of alumni takeaways in terms of elements of three values: (1) understanding and knowledge (facts such as conversion factors, and concepts such as proportions and log scales); (2) abilities and skills (communication, Excel, unit conversions); and (3) traits and dispositions (problem solving, confidence, and QL itself). The overriding conclusion of this case study is that QL education can have a place in geoscience education where the so-called context of the QL is interesting because it is in the students’ home major, and that such a course can be tailored to any level of program prerequisites