New ideas and emerging research: evaluating prediction system accuracy

BACKGROUND: Prediction e.g. of project cost is an important concern in software engineering. PROBLEM: Although many empirical validations of software engineering prediction systems have been published, no one approach dominates and sense-making of conflicting empirical results is proving challenging. METHOD: We propose a new approach to evaluating competing prediction systems based upon an unbiased statistic (Standardised Accuracy), analysis of results relative to the baseline technique of guessing and calculation of effect sizes. RESULTS: Two empirical studies are revisited and the published results are shown to be misleading when re-analysed using our new approach. CONCLUSION: Biased statistics such as MMRE are deprecated. By contrast our approach leads to valid results. Such steps will greatly assist in performing future meta-analyses

Six reasons for rejecting an industrial survey paper

Context: Despite their importance in any empirically based research program, industrial surveys are not very common in the software engineering literature. In our experience, a possible reason is their difficulty of publication. Goal: We would like to understand what are the issues that may prevent the publication of papers reporting industrial surveys. Method: In this preliminary work, we analyzed the surveys we conducted and extracted the main lessons learned in terms of issues and problems. Results: Most common critics posed to industrial surveys are: lack of novelty, limitation of the geographic scope and sampling issues. Conclusions: Most objections that led to reject a survey paper actually are not easy to overcome and others are not so serious. These objections could restrain researchers from conducting this type of studies that represent an important methodological asset. For these reasons, we think that reviewers should be less severe to judge survey papers provided that all the limitations of the study are well explained and highlighte

Research Findings on Empirical Evaluation of Requirements Specifications Approaches

Numerous software requirements specification (SRS) approaches have been proposed in software engineering. However, there has been little empirical evaluation of the use of these approaches in specific contexts. This paper describes the results of a mapping study, a key instrument of the evidence-based paradigm, in an effort to understand what aspects of SRS are evaluated, in which context, and by using which research method. On the basis of 46 identified and categorized primary studies, we found that understandability is the most commonly evaluated aspect of SRS, experiments are the most commonly used research method, and the academic environment is where most empirical evaluation takes place

Reflections on 'What do we Think we are Doing' 20-year Most Influential Paper award talk

My 1996 paper [1] challenged the VL community to ask What do we think we are doing? It might now be called a Systematic Literature Review, although formal procedures for SLR were not developed until later [5]. It made a textual analysis of publications in which authors described a cognitive rationale for VL research, observing that many relied on insights from folk psychology, from introspection, or speculative computer analogies to the brain. This was a study of metacognition – beliefs about one’s cognitive ability that shape the mental strategies we choose. In the case of programming language designers, the choices being shaped were not their own problem-solving strategies (something we all do), but the design rationale for new languages (which will affect others).Hitachi Lt

A literature review of expert problem solving using analogy

We consider software project cost estimation from a problem solving perspective. Taking a cognitive psychological approach, we argue that the algorithmic basis for CBR tools is not representative of human problem solving and this mismatch could account for inconsistent results. We describe the fundamentals of problem solving, focusing on experts solving ill-defined problems. This is supplemented by a systematic literature review of empirical studies of expert problem solving of non-trivial problems. We identified twelve studies. These studies suggest that analogical reasoning plays an important role in problem solving, but that CBR tools do not model this in a biologically plausible way. For example, the ability to induce structure and therefore find deeper analogies is widely seen as the hallmark of an expert. However, CBR tools fail to provide support for this type of reasoning for prediction. We conclude this mismatch between experts’ cognitive processes and software tools contributes to the erratic performance of analogy-based prediction

Customer purchase behavior prediction in E-commerce: a conceptual framework and research agenda

Digital retailers are experiencing an increasing number of transactions coming from their consumers online, a consequence of the convenience in buying goods via E-commerce platforms. Such interactions compose complex behavioral patterns which can be analyzed through predictive analytics to enable businesses to understand consumer needs. In this abundance of big data and possible tools to analyze them, a systematic review of the literature is missing. Therefore, this paper presents a systematic literature review of recent research dealing with customer purchase prediction in the E-commerce context. The main contributions are a novel analytical framework and a research agenda in the field. The framework reveals three main tasks in this review, namely, the prediction of customer intents, buying sessions, and purchase decisions. Those are followed by their employed predictive methodologies and are analyzed from three perspectives. Finally, the research agenda provides major existing issues for further research in the field of purchase behavior prediction online

Invited Panel: Evidence Based Practice (EBP) – The Problem and Challenges, The Need within IS research and practice, Open Access Publishing.

Launch of the ‘Journal for Evidence Based Information Systems’ (EBIS): An open access journal for IS researchers and practitioners – An independent journal in association with the UKAI

Costs, Benefits and Value Distribution – Ingredients for Successful Cross-Organizational ES Business Cases

This paper introduces my PhD research project on developing guidelines for creating successful business cases for Enterprise System implementations in network settings. Three important aspects that were found to be important in such business cases are: the costs, benefits and the value distribution within a network. Each of the three aspects is addressed in this paper and the relationships between them are pointed out. A research model is presented showing how all three aspects contribute to the main goal of defining successful business case guidelines

Tinjauan Pustaka Sistematic: Penerapan Metode Position Averaging Point Pada Computer Vision

Computer Vision adalah salah satu parameter penting untuk menghasilkan suatu sistem yang hampir mendekati dengan sistem visual manusia. Pada penelitian ini bertujuan untuk mengkaji Literatur Review terkait penerapan metode Position Averaging Point pada Computer Vision. Metode penelitian yang digunakan dalam penelitian ini menggunakan pendekatan paradigma Systematic Literature Review (SLR) terhadap jurnal yang sudah di publikasikan dari tahun 2016 sampai tahun 2022. Pengumpulan data dilakukan dengan mendokumentasikan dari berbagai sumber jurnal yang mempunyai penelitian serupa pada laporan penelitian. Jurnal yang diperoleh dari search engine dalam penelitian ini sebanyak 3 (tiga) jurnal dengan menggunakan aplikasi Google Chrome dengan situs Google Scholar. Berdasarkan penelitian ini didapatkan bahwa objek penerapan metode Positin Averaging Point pada Computer Vision pada penelitian ini banyak yang mengukur panjang dengan akurasi rata-rata ikan lele