Challenges in Preserving Intent Comprehensibility in Software

Software is not only difficult to create, but it is also difficult to understand. Even the authors themselves in a relatively short time become unable to readily interpret their own code and to explain what intent they have followed by it. Software is being created with the goal to satisfy the needs of a customer or directly of the end users. Out of these needs comes the intent, which is relatively well understandable to all stakeholders. By using other specialized modeling techniques (typically the UML language) or in the code itself, use cases and other high-level specification and analytical artifacts in common software development almost completely dissolve. Along with dedicated initiatives to improve preserving intent comprehensibility in software, such as literate programming, intentional programming, aspect-oriented programming, or the DCI (Data, Context and Interaction) approach, this issue is a subject of contemporary research in the re-revealed area of engaging end users in software development, which has its roots in Alan Kay's vision of a personal computer programmable by end users. From the perspective of the reality of complex software system development, the existing approaches are solving the problem of losing intent comprehensibility only partially by a simplified and limited perception of the intent and do this only at the code level. This paper explores the challenges in preserving the intent comprehensibility in software. The thorough treatment of this problem requires a number of techniques and approaches to be engaged, including preserving use cases in the code, dynamic code structuring, executable intent representation using domain specific languages, advanced UML modularization, 3D rendering of UML, and representation and animation of organizational patterns.