Factors Influencing the Software Development Process in Small Scale Industries
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Software development is a complex process which is divided into many phases. According to the software type and industries the development process is restructured. During the entire development what are the main factors which is influencing the process and affecting the quality. The main objective of this study is to focus on factors influencing the development process and how it affects the small scale industries after coming in to the real practice.
 Entire Software development is a layered process in which different factors are responsible to get the best products. This paper is focused on different technical and non-technical influencing factors which give major impact on the software quality. With influencing factors, their applicability in small scale industries also studied.
 Three important technical factors i.e. SDLC model and its principles, Cost estimation and Risk parameter whereas two important influencing factors in non-technical.i.e. success factors and environmental factors. Non-technical factors more influencing than technical factors. 
 All technical and non-technical factors have their own role but to apply all these quality parameters in small scale industries we need to make them more easy for their applicability. If quality development process and its parameters are tuned to easy and affordable level more businessmen will shift from manual working environment to the digital working environment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it